Earth-based render of tabique walls – an experimental work contribution

A research work focused on studying earth render for tabique application purposes is presented. Initially, a brief description of the tabique building technique is provided. The relevance of the application of this traditional building technique is also highlighted. Different compositions of earth render are experimentally analysed and the respective performance is evaluated. Flexural and compressive strengths, workability, drying shrinkage cracking and water resistance are the material properties assessed. A simple earth render is selected as being adequate for tabique building applications and it is applied on the manufacturing of a tabique wall sample. This wall sample is monitored in terms of thermal insulation ability and its thermal transmission coefficient is estimated. Taking into account that there is still a lack of published technical information related to this topic, this paper may contribute to solve this limitation and to give some guidance in future repairing processes of tabique construction. The technological benefit of adding lime or cement with earth is researched. Real tabique timber structure samples are applied in order to validate the obtained experimental results.info:eu-repo/semantics/publishedVersio

Evaluation of polymer choice on immunogenicity of chitosan coated PLGA NPs with surface-adsorbed pneumococcal protein antigen PspA4Pro

Polymeric nanoparticles (NPs) are recognized as potential delivery vehicles for vaccines. PLGA is a biocompatible polymer synonymous with polymeric NPs, which can be coated with other polymers such as chitosan that has intrinsic adjuvant properties as well as mucoadhesive properties. Numerous modifications and variations exist for PLGA and chitosan, which can influence the NP characteristics and the resulting immunogenicity. The current study investigated variations for making chitosan coated PLGA NPs incorporating recombinant pneumococcal surface protein A from family 2, clade 4 (PspA4Pro) antigen as a vaccine targeting the vast majority of pneumococcal strains and determine the effect of the polymers on particle size, surface charge, and surface marker upregulation on a dendritic cell (DC) line in vitro. PLGA variations tested with the ester-terminal group had the greatest detriment for prospective vaccine use, due to the lowest PspA4Pro adsorption and induction of CD40 and CD86 cell surface markers on DCs. The negatively charged chitosans exhibited the lowest surface marker expressions, similar to the uncoated NP, supporting the commonly accepted notion that positive surface charge augments immunogenic effects of the NPs. However, the study indicated that NPs made from PLGA with an acid terminated group, and chitosan HCl salt, exhibit particle characteristics, antigen adsorption efficiency and immunogenicity, which could be most suitable as a vaccine formulation

Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms.

Because of the high costs associated with ascertainment of families, most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. Although microsatellite markers spaced every 10 cM typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carried out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 single-nucleotide polymorphisms. Of the ~1100 families, 972 were informative for further analyses, and mean information content was 0.86 after pruning for linkage disequilibrium. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with bipolar II disorder (BPII) and 702 subjects with recurrent major depression. Three affection status models (ASMs) were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus recurrent major depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (non-parametric pairs LOD 3.4 for rs1046943 at 119 cM) and 9q21 (non-parametric pairs logarithm of odds (LOD) 3.4 for rs722642 at 78 cM) using only BPI and schizoaffective (SA), BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis, we observed 59 parametric LODs of 2 or greater, many of which are likely to be close to maximum possible scores. Although some linkage findings may be false positives, the results could help prioritize the search for rare variants using whole exome or genome sequencing

Monitoring of activated sludge settling ability through image analysis : validation on full-scale wastewater treatment plants

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid–liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.Empresa de Águas, Efluentes e Resíduos de Braga, Portugal - EM (AGERE)Fundação para a Ciência e a Tecnologia (FCT

