Métodos de análise da complexidade no problema de empacotamento de paletes do distribuidor

In the pallet loading problem, one of the main goals is to allocate the highest number of boxes as possible, to minimize empty spaces in the pallet. Those empty spaces are called trim-loss. If all boxes have a rectangular shape, which is the most common one, it is possible to pack them so that their faces are coincident with themselves. By doing that, the trim-loss can be minimized. Although loading a pallet may seem linear to most people, some customers impose restrictions that increase the complexity of the pallet loading. Due to that, to evaluate the complexity of a packed pallet, some metrics were created. They consist in an evaluation of a set of parameters that are inherent to the pallet loading process and affect its complexity. After analysing some of those constraints and loading methods enforced by some pickers in a real company, it was possible to obtain samples where the metrics were applied to learn which parameters add the most complexity in the pallet loading process. In the future, after knowing the relevancy of each parameter, the metrics can be used in pallet generation tools to learn how complex is the loading of a certain pallet and study new and easier ways to load the boxes that reduce the complexity of such process. Two statistical tests were then used to analyse the samples retrieved: the principal components analysis and the multiple linear regression. The first is used to combine multiple variables into a smaller set that represents the most relevant information, while the multiple linear regression uses the variables and respective observations to calculate a model that can predict the value of the complexity of a packed pallet in given circumstances. In the first one, it was learned that three principal components were extracted, but since the third one explained a small percentage of the total data variance, it was decided to retain only two components: the box quantities, which explains 41% of the total variance, followed by the box dimensions, explaining 28% of the total variance. The multiple linear regression revealed that the component representing the box quantities, which contains the Number of Box Types, Number of Column Piles, Number of Boxes, Time Spent Packing, and Percentage of Fragile Boxes variables is the component that mostly increase the complexity of pallet cargo arrangements. Although the model can predict the data that was obtained with an average accuracy, some of the coefficients ended up being small, those being related to the components Box Dimensions, which has the Number of Heavy Boxes, Average Box Weight, Average Maximum Width variables, and Height Between Pile and Worker and Number variables, meaning that they aren’t very significant towards evaluating the complexity of a pallet loading process. Using a multiple linear regression with the 9 variables showed that the variable who adds more complexity is the Number of Column Piles. Overall, the results obtained were acceptable, and showed that the variable that adds more complexity is the ones that the pickers see as adding more complexity, and also that the results of the multiple regression with the components match the one using the original variables. It is worth noting that this variable is subjective, meaning that one worker’s perception on the complexity may not match others’ perception. Despite having obtained only one variable being considered as statistically significant towards explaining the complexity in the pallet loading problem, it doesn’t mean it’s the only one that adds complexity.No problema de carregamento de paletes, um dos grandes objetivos é alocar o maior número de caixas possível, visando minimizar espaços vazios conhecidos por trim-loss. Se todas as caixas possuírem um formato retangular, que é o formato mais comum, é possível arrumá-las de forma que as suas faces fiquem encostadas entre si, minimizando assim o trim-loss. No entanto, apesar do empacotamento de caixas em paletes parecer linear para a maioria das pessoas, certos clientes impõem restrições que aumentam a complexidade do empacotamento. Como tal, para avaliar a complexidade de um arranjo de paletes, criaram-se métricas, que consistem na avaliação de um conjunto de parâmetros inerentes ao processo ou às características do carregamento de paletes que afetam a sua complexidade. Após analisar numa empresa real as restrições e os métodos de empacotamento usados pelos operadores, foi possível obter amostras onde as métricas são aplicadas para tentar saber quais as mais relevantes no processo, para assim futuramente estas métricas serem aplicadas em ferramentas de geração de paletes para poder analisar os resultados obtidos e estudar maneiras onde estas sejam carregadas mais facilmente. Posteriormente, dois testes estatísticos foram aplicados aos dados recolhidos: uma análise de componentes principais e a regressão linear múltipla. O primeiro usa-se para combinar várias variáveis e formar um conjunto mais pequeno que represente a informação mais relevante, enquanto a regressão linear múltipla usa as variáveis e respetivas observações para calcular um modelo que consiga prever valores de complexidade do carregamento de paletes em quaisquer circunstâncias. No primeiro, verificou-se a existência de três componentes principais, mas dado que o terceiro componente explica uma percentagem da variância total dos dados pequena, decidiu-se extrair apenas dois componentes: as quantidades das caixas é o componente que explica maiores valores de variância nos dados (41%), seguido pelas dimensões das caixas, explicando 28% da variância total dos dados. A regressão linear múltipla revelou que o componente que representa as quantidades das caixas, que contém as variáveis Número de Tipos de Caixa, Número de Colunas, Número de Caixas, Tempo Despendido a Carregar Caixas e Percentagem de Caixas Frágeis, é aquele que faz crescer mais substancialmente a complexidade do carregamento de caixas em paletes. Com os vários testes, verificou-se que os componentes Dimensões das Caixas, que possui as variáveis Número de Caixas Pesadas Carregadas, Peso Médio das Caixas, Largura Máxima Média, e a diferença de alturas entre pilhas de caixas e o operador, não acrescentam muita significância na explicação da avaliação da complexidade no problema de carregamento de paletes. A regressão linear múltipla com as variáveis originais mostrou que o Número de Colunas é a variável que adiciona mais complexidade. Apesar do modelo obtido ter significância, quase todos os coeficientes obtidos acabaram por ser baixos e com valores Significância (sig.) acima de 0,05, não sendo essas variáveis relevantes no modelo. Valores baixos de Cronbach’s Alpha e R2 ajustado evidenciam a suscetibilidade da aparição destes valores. No geral, os resultados obtidos nesta dissertação foram satisfatórios, mas os coeficientes baixos da regressão linear múltipla não foram bons. O número de observações retido e o escalamento das variáveis são causas possíveis para esta discrepância de valores ter acontecido. Vale a pena referir que a variável que avalia a complexidade é uma variável subjetiva, pelo que o que um picker considera como sendo complexo pode não corresponder ao que outros trabalhadores pensem. Apesar de, estatisticamente, apenas uma variável ter significância na explicação da complexidade, na realidade todas as variáveis têm alguma influência na complexidade do carregamento de caixas em paletes. No geral, a perceção dos trabalhadores tem semelhanças com aquilo que se obteve nos resultados das regressões lineares

