Shoot cuttings propagation of giant reed (Arundo donax L.) in water and moist soil: The path forward?

Giant reed (Arundo donax L.) is a perennial rhizomatous grass that can be regarded as an ideal crop for bioenergy production, owing to several intrinsic characteristics. Despite to the promising yield results obtained in many plot experiments, the cultivation of giant reed at field scale is still a challenge. Owing to the floral sterility of the species, rhizome propagation has been predominantly used to establish field plots experiments, although this method is unpractical and monetarily expensive. Giant reed is a hydrophytic plant that typically spread in riparian systems by flood-mediated fragmentation and dispersal of vegetative propagules. Since giant reed propagation is strictly dependent on temporary abundance of water, this plant characteristic might be exploited for fostering the diffusion of giant reed as a bioenergy field crop. The objectives of this paper were: i) to disseminate some techniques for shoot cutting propagation of giant reed in water and in moist soil; ii) to address the critical points that remain to be solved for a widespread diffusion of this species as a bioenergy field crop.     

On the Second-Law inconsistency of Emergy Analysis

The paper argues against the claim made by Emergy Analysts that emergy is an exergy-based procedure. Both Emergy- and Exergy Analysis employ space- and time integrated energy input/output models to quantitatively assess the resource consumption of physical systems: the issue at stake is whether Emergy is embodied energy or embodied exergy. Although the compatibility of Exergy- and Emergy accounting procedures, the significance of the peculiar Emergy Algebra, and some cost-allocation issues have been studied in detail, a final agreement could not be reached, so that some doubt exists about the degree of compatibility of the two methods. The present paper shows that the definitions and the procedures employed in Emergy Analysis are in fact First Law-based, and that they neglect or misrepresent Second Law issues. This conclusion is reached by carefully reviewing and critically analyzing a series of general and specific procedures contained in the original Odum books and in some of the most representative publications by Emergy analysts.     

A model to design and optimize multi-energy systems in buildings at the design concept stage

Increasing interest is currently being addressed to multi-energy systems in buildings. These systems integrate different energy sources, at least one of which is renewable, in order to cover the thermal and electrical loads of a building. Since the design and operation of such systems are very complicated for many reasons (e.g. the intermittent nature of the renewable sources, the highly interlinked system layouts), it is of the foremost importance to provide tools to help select the best system configuration and energy sources mix.A modelling approach to multi-energy systems in buildings, based on the energy hub concept is presented in this work. This approach allows the coupling between the energy demand and the energy supply in a building to be modelled in a synthetic way. The model was customised to be used at the concept stage of the building design, either as a system simulation tool or as a system selection tool. If the prices and the characteristics of the energy converters and of the energy-wares are known, it is possible, with a certain set of constraints, to determine the configuration that minimises the initial investment costs, the use of non-renewable sources or the life-cycle costs. This approach makes it possible to avoid the simulation and ranking of a set of different system configurations, and also permits the study of the behaviour of such systems in an open configuration and not as individual systems. An application of the methodology to a case study is provided.     

Different effects of microbubble destruction and translation in Doppler measurements

In flow measurements in which microbubbles are involved, the amplitude and phase of the received echo signal are noticeably influenced by the transmitted ultrasound intensity. Previous studies have shown that, when such intensity is progressively increased, the Doppler spectrum is accordingly distorted, i.e., it is asymmetrically broadened toward the negative frequency side. Such deformation has been attributed to radiation force, which pushes the microbubbles into the sound propagation direction, thus yielding additional phase delays in the received echoes. However, the possible contribution of microbubble destruction to this spectral deformation has not been considered yet. In this paper, this issue is investigated by analyzing the experimental spectra produced by two different types of microbubbles suspended in a moving fluid and insonified in pulsed wave (PW) mode at programmable pulse repetition frequency (PRF) and pressure. Conditions are created in which either the radiation force or the destruction mechanism is expected to be dominant. Effects produced by the two phenomena on the Doppler spectrum are shown to be different. When the PRF is low (2 kHz), so that, according to theoretical simulations, the radiation force effect is negligible, a 26 dB noise floor increase is observed for a 13 dB pressure increment. For a higher PRF (16 kHz), the same pressure increase not only affects the noise floor, but also causes the bubbles to deviate from their original streamlines, yielding a Doppler bandwidth increase by a factor of 5. It is concluded that asymmetrical spectral broadening is mainly due to radiation force, and microbubble destruction mainly results in an increased noise floor without affecting the spectral shape.     