Microalgal biorefineries

ABSTRACT: Microalgae-based bioproducts remain expensive mainly due to microalgae cultivation, harvesting, and downstream processing costs. Nonetheless, microalgae are a high potential source of several biofuels, biofertilizers, and bioproducts (e.g., carbohydrates, long-chain fatty acids, pigments, and proteins), which can provide important nutritional, cosmetical, pharmaceutical, and health benefits. In addition, they are able to perform wastewater bioremediation and carbon dioxide mitigation. This not only contributes to a more sustainable microalgae production, with environmental benefits, but also offers cost savings on the whole process. Hence, from these small cellular factories, a large source of compounds and products can be obtained, providing a real microalgal-based biorefinery. This type of approach is crucial for the full application and commercialization of microalgae in a large range of products and industries, with added benefits for bioeconomy and society in general. This chapter addresses the potential transformation of microalgal biomass into a wide range of marketable products, presenting examples of experimental microalgae-based biorefineries grown in an autotrophic mode at a laboratory scale.info:eu-repo/semantics/publishedVersio

Enzyme classification with peptide programs: a comparative study

<p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

Chemical and Microbiological Contamination in Limpet (Patella spp.) of the Portuguese Coast

Coastal production areas can be impacted by anthropogenic contamination from urban, agro-industrial and leisure activities. Some contaminants, such as chemical substances might also have a telluric origin. Non filter feeding univalve mollusks, such as limpets, which are collected in rocky shores either for sale or for auto-consumption, are very appreciated in Portugal, but have been excluded from provisions on the classification of production areas, although can present relevant contamination. Thus, the aim of this study was to assess the microbiological and toxic metal contaminations in limpets (Patella spp) of the Portuguese coast, taking into account the production area and seasonal variation, and comparing their contamination levels with those occurring in bivalve mollusk indicator species, mussel (Mytilus edulis). The risks associated to the consumption of limpet meals were also assessed. For that, microbial total and fecal levels and cadmium, lead and mercury contents in limpets and mussels samples from three coastal areas over several months were analyzed based on standard methodologies. Contents of mercury and lead in limpets from the three areas studied, were always below the limits of 0.50 mg kg-1 and 1.5 mg kg-1 allowed by the EU, respectively. Regarding cadmium, levels in limpet were always above the limit of 1.0 mg kg-1, reaching about 3.0 mg kg-1 in some samples. These values probably indicate contamination from telluric origin (soil or rocks) in the coastal studied areas. Results indicated that microbiological contamination of fecal origin was low and in general below the detection level. Contamination levels did not show a clear seasonal pattern. The two mollusk species, limpets and mussels, differed statistically in all contaminants analyzed, being cadmium the most of concern, and always higher in limpets than in mussel samples. Thus, the potential risk associated with limpet consumption, taking into account the cadmium tolerable weekly intake (TWI), was investigated, being possible to reach a reliable recommendation of less than a monthly meal of 160 g. As recreational picking of limpets is common in Portugal, official 4recommendations of maximum periodic human consumption should be published and enforcement increased in forbidden areasinfo:eu-repo/semantics/acceptedVersio

A novel sensor measuring local voidage profile inside a fluidised bed reactor

Liquid-solid fluidisation is frequently encountered in drinking water treatment processes, often to obtain a large liquid-solid interfacial surface area. A large surface area is crucial for optimal seeded crystallisation in full-scale softening reactors. Due to crystallisation, particles grow and migrate to a lower zone in the reactor which leads to a stratified bed. Larger particles adversely affect the surface area. To maintain optimal process conditions in the fluidised beds, information is needed about the distribution of particle size, local voidage and available surface area, over the reactor height. In this work, a sensor is developed to obtain the hydraulic state gradient, based on Archimedes’ principle. A cylindrical heavy object is submerged in the fluidised bed and lowered gradually while its weight is measured at various heights using a sensitive force measuring device. Based on accurate fluidisation experiments with calcite grains, the voidage is determined and a straightforward empirical model is developed to estimate the particle size as a function of superficial fluid velocity, kinematic viscosity, suspension density, voidage and particle density. The surface area and specific space velocity can be estimated accordingly, which represent key performance indicators regarding the hydraulic state of the fluidised bed reactor. The prediction error for voidage is 5 ± 2 % and for particle size 9 ± 4 %. The newly developed soft sensor is a more time-effective method for obtaining the hydraulic state in full-scale liquid-solid fluidised bed reactors