969 resultados para Red clay-based ceramic tiles


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Red flesh fruit is a character which interest is increasing in several commercial species. Following a review of the research on the biosynthesis and accumulation of anthocyanin in pears (Chapter 1) the general aim of the project is reported in Chapter 2. Chapter 3 reports the results of a molecular analysis of 33 red-fleshed pear accessions, genotyped with 18 SSR markers with the aim of improving germplasm conservation strategies to support ongoing breeding programs. The molecular profiles revealed both cases of synonymy and homonymy and 6 unique genotypes were identified. The S-allele were established to highlight the genetic relationships among these landraces. Four of the unique genotypes have been clustered based on pomological data. In the Chapter 4, the work was directed to identify the putative genomic regions involved in the appearance of this character in pear fruit. A crossing population (‘Carmen’ x ‘Cocomerina Precoce’) segregating for the trait was phenotyped for 2 consecutive years and used for QTL analysis. A strong QTL was identified in a small genomic region related to the red flesh fruit trait at 27 Mb from the start of LG5. Two candidate genes were detected in this genomic region: ‘PcMYB114’ and ‘PcABCC2’. SSR marker SSR114 was found able to detect the red flesh phenotype segregation in all the red-fleshed pear accessions and segregating progenies tested. Chapter 5 focuses on examining the trend of anthocyanin synthesis and accumulation during the fruit development, from fruit set to ripening time. Three different trials were planned: qPCR and HPLC methods were performed to correlate the genes expression with the anthocyanin accumulation in ‘Cocomerina Precoce’ and six progenies. Total transcriptome sequencing was used to compare the differential genes expression between red and white-fleshed fruit. Chapter 6 reviews and analyses all the earlier study findings while providing new potential future perspectives.

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The first main conclusion drawn from this dissertation concerns the amount of Pt deposited on the asymmetric layer of membrane produced by tape casting porosity shaping method. Three different amounts were investigated (0.15, 1.5 and 4.5 mg cm-2 ). The most optimal performance, based on H2 permeation performances, was attained when 1.5 mg cm-2 of Pt was deposited on the porous layer, resulting in a 0.642 mL min-1 cm-2 permeated H2 when 80% H2 in He was employed as the feed. Pt deposition method is influenced by the concentration of the Pt precursor, which results in different morphology of the catalyst. The second development focused on further optimization on tape casting membranes concerning the solvent employed for the Pt catalyst deposition. The same concentration of Pt was employed, depositing 1.5 mg cm-2 on the porous side of the membrane, but a mixture of acetone and water was employed as solvent. This mixture allowed the suppression of effects leading to poorly dispersed particles. As a result, it was possible to achieve 0.74 mL min-1 cm-2 at 750°C with 50% H2 in He. Lastly, first-ever permeation performance measurements into an innovative ceramic membrane type for hydrogen separation was investigated. In-depth research was done on a group of hierarchically-structured BaCe0.65Zr0.20Y0.15O3-δ(BCZY) - Gd0.2Ce0.8O2-δ(GDC) membranes produced by freeze casting porosity shaping method. Membranes were investigated observing the effect of deposition solvent and the effect of porous layer thickness. Employing a mixture of Acetone and water resulted in better hydrogen permeation at temperatures (T > 650°C), reaching 0.26 mL min-1 cm-2 at 750°C with 50% H2 in He. The reduction of porous layer thickness led to a hydrogen flow of 0.33 mL min-1 cm-2 , at 750°C with 50% H2 in He.

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In this thesis work, a cosmic-ray telescope was set up in the INFN laboratories in Bologna using smaller size replicas of CMS Drift Tubes chambers, called MiniDTs, to test and develop new electronics for the CMS Phase-2 upgrade. The MiniDTs were assembled in INFN National Laboratory in Legnaro, Italy. Scintillator tiles complete the telescope, providing a signal independent of the MiniDTs for offline analysis. The telescope readout is a test system for the CMS Phase-2 upgrade data acquisition design. The readout is based on the early prototype of a radiation-hard FPGA-based board developed for the High Luminosity LHC CMS upgrade, called On Board electronics for Drift Tubes. Once the set-up was operational, we developed an online monitor to display in real-time the most important observables to check the quality of the data acquisition. We performed an offline analysis of the collected data using a custom version of CMS software tools, which allowed us to estimate the time pedestal and drift velocity in each chamber, evaluate the efficiency of the different DT cells, and measure the space and time resolution of the telescope system.

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The IoT is growing more and more each year and is becoming so ubiquitous that it includes heterogeneous devices with different hardware and software constraints leading to an highly fragmented ecosystem. Devices are using different protocols with different paradigms and they are not compatible with each other; some devices use request-response protocols like HTTP or CoAP while others use publish-subscribe protocols like MQTT. Integration in IoT is still an open research topic. When handling and testing IoT sensors there are some common task that people may be interested in: reading and visualizing the current value of the sensor; doing some aggregations on a set of values in order to compute statistical features; saving the history of the data to a time-series database; forecasting the future values to react in advance to a future condition; bridging the protocol of the sensor in order to integrate the device with other tools. In this work we will show the working implementation of a low-code and flow-based tool prototype which supports the common operations mentioned above, based on Node-RED and Python. Since this system is just a prototype, it has some issues and limitations that will be discussed in this work.