Spatial heterogeneity,industry heterogeneity,and entrepreneurship

The prevalence of entrepreneurship varies not only across regions but also among industries. Using a unique panel dataset of 60 two-digit industries across 64 provinces from 2000 to 2010 in Vietnam, we investigate the importance of spatial and sectoral heterogeneity in an analysis of the determinants of entrepreneurship and empirically explore the interaction effect of geographic conditions and industry dynamism. Overall, our results confirm the significance of industry structural variables and their joint effect with geographic conditions in fostering new firm formation. Particularly, (i) growth-driven entries are generally higher in provinces that offer higher salaries; (ii) technology-intensive industries within regions that have strong knowledge spillover effects are appealing to new entries. Others noteworthy findings include: (i) ‘necessity entrepreneurship’ is prevalent in Vietnam, but limited to extractive and service industries that are typically labor intensive; (ii) firms tend to concentrate more in agglomerated locations. This effect, however, evaporates for high-tech industries; and (iii) industry profitability and niche dynamism all play a crucial role in stimulating new start-ups. We apply the system generalized method of moments to obtain empirical evidence in the study.     

Transient analysis of non-Markovian models using stochastic state classes

The method of stochastic state classes approaches the analysis of Generalised Semi Markov Processes (GSMPs) through the symbolic derivation of probability density functions over supports described by Difference Bounds Matrix (DBM) zones. This makes steady state analysis viable, provided that at least one regeneration point is visited by every cyclic behaviour of the model.We extend the approach providing a way to derive transient probabilities. To this end, stochastic state classes are extended with a supplementary timer that enables the symbolic derivation of the distribution of time at which a class can be entered. The approach is amenable to efficient implementation when model timings are given by expolynomial distributions, and it can be applied to perform transient analysis of GSMPs within any given time bound. In the special case of models underlying a Markov Regenerative Process (MRGP), the method can also be applied to the symbolic derivation of local and global kernels, which in turn provide transient probabilities through numerical integration of generalised renewal equations. Since much of the complexity of this analysis is due to the local kernel, we propose a selective derivation of its entries depending on the specific transient measure targeted by the analysis.     

m-Asynchronous cellular automata: from fairness to quasi-fairness

A new model for the study of asynchronous cellular automata dynamical behavior is introduced with the main purpose of unifying several existing paradigms. The main idea is to measure the set of updating sequences to quantify the dependency of the properties under investigation from them. We propose to use the class of quasi-fair measures, namely measures that satisfy some fairness conditions on the updating sequences. Basic set properties like injectivity and surjectivity are adapted to the new setting and studied. In particular, we prove that they are dimensions sensitive properties (i.e., they are decidable in dimension 1 and undecidable in higher dimensions). A first exploration of dynamical properties is also started, some results about equicontinuity and expansivity behaviors are provided.     

Is there a correlation between journal impact factor and researchers’ performance? A study comprising the fields of clinical nephrology and neurosciences

Quantifying the scientific performance of investigators has become an integral part of decision-making in research policy. The aim of the present study was to evaluate if there is a correlation between journal impact factor (IF) and researchers’ influence among a selected group of Brazilian investigators in the fields of clinical nephrology and neurosciences. This study was based on 94 senior investigators (36 in clinical nephrology and 58 in clinical neurosciences) receiving productivity scholarships from the Brazilian Council for Scientific and Technological Development (CNPq) according to a list provided by the agency in February 2009. Scientific performance indicators included in the analysis were: number of papers indexed by the Web of Science and Scopus databases, number of citations, h- and m-index. IFs were analyzed as (1) cumulative IF (∑IF), (2) IF adjusted by time (IF/t), and (3) average IF. There was a moderate positive correlation only between ∑IF and two indicators: total number of citations (P < 0.001) and h-index (P < 0.001). There was also a positive correlation between IF/t and m-index (P < 0.001). There was an agreement in these correlations between both groups (clinical nephrology and neurosciences). No significant correlation between the average IF and any of the scientific indicators was detected. A cut-off of 10.53 for IF/t showed the best performance in predicting researchers with m-index equal to or greater than 1. According to our findings, other qualitative and quantitative instruments rather than IF are clearly needed for identifying researchers with outstanding scientific output.     

On the predictive ability of mechanistic models for the Haitian cholera epidemic

Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. We address the above issue in a formal model comparison framework and provide a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels and coupling mechanisms. Reference is made to records of the recent Haiti cholera epidemics. Our intensive computations and objective model comparisons show that spatially explicit models accounting for spatial connections have better explanatory power than spatially disconnected ones for short-to-intermediate calibration windows, while parsimonious, spatially disconnected models perform better with long training sets. On average, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management.