901 resultados para Expressive language development


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Evolution of the traditional consumer in a power system to a prosumer has posed many problems in the traditional uni-directional grid. This evolution in the grid model has made it important to study the behaviour of microgrids. This thesis deals with the laboratory microgrid setup at the Munich School of Engineering, built to assist researchers in studying microgrids. The model is built in Dymola which is a tool for the OpenModelica language. Models for the different components were derived, suiting the purpose of this study. The equivalent parameters were derived from data sheets and other simulation programs such as PSCAD. The parameters were entered into the model grid and tested at steady state, firstly. This yielded satisfactory results that were similar to the reference results from MATPOWER power flow. Furthermore, fault conditions at several buses were simulated to observe the behaviour of the grid under these conditions. Recommendations for further developing this model to include more detailed models for components, such as power electronic converters, were made at the end of the thesis.

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Deep learning methods are extremely promising machine learning tools to analyze neuroimaging data. However, their potential use in clinical settings is limited because of the existing challenges of applying these methods to neuroimaging data. In this study, first a data leakage type caused by slice-level data split that is introduced during training and validation of a 2D CNN is surveyed and a quantitative assessment of the model’s performance overestimation is presented. Second, an interpretable, leakage-fee deep learning software written in a python language with a wide range of options has been developed to conduct both classification and regression analysis. The software was applied to the study of mild cognitive impairment (MCI) in patients with small vessel disease (SVD) using multi-parametric MRI data where the cognitive performance of 58 patients measured by five neuropsychological tests is predicted using a multi-input CNN model taking brain image and demographic data. Each of the cognitive test scores was predicted using different MRI-derived features. As MCI due to SVD has been hypothesized to be the effect of white matter damage, DTI-derived features MD and FA produced the best prediction outcome of the TMT-A score which is consistent with the existing literature. In a second study, an interpretable deep learning system aimed at 1) classifying Alzheimer disease and healthy subjects 2) examining the neural correlates of the disease that causes a cognitive decline in AD patients using CNN visualization tools and 3) highlighting the potential of interpretability techniques to capture a biased deep learning model is developed. Structural magnetic resonance imaging (MRI) data of 200 subjects was used by the proposed CNN model which was trained using a transfer learning-based approach producing a balanced accuracy of 71.6%. Brain regions in the frontal and parietal lobe showing the cerebral cortex atrophy were highlighted by the visualization tools.

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In the ‘society of acceleration and uncertainty’ (Rosa, 2013), the young are struggling to interpret our complex and fast-changing world. The entity and the velocity of changes are so enormous that we need new narratives or languages to conceptualise them. Among those changes “Climate Change” is placed in a particular difficult position. As the writer A. Ghosh said: “The current climate crisis is also a crisis of culture, and thus of the imagination”. In fact, in today’s literature and cinema a strong dichotomy exists between fictional and non-fictional works, but none of those extremities seems suitable to picture an “adequate representation” of climate change issues, particularly those that are related to future. The main goal of my study, carried out within FEDORA EU project, was to understand to what extent the hybrid film form called “mockumentary” (a language that adopts the aesthetics of factual production to give an illusion of truth to invented stories) could inspire and help students in overcoming the mentioned dichotomy, working as a tool to foster the development of argumentative and imaginative skills needed to picture “immaginary yet realistic” climate change scenarios.

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Questa tesi di laurea compie uno studio sull’ utilizzo di tecniche di web crawling, web scraping e Natural Language Processing per costruire automaticamente un dataset di documenti e una knowledge base di coppie verbo-oggetto utilizzabile per la classificazione di testi. Dopo una breve introduzione sulle tecniche utilizzate verrà presentato il metodo di generazione, prima in forma teorica e generalizzabile a qualunque classificazione basata su un insieme di argomenti, e poi in modo specifico attraverso un caso di studio: il software SDG Detector. In particolare quest ultimo riguarda l’applicazione pratica del metodo esposto per costruire una raccolta di informazioni utili alla classificazione di documenti in base alla presenza di uno o più Sustainable Development Goals. La parte relativa alla classificazione è curata dal co-autore di questa applicazione, la presente invece si concentra su un’analisi di correttezza e performance basata sull’espansione del dataset e della derivante base di conoscenza.

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To verify whether fluorescence in situ hybridization (FISH) of cells from the buccal epithelium could be employed to detect cryptomosaicism with a 45,X lineage in 46,XY patients. Samples of nineteen 46,XY healthy young men and five patients with disorders of sex development (DSD), four 45,X/46,XY and one 46,XY were used. FISH analysis with X and Y specific probes on interphase nuclei from blood lymphocytes and buccal epithelium were analyzed to investigate the proportion of nuclei containing only the signal of the X chromosome. The frequency of nuclei containing only the X signal in the two tissues of healthy men did not differ (p = 0.69). In all patients with DSD this frequency was significantly higher, and there was no difference between the two tissues (p = 0.38), either. Investigation of mosaicism with a 45,X cell line in patients with 46,XY DSD or sterility can be done by FISH directly using cells from the buccal epithelium.