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Orientierungsschätzung mit einem Sliding Mode-Beobachter auf Basis Body Sensor Network-integrierter Inertialsensorik

Background: The fungal genus Sporothrix includes at least four human pathogenic species. One of these species, S. brasiliensis, is the causal agent of a major ongoing zoonotic outbreak of sporotrichosis in Brazil. Elsewhere, sapronoses are caused by S. schenckii and S. globosa. The major aims on this comparative genomic study are: 1) to explore the presence of virulence factors in S. schenckii and S. brasiliensis; 2) to compare S. brasiliensis, which is cat-transmitted and infects both humans and cats with S. schenckii, mainly a human pathogen; 3) to compare these two species to other human pathogens (Onygenales) with similar thermo-dimorphic behavior and to other plant-associated Sordariomycetes. Results: The genomes of S. schenckii and S. brasiliensis were pyrosequenced to 17x and 20x coverage comprising a total of 32.3 Mb and 33.2 Mb, respectively. Pair-wise genome alignments revealed that the two species are highly syntenic showing 97.5% average sequence identity. Phylogenomic analysis reveals that both species diverged about 3.8-4.9 MYA suggesting a recent event of speciation. Transposable elements comprise respectively 0.34% and 0.62% of the S. schenckii andS. brasiliensis genomes and expansions of Gypsy-like elements was observed reflecting the accumulation of repetitive elements in the S. brasiliensis genome. Mitochondrial genomic comparisons showed the presence of group-I intron encoding homing endonucleases (HE’s) exclusively in S. brasiliensis. Analysis of protein family expansions and contractions in theSporothrix lineage revealed expansion of LysM domain-containing proteins, small GTPases, PKS type1 and leucin-rich proteins. In contrast, a lack of polysaccharide lyase genes that are associated with decay of plants was observed when compared to other Sordariomycetes and dimorphic fungal pathogens, suggesting evolutionary adaptations from a plant pathogenic or saprobic to an animal pathogenic life style. Conclusions: Comparative genomic data suggest a unique ecological shift in the Sporothrix lineage from plant-association to mammalian parasitism, which contributes to the understanding of how environmental interactions may shape fungal virulence. . Moreover, the striking differences found in comparison with other dimorphic fungi revealed that dimorphism in these close relatives of plant-associated Sordariomycetes is a case of convergent evolution, stressing the importance of this morphogenetic change in fungal pathogenesis

