Effects of buffering properties and undissociated acid concentration on dissolution of dental enamel in relation to pH and acid type

To quantify the relationships between buffering properties and acid erosion and hence improve models of erosive potential of acidic drinks, a pH-stat was used to measure the rate of enamel dissolution in solutions of citric, malic and lactic acids, with pH 2.4-3.6 and with acid concentrations adjusted to give buffer capacities (β) of 2-40 (mmol·l(-1))·pH(-1) for each pH. The corresponding undissociated acid concentrations, [HA], and titratable acidity to pH 5.5 (TA5.5) were calculated. In relation to β, the dissolution rate and the strength of response to β varied with acid type (lactic > malic ≥ citric) and decreased as pH increased. The patterns of variation of the dissolution rate with TA5.5 were qualitatively similar to those for β, except that increasing pH above 2.8 had less effect on dissolution in citric and malic acids and none on dissolution in lactic acid. Variations of the dissolution rate with [HA] showed no systematic dependence on acid type but some dependence on pH. The results suggest that [HA], rather than buffering per se, is a major rate-controlling factor, probably owing to the importance of undissociated acid as a readily diffusible source of H(+) ions in maintaining near-surface dissolution within the softened layer of enamel. TA5.5 was more closely correlated with [HA] than was β, and seems to be the preferred practical measure of buffering. The relationship between [HA] and TA5.5 differs between mono- and polybasic acids, so a separate analysis of products according to predominant acid type could improve multivariate models of erosive potential.

Jatropha mahafalensis oil from Madagascar: properties and suitability as liquid biofuel

Access to affordable and renewable sources of energy is crucial to reducing poverty and enhancing rural development in countries of the global South. Straight vegetable oil was recently identified as a possible alternative to conventional biomass for rural energy supply. In this context, the Jatropha curcas Linn. species has been extensively investigated with regard to its potential as a biofuel feedstock. In contrast, only little is known about Jatropha mahafalensis Jum. & H. Perrier, which is an indigenous and endemic representative of the Jatropha genus in Madagascar. This paper explores the potential and suitability of J. mahafalensis as a biofuel feedstock. Seed samples were collected in the area of Soalara in south-western Madagascar in February and September 2011. Two agro-ecological zones (coastal area and calcareous plateau) and two plant age groups (below and above 10 years) were considered. These four sample groups were analyzed with regard to oil properties, element contents, and fatty acid profiles. Measured values differed greatly between the two harvests, probably owing to different climatic or storage conditions. No direct relation between age of trees or location and oil quality could be established. The analyses indicate that J. mahafalensis oil can be used in oil lamps, cooking stoves and stationary combustion engines for electrification or for biodiesel production. However, modifications in storage and extraction methods, as well as further processing steps are necessary to enable its utilization as a straight vegetable oil and feedstock for biodiesel production. If these technical requirements can be met, and if it turns out that J. mahafalensis oil is economically competitive in comparison with firewood, charcoal, paraffin and petroleum, it can be considered as a promising feedstock for rural energy supply.

Virtual Infrastructures as a Service enabling Converged Optical Networks and Data Centres

Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.

A Cruciform Electron Donor-Acceptor Semiconductor with Solid-State Red Emission: 1D/2D Optical Waveguides and Highly Sensitive/Selective Detection of H2S Gas

In this paper, a new cruciform donor–acceptor molecule 2,2'-((5,5'-(3,7-dicyano-2,6-bis(dihexylamino)benzo[1,2-b:4,5-b']difuran-4,8-diyl)bis(thiophene-5,2-diyl))bis (methanylylidene))dimalononitrile (BDFTM) is reported. The compound exhibits both remarkable solid-state red emission and p-type semiconducting behavior. The dual functions of BDFTM are ascribed to its unique crystal structure, in which there are no intermolecular face-to-face π–π interactions, but the molecules are associated by intermolecular CN…π and H-bonding interactions. Firstly, BDFTM exhibits aggregation-induced emission; that is, in solution, it is almost non-emissive but becomes significantly fluorescent after aggregation. The emission quantum yield and average lifetime are measured to be 0.16 and 2.02 ns, respectively. Crystalline microrods and microplates of BDFTM show typical optical waveguiding behaviors with a rather low optical loss coefficient. Moreover, microplates of BDFTM can function as planar optical microcavities which can confine the emitted photons by the reflection at the crystal edges. Thin films show an air-stable p-type semiconducting property with a hole mobility up to 0.0015 cm2V−1s−1. Notably, an OFET with a thin film of BDFTM is successfully utilized for highly sensitive and selective detection of H2S gas (down to ppb levels).

Climate change impacts on tree species, forest properties, and ecosystem services

– Swiss forests experience strong impacts under the CH2011 scenarios, partly even for the low greenhouse gas scenario RCP3PD. Negative impacts prevail in low-elevation forests, whereas mostly positive impacts are expected in high-elevation forests. – Major changes in the distribution of the two most important tree species, Norway spruce and European beech, are expected. Growth conditions for spruce improve in a broad range of scenarios at presently cool high-elevation sites with plentiful precipitation, but in the case of strong warming (A1B and A2) spruce and beech are at risk in large parts of the Swiss Plateau. – High elevation forests that are temperature-limited will show little change in species composition but an increase in biomass. In contrast, forests at low elevations in warm-dry inner-Alpine valleys are sensitive to even moderate warming and may no longer sustain current biomass and species. – Timber production potential, carbon storage, and protection from avalanches and rockfall react differently to climate change, with an overall tendency to deteriorate at low elevations, and improve at high elevations. – Climate change will affect forests also indirectly, e.g., by increasing the risk of infestation by spruce bark beetles, which will profit from an extended flight period and will produce more generations per year.

Multifunctional Coordination Compounds: Design and Properties [and Discussion]

M. Verdaguer

Simple measures of climate, soil properties and plant traits predict national-scale grassland soil carbon stocks

Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. Using data from an extensive national survey of English grasslands, we show that surface soil (0–7 cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. Soil C stocks in the largest pool, of intermediate particle size (50–250 μm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0·45–50 μm), was explained by soil pH and the community abundance-weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N-rich vegetation. The C stock in the small active fraction (250–4000 μm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. Synthesis and applications. Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1–100 000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

A Genetic Algorithm to associate optical measurements and estimate orbits of geocentric objects

Cataloging geocentric objects can be put in the framework of Multiple Target Tracking (MTT). Current work tends to focus on the S = 2 MTT problem because of its favorable computational complexity of O(n²). The MTT problem becomes NP-hard for a dimension of S˃3. The challenge is to find an approximation to the solution within a reasonable computation time. To effciently approximate this solution a Genetic Algorithm is used. The algorithm is applied to a simulated test case. These results represent the first steps towards a method that can treat the S˃3 problem effciently and with minimal manual intervention.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.