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Most epidemiological studies concerning differentiated thyroid cancers (DTC) indicate an increasing incidence over the last two decades. This increase might be partially explained by the better access to health services worldwide, but clinicopathological analyses do not fully support this hypothesis, indicating that there are carcinogenetic factors behind this noticeable increasing incidence. Although we have undoubtedly understood the biology and molecular pathways underlying thyroid carcinogenesis in a better way, we have made very little progresses in identifying a risk profile for DTC, and our knowledge of risk factors is very similar to what we knew 30-40 years ago. In addition to ionizing radiation exposure, the most documented and established risk factor for DTC, we also investigated the role of other factors, including eating habits, tobacco smoking, living in a volcanic area, xenobiotics, and viruses, which could be involved in thyroid carcinogenesis, thus, contributing to the increase in DTC incidence rates observed.

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The segment of the world population showing permanent or temporary lactose intolerance is quite significant. Because milk is a widely consumed food with an high nutritional value, technological alternatives have been sought to overcome this dilemma. Microfiltration combined with pasteurization can not only extend the shelf life of milk but can also maintain the sensory, functional, and nutritional properties of the product. This studied developed a pasteurized, microfiltered, lactose hydrolyzed (delactosed) skim milk (PMLHSM). Hydrolysis was performed using β-galactosidase at a concentration of 0.4mL/L and incubation for approximately 21h at 10±1°C. During these procedures, the degree of hydrolysis obtained (>90%) was accompanied by evaluation of freezing point depression, and the remaining quantity of lactose was confirmed by HPLC. Milk was processed using a microfiltration pilot unit equipped with uniform transmembrane pressure (UTP) ceramic membranes with a mean pore size of 1.4 μm and UTP of 60 kPa. The product was submitted to physicochemical, microbiological, and sensory evaluations, and its shelf life was estimated. Microfiltration reduced the aerobic mesophilic count by more than 4 log cycles. We were able to produce high-quality PMLHSM with a shelf life of 21 to 27d when stored at 5±1°C in terms of sensory analysis and proteolysis index and a shelf life of 50d in regard to total aerobic mesophile count and titratable acidity.

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Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

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The Atlantic rainforest species Ocotea catharinensis, Ocotea odorifera, and Ocotea porosa have been extensively harvested in the past for timber and oil extraction and are currently listed as threatened due to overexploitation. To investigate the genetic diversity and population structure of these species, we developed 8 polymorphic microsatellite markers for O. odorifera from an enriched microsatellite library by using 2 dinucleotide repeats. The microsatellite markers were tested for cross-amplification in O. catharinensis and O. porosa. The average number of alleles per locus was 10.2, considering all loci over 2 populations of O. odorifera. Observed and expected heterozygosities for O. odorifera ranged from 0.39 to 0.93 and 0.41 to 0.92 across populations, respectively. Cross-amplification of all loci was successfully observed in O. catharinensis and O. porosa except 1 locus that was found to lack polymorphism in O. porosa. Combined probabilities of identity in the studied Ocotea species were very low ranging from 1.0 x 10-24 to 7.7 x 10-24. The probability of exclusion over all loci estimated for O. odorifera indicated a 99.9% chance of correctly excluding a random nonparent individual. The microsatellite markers described in this study have high information content and will be useful for further investigations on genetic diversity within these species and for subsequent conservation purposes.

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Tabebuia cassinoides (Lam.) DC., popularly known as caxeta, is a tree species that belongs to the plant family Bignoniaceae. This species is endemic to the Brazilian Atlantic Forest and is widely exploited commercially. To date, little is known about its genetic structure, preventing the establishment of adequate management plans for this taxon. The objective of this study was to construct a microsatellite-enriched genomic library for T. cassinoides to select polymorphic loci, and standardize polymerase chain reaction amplification conditions. Of the 15 loci examined, 5 were polymorphic. The number of alleles per locus ranged from 2 to 8, with a mean of 4.4. The microsatellite loci described here represent the basis for detailed population genetic studies of this species, which will greatly contribute for the development of better conservation strategies for this taxon.

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• Microsatellite primers were developed for the tree species Genipa americana (Rubiaceae) for further population genetic studies. • We identified 144 clones containing 65 repeat motifs from a genomic library enriched for (CT)8 and (GT)8 motifs. Primer pairs were developed for 32 microsatellite loci and validated in 40 individuals of two natural G. americana populations. Seventeen loci were polymorphic, revealing from three to seven alleles per locus. The observed and expected heterozygosities ranged from 0.24 to 1.00 and from 0.22 to 0.78, respectively. • The 17 primers identified as polymorphic loci are suitable to study the genetic diversity and structure, mating system, and gene flow in G. americana.

