An improved method for measuring soil microbial activity by gas phase flow injection analysis

The rate of carbon dioxide production is commonly used as a measure of microbial activity in the soil. The traditional method of CO2 determination involves trapping CO2 in an alkali solution and then determining CO2 concentration indirectly by titration of the remaining alkali in the solution. This method is still commonly employed in laboratories throughout the world due to its relative simplicity and the fact that it does not require expensive, specific equipment. However, there are several drawbacks: the method is time-consuming, requires large amounts of chemicals and the consistency of results depends on the operator's skills. With this in mind, an improved method was developed to analyze CO2 captured in alkali traps, which is cheap and relatively simple, with a substantially shorter sample handling time and reproducibility equivalent to the traditional titration method. A comparison of the concentration values determined by gas phase flow injection analysis (GPFIA) and titration showed no significant difference (p > 0.05), but GPFIA has the advantage that only a tenth of the sample volume of the titration method is required. The GPFIA system does not require the purchase of new, costly equipment but the device was constructed from items commonly found in laboratories, with suggestions for alternative configurations for other detection units. Furthermore, GPFIA for CO2 analysis can be equally applied to samples obtained from either the headspace of microcosms or from a sampling chamber that allows CO2 to be released from alkali trapping solutions. The optimised GPFIA method was applied to analyse CO2 released from degrading hydrocarbons from a site contaminated by diesel spillage.

Mathématique et statistique en science de l’information et en science de la communication: infométrie mathématique et infométrie statistique des revues scientifiques

L’application de la mathématique et de la statistique à l’étude des phénomènes informationnels a entraîné la naissance en science de l’information d’un nouvel axe de recherche et de développement, l’infométrie. Après avoir montré l’intérêt de cette application mais aussi avoir mis en garde contre certains abus et contre certains mauvais usages, nous présentons quelques exemples d’infométrie mathématique et d’infométrie statistique appliquées aux revues scientifiques. Ils illustrent l’étendue et l’efficacité des analyses qui peuvent être faites sur une ou plusieurs variables informationnelles.

E-publishing development and changes in the scholarly communication system

New and alternative scientific publishing business models is a reality driven mostly by the information and communication technologies, by the movements towards the recovery of control of the scientific communication activities by the academic community, and by the open access approaches. The hybrid business model, mixing open and toll-access is a reality and they will probably co-exist with respective trade-offs. This essay discusses the changes driven by the epublishing and the impacts on the scholarly communication system stakeholders' interrelationships (publishers-researchers, publishers-libraries and publishers-users interrelationships), and the changes on the scientific publishing business models, followed by a discussion of possible evolving business models. Whatever the model which evolves and dominates, a huge cultural change in authors' and institutions publishing practices will be necessary in order to make the open access happen and to consolidate the right business models for the traditional publishers. External changes such as policies, rewarding systems and institutions mandates should also happen in order to sustain the whole changing scenario.

Genetic structure and gene flow of Eugenia dysenterica natural populations

This study was carried out to assess the genetic variability of ten "cagaita" tree (Eugenia dysenterica) populations in Southeastern Goiás. Fifty-four randomly amplified polymorphic DNA (RAPD) loci were used to characterize the population genetic variability, using the analysis of molecular variance (AMOVA). A phiST value of 0.2703 was obtained, showing that 27.03% and 72.97% of the genetic variability is present among and within populations, respectively. The Pearson correlation coefficient (r) among the genetic distances matrix (1 - Jaccard similarity index) and the geographic distances were estimated, and a strong positive correlation was detected. Results suggest that these populations are differentiating through a stochastic process, with restricted and geographic distribution dependent gene flow.