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Série Temporal: Aumento Nominal do Salário Mínimo Vs Poder de Compra Lastreado em Dólar
Ferro no Assalariado: Poder de Compra Decrescente.
Evolução dos Custos de Silvicultura (Ciclo de 6 Anos) e Receitas Ajustada pelo Custo Capital ao Longo do Tempo
Fonte: Relatório de R.I | Compilado por Gabriel Ribeiro Cunha | Depuração de DRE
Série Temporal: Preço do Metro Cúbico "Eucalipto Pulpwood" (Real vs Dólar)
Trabalho Plantadas
Computing T-cell receptor recognition motifs and their matches in the human proteome
T-cells which recognise and kill cells expressing tumour-associated antigens are a promising new anti-cancer agent. However, in a few cases reactivity to antigens expressed by normal tissue caused serious adverse events. To mitigate such risks, Adaptimmune developed an extensive in-vitro testing pipeline. A pivotal element was predicting the repertoire of potential targets in human tissues that the therapeutic T-cells might respond to. The script reproduces two important figures of our paper. Computations involved checking > 10 million peptide sequences for matches in the human proteome, under 126 different criteria.
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Time Series MCH Service Utilization.
Clustering and Visualization of Human Motion Data using K-means
This analysis explores a dataset of human motion primitives, focusing on preprocessing, exploratory data analysis (EDA), and clustering. Data is loaded from multiple text files, cleaned, and normalized. EDA includes summary statistics, distributions, boxplots, and scatter plots, as well as a correlation heatmap. Clustering is performed using K-means, with the optimal number of clusters determined via the elbow method, and hierarchical clustering is applied to a sample of the data. The clustering results are evaluated using the Hopkins statistic and Davies-Bouldin Index. This comprehensive analysis provides insights into the dataset's structure and clustering tendencies.