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Ericaria amentacea is an endemic alga of the Mediterranean Sea that lives in the littoral rocky fringe. The species is sensitive to environmental changes, so it’s used to assess the water ecological quality. Nevertheless, E. amentacea is deeply impacted by coastal development which cause rapid regression despite data on its distribution and healthy status are still limited. Moreover, it’s little known by people outside the scientific community. In this context, Portofino Seaweed Garden was born, a conservation and citizen science project aim to involve marine outdoor enthusiasts in protecting and restoring E. amentacea, creating a submerged garden. Restoration measures have been encouraged by EU regulations. Here, using citizen science, 1) I evaluated the spatial variability of E. amentacea abundance along the central-eastern Ligurian coast, to evaluate its status and choose donor and restoration sites. 2) I carried out an E. amentacea restoration (with outplanting lab-cultured embryos on 50 clay tiles). 3) I assessed the community involvement and education of volunteers. Simple protocol was created to train them on the monitoring. Unprecedented E. amentacea reproductive mismatch affected the restoration performance, probably caused by marine heat wave that hit the Mediterranean in summer 2022. After fertile apices collection in Pontetto (GE) and during laboratory phase, gametes spawned on the discs didn’t settle as expected. Only 16 tiles showed juveniles and they were outplanted at Punta Castello (C zone of Portofino MPA). Unfortunately, they didn’t survive in the field due to an interplay of physical and biological factors. From citizen science point of view, the project demonstrated positive outcomes of collaborations between people and scientists by involving more than 100 participants. Citizen scientists became specialize in the protocol providing quality data for E. amentacea conservation. Current results suggest that outplanting should be further tested.

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Among the various ways of adopting the biographical approach, we used the curriculum vitaes (CVs) of Brazilian researchers who work as social scientists in health as our research material. These CVs are part of the Lattes Platform of CNPq - the National Council for Scientific and Technological Development, which includes Research and Institutional Directories. We analyzed 238 CVs for this study. The CVs contain, among other things, the following information: professional qualifications, activities and projects, academic production, participation in panels for the evaluation of theses and dissertations, research centers and laboratories and a summarized autobiography. In this work there is a brief review of the importance of autobiography for the social sciences, emphasizing the CV as a form of autobiographical practice. We highlight some results, such as it being a group consisting predominantly of women, graduates in social sciences, anthropology, sociology or political science, with postgraduate degrees. The highest concentration of social scientists is located in Brazil's southern and southeastern regions. In some institutions the main activities of social scientists are as teachers and researchers with great thematic diversity in research.

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Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

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Graphene and carbon nanotube nanocomposite (GCN) was synthesised and applied in gene transfection of pIRES plasmid conjugated with green fluorescent protein (GFP) in NIH-3T3 and NG97 cell lines. The tips of the multi-walled carbon nanotubes (MWCNTs) were exfoliated by oxygen plasma etching, which is also known to attach oxygen content groups on the MWCNT surfaces, changing their hydrophobicity. The nanocomposite was characterised by high resolution scanning electron microscopy; energy-dispersive X-ray, Fourier transform infrared and Raman spectroscopies, as well as zeta potential and particle size analyses using dynamic light scattering. BET adsorption isotherms showed the GCN to have an effective surface area of 38.5m(2)/g. The GCN and pIRES plasmid conjugated with the GFP gene, forming π-stacking when dispersed in water by magnetic stirring, resulting in a helical wrap. The measured zeta potential confirmed that the plasmid was connected to the nanocomposite. The NIH-3T3 and NG97 cell lines could phagocytize this wrap. The gene transfection was characterised by fluorescent protein produced in the cells and pictured by fluorescent microscopy. Before application, we studied GCN cell viability in NIH-3T3 and NG97 line cells using both MTT and Neutral Red uptake assays. Our results suggest that GCN has moderate stability behaviour as colloid solution and has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity and good transfection efficiency.

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For the first time, oxygen terminated cellulose carbon nanoparticles (CCN) was synthesised and applied in gene transfection of pIRES plasmid. The CCN was prepared from catalytic of polyaniline by chemical vapour deposition techniques. This plasmid contains one gene that encodes the green fluorescent protein (GFP) in eukaryotic cells, making them fluorescent. This new nanomaterial and pIRES plasmid formed π-stacking when dispersed in water by magnetic stirring. The frequencies shift in zeta potential confirmed the plasmid strongly connects to the nanomaterial. In vitro tests found that this conjugation was phagocytised by NG97, NIH-3T3 and A549 cell lines making them fluorescent, which was visualised by fluorescent microscopy. Before the transfection test, we studied CCN in cell viability. Both MTT and Neutral Red uptake tests were carried out using NG97, NIH-3T3 and A549 cell lines. Further, we use metabolomics to verify if small amounts of nanomaterial would be enough to cause some cellular damage in NG97 cells. We showed two mechanisms of action by CCN-DNA complex, producing an exogenous protein by the transfected cell and metabolomic changes that contributed by better understanding of glioblastoma, being the major finding of this work. Our results suggested that this nanomaterial has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity, good transfection efficiency, and low cell damage in small amounts of nanomaterials in metabolomic tests.

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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

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Propolis is a resin that bees collect from different plant sources and use in the defense of the bee community. The intricate composition of propolis varies depending on plant sources from different geographic regions and many types have been reported. Red coloured propolis found in several states in Brazil and in other countries has known antimicrobial and antioxidant activity. Different analytical methods have been applied to studies regarding the chemical composition and plant origins of red propolis. In this study samples of red propolis from different regions have been characterised using direct infusion electrospray ionisation mass spectrometry (ESI(-)-MS) fingerprinting. Data from the fingerprints was extracted and analysed by multivariate analysis to group the samples according to their composition and marker compounds. Despite similar colour, the red coloured propolis samples were divided into three groups due to contrasting chemical composition, confirming the need to properly characterise the chemical composition of propolis.

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The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.