Influence of different fibers on the change of pore pressure of self-consolidating concrete exposed to fire

The focus of this paper is given to investigate the effect of different fibers on the pore pressure of fiber reinforced self-consolidating concrete under fire. The investigation on the pore pressure-time and temperature relationships at different depths of fiber reinforced self-consolidating concrete beams was carried out. The results indicated that micro PP fiber is more effective in mitigating the pore pressure than macro PP fiber and steel fiber. The composed use of steel fiber, micro PP fiber and macro PP fiber showed clear positive hybrid effect on the pore pressure reduction near the beam bottom subjected to fire. Compared to the effect of macro PP fiber with high dosages, the effect of micro PP fiber with low fiber contents on the pore pressure reduction is much stronger. The significant factor for reduction of pore pressure depends mainly on the number of PP fibers and not only on the fiber content. An empirical formula was proposed to predict the relative maximum pore pressure of fiber reinforced self-consolidating concrete exposed to fire by considering the moisture content, compressive strength and various fibers. The suggested model corresponds well with the experimental results of other research and tends to prove that the micro PP fiber can be the vital component for reduction in pore pressure, temperature as well spalling of concrete.

Optimization of low-cost nutritional supplementation for lignocellulosic ethanol fermentation

[Excerpt] Bioethanol from lignocellulosic materials (LCM), also called second generation bioethanol, is considered a promising alternative to first generation bioethanol. An efficient production process of lignocellulosic bioethanol involves an effective pretreatment of LCM to improve the accessibility of cellulose and thus enhance the enzymatic saccharification. One interesting approach is to use the whole slurry from treatment, since allows economical and industrial benefits: washing steps are avoided, water consumption is lower and the sugars from liquid phase can be used, increasing ethanol concentration [1]. However, during the pretreatment step some compounds (such as furans, phenolic compounds and weak acids) are produced. These compounds have an inhibitory effect on the microorganisms used for hydrolysate fermentation [2]. To overcome this, the use of a robust industrial strain together with agro-industrial by-products as nutritional supplementation was proposed to increase the ethanol productivities and yields. (...)

Self-esteem, assertiveness and resilience in adolescents institutionalized

The institutionalization of children and adolescents has been an increasingly visible problem in modern society. Unfavourable socio-economic conditions have been joining the behavior problems and school absenteeism. When the family fails in its competence for education, social security or the Court withdraws the child or adolescent to a host institution. The aim of this research was to characterize self-esteem, assertiveness and resilience of institutionalized adolescents in the northern region of Portugal and to establish associations with these dependent variables and gender, scholar level and duration of the institutionalization. For the purpose of this study a wider questionnaire was carried out, and validated with a smaller group. It was a transversal study following a predominantly quantitative methodology, with a convenience sample. The sample included 101 adolescents (55 female and 46 males) from eight institutions, aged between 11 to 21 years old (average 15.45). For self-esteem the Rosenberg Self-Esteem Scale (Rosenberg, 1965), already validate for Portuguese adolescents, was used. For assertiveness and resilience it was applied the Global Evaluation Scale of Assertiveness and the Global Evaluation Scale of Resilience (Jardim & Pereira, 2006) we previously adapted and validated for adolescents. Collected data was introduced in a SPSS database. A descriptive analysis was done to characterize the sample concerning all the variables. To establish associations between individual factors and dependent variables t test, correlations and non-parametric test were applied. Results indicated a relatively low self-esteem (28.03), with girls having a lower value than boys, without significant differences. No correlations were found between self-esteem and the time in the institution. Assertiveness of the sample is average (23.97) and higher for girls than boys, with a positive significant correlation with the scholar grade. Also the resilience is average (25.97), having girls a little lower mean than boys and no significant differences or correlations were found.

Optimization of peptide nucleic acid fluorescence in situ hybridization (PNA-FISH) for the detection of bacteria: the effect of pH, dextran sulfate and probe concentration

Fluorescence in situ hybridization (FISH) is a molecular technique widely used for the detection and characterization of microbial populations. FISH is affected by a wide variety of abiotic and biotic variables and the way they interact with each other. This is translated into a wide variability of FISH procedures found in the literature. The aim of this work is to systematically study the effects of pH, dextran sulfate and probe concentration in the FISH protocol, using a general peptide nucleic acid (PNA) probe for the Eubacteria domain. For this, response surface methodology was used to optimize these 3 PNA-FISH parameters for Gram-negative (Escherichia coli and Pseudomonas fluorescens) and Gram-positive species (Listeria innocua, Staphylococcus epidermidis and Bacillus cereus). The obtained results show that a probe concentration higher than 300 nM is favorable for both groups. Interestingly, a clear distinction between the two groups regarding the optimal pH and dextran sulfate concentration was found: a high pH (approx. 10), combined with lower dextran sulfate concentration (approx. 2% [w/v]) for Gram-negative species and near-neutral pH (approx. 8), together with higher dextran sulfate concentrations (approx. 10% [w/v]) for Gram-positive species. This behavior seems to result from an interplay between pH and dextran sulfate and their ability to influence probe concentration and diffusion towards the rRNA target. This study shows that, for an optimum hybridization protocol, dextran sulfate and pH should be adjusted according to the target bacteria.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Self-reported psychosocial factors among In Vitro Fertilization patients interviewed alone or with the partner

"Published online: 07 Nov 2015"

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.