Comparative genomics of the major fungal agents of human and animal Sporotrichosis: Sporothrix schenckii and Sporothrix brasiliensis

Abstract Background The fungal genus Sporothrix includes at least four human pathogenic species. One of these species, S. brasiliensis, is the causal agent of a major ongoing zoonotic outbreak of sporotrichosis in Brazil. Elsewhere, sapronoses are caused by S. schenckii and S. globosa. The major aims on this comparative genomic study are: 1) to explore the presence of virulence factors in S. schenckii and S. brasiliensis; 2) to compare S. brasiliensis, which is cat-transmitted and infects both humans and cats with S. schenckii, mainly a human pathogen; 3) to compare these two species to other human pathogens (Onygenales) with similar thermo-dimorphic behavior and to other plant-associated Sordariomycetes. Results The genomes of S. schenckii and S. brasiliensis were pyrosequenced to 17x and 20x coverage comprising a total of 32.3 Mb and 33.2 Mb, respectively. Pair-wise genome alignments revealed that the two species are highly syntenic showing 97.5% average sequence identity. Phylogenomic analysis reveals that both species diverged about 3.8-4.9 MYA suggesting a recent event of speciation. Transposable elements comprise respectively 0.34% and 0.62% of the S. schenckii and S. brasiliensis genomes and expansions of Gypsy-like elements was observed reflecting the accumulation of repetitive elements in the S. brasiliensis genome. Mitochondrial genomic comparisons showed the presence of group-I intron encoding homing endonucleases (HE’s) exclusively in S. brasiliensis. Analysis of protein family expansions and contractions in the Sporothrix lineage revealed expansion of LysM domain-containing proteins, small GTPases, PKS type1 and leucin-rich proteins. In contrast, a lack of polysaccharide lyase genes that are associated with decay of plants was observed when compared to other Sordariomycetes and dimorphic fungal pathogens, suggesting evolutionary adaptations from a plant pathogenic or saprobic to an animal pathogenic life style. Conclusions Comparative genomic data suggest a unique ecological shift in the Sporothrix lineage from plant-association to mammalian parasitism, which contributes to the understanding of how environmental interactions may shape fungal virulence. . Moreover, the striking differences found in comparison with other dimorphic fungi revealed that dimorphism in these close relatives of plant-associated Sordariomycetes is a case of convergent evolution, stressing the importance of this morphogenetic change in fungal pathogenesis

Direct antiviral therapy for treatment of hepatitis C: A real-world study from Brazil

Introduction and objectives: Direct antiviral agents (DAAs) including sofosbuvir (SOF), daclatasvir (DCV), simeprevir (SIM) and ombitasvir, paritaprevir and dasabuvir were introduced 2015 in Brazil for treatment of hepatitis C virus (HCV) infection. The aims of this study were to assess effectiveness and safety of HCV treatment with DAA in real-life world in a highly admixed population from Brazil. Materials and methods: All Brazilian reference centers for HCV treatment were invited to take part in a web-based registry, prospectively conducted by the Brazilian Society of Hepatology, to assess outcomes of HCV treatment in Brazil with DAAs. Data to be collected included demographics, disease severity and comorbidities, genotype (GT), viral load, DAA regimens, treatment side effects and sustained virological response (SVR). Results: 3939 patients (60% males, mean age 58 ± 10 years) throughout the country were evaluated. Most had advanced fibrosis or cirrhosis, GT1 and were treated with SOF/DCV or SOF/SIM. Overall SVR rates were higher than 95%. Subjects with decompensated cirrhosis, GT2 and GT3 have lower SVR rates of 85%, 90% and 91%, respectively. Cirrhosis and decompensated cirrhosis in GT1 and male sex and decompensated cirrhosis in GT3 were significantly associated with no SVR. Adverse events (AD) and serious AD occurred in 18% and 5% of those subjects, respectively, but less than 1% of patients required treatment discontinuation. Conclusion: SOF-based DAA regimens are effective and safe in the heterogeneous highly admixed Brazilian population and could remain an option for HCV treatment at least in low-income countries

AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data

Seminário de Dissertação (2024)

Página da disciplina de Seminário de Dissertação (MPPP, UFPE, 2022) Lista de participantes == https://docs.google.com/spreadsheets/d/1mrULe1y04yPxHUBaF50jhaM1OY8QYJ3zva4N4yvm198/edit#gid=