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Hevea brasiliensis is a native species of the Amazon Basin of South America and the primary source of natural rubber worldwide. Due to the occurrence of South American Leaf Blight disease in this area, rubber plantations have been extended to suboptimal regions. Rubber tree breeding is time-consuming and expensive, but molecular markers can serve as a tool for early evaluation, thus reducing time and costs. In this work, we constructed six different cDNA libraries with the aim of developing gene-targeted molecular markers for the rubber tree. A total of 8,263 reads were assembled, generating 5,025 unigenes that were analyzed; 912 expressed sequence tags (ESTs) represented new transcripts, and two sequences were highly up-regulated by cold stress. These unigenes were scanned for microsatellite (SSR) regions and single nucleotide polymorphisms (SNPs). In total, 169 novel EST-SSR markers were developed; 138 loci were polymorphic in the rubber tree, and 98 % presented transferability to six other Hevea species. Locus duplication was observed in H. brasiliensis and other species. Additionally, 43 SNP markers in 13 sequences that showed similarity to proteins involved in stress response, latex biosynthesis and developmental processes were characterized. cDNA libraries are a rich source of SSR and SNP markers and enable the identification of new transcripts. The new markers developed here will be a valuable resource for linkage mapping, QTL identification and other studies in the rubber tree and can also be used to evaluate the genetic variability of other Hevea species, which are valuable assets in rubber tree breeding.

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This study compares the impact of obesogenic environment (OE) in six different periods of development on sperm parameters and the testicular structure of adult rats and their correlations with sex steroid and metabolic scenario. Wistar rats were exposed to OE during gestation (O1), during gestation/lactation (O2), from weaning to adulthood (O3), from lactation to adulthood (O4), from gestation to sexual maturity (O5), and after sexual maturation (O6). OE was induced by a 20% fat diet, and control groups were fed a balanced diet (4% fat). Serum leptin levels and adiposity index indicate that all groups were obese, except for O1. Three progressive levels of impaired metabolic status were observed: O1 presented insulin resistance, O2 were insulin resistant and obese, and groups O3, O4, and O5 were insulin resistant, obese, and diabetic. These three levels of metabolic damage were proportional to the increase of leptin and decreased circulating testosterone. The impairment in the daily sperm production (DSP) paralleled these three levels of metabolic and hormonal damage being marginal in O1, increasing in O2, and being higher in groups O3, O4, O5, and O6. None of the OE periods affected the sperm transit time in the epididymis, and the lower sperm reserves were caused mainly by impaired DSP. In conclusion, OE during sexual maturation markedly reduces the DSP at adulthood in the rat. A severe reduction in the DSP also occurs in OE exposure during gestation/lactation but not in gestation, indicating that breast-feeding is a critical period for spermatogenic impairment under obesogenic conditions.

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The aim of the present work was to produce a cationic solid lipid nanoparticle (SLN) as non-viral vector for protein delivery. Cationic SLN were produced by double emulsion method, composed of softisan(®) 100, cetyltrimethylammonium bromide (CTAB), Tween(®) 80, Span(®) 80, glycerol and lipoid(®) S75 loading insulin as model protein. The formulation was characterized in terms of mean hydrodynamic diameter (z-ave), polydispersity index (PI), zeta potential (ZP), stability during storage time, stability after lyophilization, effect of toxicity and transfection ability in HeLa cells, in vitro release profile and morphology. SLN were stable for 30days and showed minimal changes in their physicochemical properties after lyophilization. The particles exhibited a relatively slow release, spherical morphology and were able to transfect HeLa cells, but toxicity remained an obstacle. Results suggest that SLN are nevertheless promising for delivery of proteins or nucleic acids for gene therapy.

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The role of key cell cycle regulation genes such as, CDKN1B, CDKN2A, CDKN2B, and CDKN2C in sporadic medullary thyroid carcinoma (s-MTC) is still largely unknown. In order to evaluate the influence of inherited polymorphisms of these genes on the pathogenesis of s-MTC, we used TaqMan SNP genotyping to examine 45 s-MTC patients carefully matched with 98 controls. A multivariate logistic regression analysis demonstrated that CDKN1B and CDKN2A genes were related to s-MTC susceptibility. The rs2066827*GT+GG CDKN1B genotype was more frequent in s-MTC patients (62.22%) than in controls (40.21%), increasing the susceptibility to s-MTC (OR=2.47; 95% CI=1.048-5.833; P=0.038). By contrast, the rs11515*CG+GG of CDKN2A gene was more frequent in the controls (32.65%) than in patients (15.56%), reducing the risk for s-MTC (OR=0.174; 95% CI=0.048-0.627; P=0.0075). A stepwise regression analysis indicated that two genotypes together could explain 11% of the total s-MTC risk. In addition, a relationship was found between disease progression and the presence of alterations in the CDKN1A (rs1801270), CDKN2C (rs12885), and CDKN2B (rs1063192) genes. WT rs1801270 CDKN1A patients presented extrathyroidal tumor extension more frequently (92%) than polymorphic CDKN1A rs1801270 patients (50%; P=0.0376). Patients with the WT CDKN2C gene (rs12885) presented larger tumors (2.9±1.8 cm) than polymorphic patients (1.5±0.7 cm; P=0.0324). On the other hand, patients with the polymorphic CDKN2B gene (rs1063192) presented distant metastases (36.3%; P=0.0261). In summary, we demonstrated that CDKN1B and CDKN2A genes are associated with susceptibility, whereas the inherited genetic profile of CDKN1A, CDKN2B, and CDKN2C is associated with aggressive features of tumors. This study suggests that profiling cell cycle genes may help define the risk and characterize s-MTC aggressiveness.