Mapas mentais para o processo de aprendizagem: uma proposta de intervenção

Involving students is a challenge for the teacher, as well as the need to develop methods that can be used to meet expectations of effectiveness and quality of learning. In this context, active learning changes the focus of the teacher to the student, that is, the student is encouraged to increase her involvement in the teaching-learning process, and the Mind Map is a strategy used for this. The Mind Map is a visual diagram used to organize information and facilitate cognitive connections between ideas. A systematic review of the literature that implemented the PRISMA recommendations was carried out in relation to the Mind Maps applied in teaching. This research aimed to respond three questions. Among the results of this research, it was discovered that the greatest use of Mind Maps is to support active learning and the type of course that most uses them is the medical course. An intervention project based on the bibliographic review was proposed. This intervention consists of six activities for the use of Mind Maps in any discipline of na IFCE course. Due to the COVID-19 pandemic, this proposal was unapplied, but the literature review demonstrated the benefits of using Mind Maps in the learning process.Envolver os alunos é um desafio para o docente, assim como a necessidade de desenvolver métodos que possam ser usados para atender as expectativas de eficácia e qualidade da aprendizagem. Nesse contexto, existe a aprendizagem ativa que muda o foco do professor para o aluno, ou seja, o aluno é incentivado a aumentar seu envolvido no processo de ensino-aprendizagem e o Mapa Mental é uma estratégia usada para isso. O Mapa Mental é um diagrama visual usado para organizar informações e facilitar as conexões cognitivas entre ideias. Uma revisão sistemática da literatura que usou as recomendações PRISMA foi realizada em relação aos Mapas Mentais aplicados no ensino. Essa pesquisa teve o objetivo de responder três questões. Entre os resultados dessa pesquisa foram encontrados que a maior utilização dos Mapas Mentais é no apoio a aprendizagem ativa e o tipo de curso que mais os utilizam é o curso de medicina. Foi proposto um projeto de intervenção baseado na revisão bibliográfica. Essa intervenção consiste de seis atividades para o uso de Mapas Mentais em qualquer disciplina de um curso do IFCE. Devido à pandemia do COVID-19 essa proposta não foi aplicada, mas a revisão bibliográfica demonstrou os benefícios da utilização de Mapas Mentais no processo de aprendizagem

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Scheduling problem with unrelated parallel machines: mathematical formulation, decomposition methods and hybridization

Exportado OPUSMade available in DSpace on 2019-08-10T10:16:17Z (GMT). No. of bitstreams: 1 francisco_regis_abreu_gomes.pdf: 1524379 bytes, checksum: d7e7bb4cc9db4eecac33ba53a6bb6c96 (MD5) Previous issue date: 7Esta tese aborda dois problemas de sequenciamento de máquinas paralelas não-relacionadas com os tempos de preparação dependentes da máquina e da sequência. Ambos os problemas são NP-hard. As diferenças entre esses problemas são a função objetivo adotada e os métodos de solução utilizados. No primeiro problema, o makespan é função objetiva e a decomposição Benders combinatória é o método. Este método pode ser lento para convergir. Portanto, três procedimentos são introduzidos para acelerar sua convergência. O primeiro procedimento consiste em encerrar a execução do problema mestre quando uma solução ótima repetida é encontrada. O segundo procedimento é baseado na técnica multicut. Por fim, o terceiro procedimento é baseado no procedimento warm-start. O esquema de decomposição Benders combinatório melhorado é comparado com uma formulação matemática e uma implementação convencional da decomposição de Benders. Nos experimentos são utilizados dois conjuntos de testes da literatura. Para o primeiro conjunto, o método proposto executa 21,85% em média mais rápido do que a implementação convencional. Para o segundo conjunto, o método proposto não conseguiu encontrar uma solução ótima em apenas 31 em 600 instâncias, obteve uma diferença entre os limites inferiores e superiores de 0,07% e teve um tempo computacional médio de 377,86 s, enquanto os melhores resultados dos outros métodos foram 57, 0,17 % e 573,89 s, respectivamente. No segundo problema o atraso total é a função objetivo. Os modelos matemáticos para este problema em geral usam uma constante conhecida como big-M devido às restrições disjuntivas. Isso produz limites inferiores muito fracos que dificultam a obtenção da solução ótima, mesmo para instâncias de pequeno porte. Para resolver este problema é proposta uma formulação matemática que não use a constante big-M. Para este fim, apresenta-se uma abordagem que usa tarefas fictícias em vez da constante big-M. Além disso, é proposta uma condição de otimização que reduz o espaço de busca da solução do problema. Os experimentos realizados em cinco tipos de instâncias produziram prova computacional da superioridade do modelo proposto em comparação com modelos baseados nas formulações de Wagner (1959) e Manne (1960). O modelo proposto produziu 291 soluções ótimas em comparação com 98 e 148 dos modelos de Wagner (1959) e Manne (1960), respectivamente, e foi até três ordens de magnitude mais rápido nas 300 instâncias de pequeno porte que foram testadas. Um algoritmo de geração de coluna também é proposto para encontrar soluções quase ótimas para instâncias de tamanho médio com até 50 tarefas e dez máquinas. Ao contrário das abordagens padrão, o modelo proposto é usado em vez de um algoritmo de programação dinâmica para resolver o problema de pricing. Para acelerar a convergência do algoritmo de geração de colunas, várias heurísticas são propostas para gerar as colunas iniciais e resolver o problema de pricing. A geração de colunas híbrida obteve uma diferença média entre os limites inferiores e superiores e tempo de execução de 2,71% e 930,48 s, respectivamente, em comparação com 34,78% e 2.490,37 s, respectivamente, em relação ao modelo proposto. Os resultados indicam que as abordagens propostas são mais eficazes em tempo de execução e qualidade da solução.This thesis addresses two unrelated parallel machines scheduling problem with sequence and machine dependent setup times. Both problems are NP-hard. The differences between these problems are the objective function adopted and the solution methods used. In the first problem the makespan is objective function and combinatorial Benders decomposition is solution method. This method can be slow to converge. Therefore, three procedures are introduced to accelerate its convergence. The first procedure consists of terminating the execution of the master problem when a repeated optimal solution is found. The second procedure is based on the multicut technique. The third procedure is based on the warm-start technique. The improved combinatorial Benders decomposition scheme is compared to a mathematical formulation and a standard implementation of Benders decomposition algorithm. In the experiments, two test sets from the literature are used. For the first set the proposed method performs 21.85% on average faster than the standard implementation of the Benders algorithm. For the second set the proposed method failed to find an optimal solution in only 31 in 600 instances, obtained an average gap of 0.07%, and took an average computational time of 377.86s, while the best results of the other methods were 57, 0.17%, and 573.89s, respectively. In the second problem the total tardiness is objective function. Mathematical models for this problem often use a constant known as big-M because the disjunctive constraints. This yields very weak lower bounds that make it difficult to obtain the optimal solution, even for small-size instances. To address this problem is proposed a mathematical formulation that does not use the big-M constant. To this end is presented an approach that uses dummy jobs instead of the big-M constant. Additionally, an optimality condition method that reduces the solution space of the problem is proposed. Experiments conducted on five instance types produced computational proof of the superiority of the proposed model compared to models based on Wagners (1959) and Mannes (1960) formulations. The proposed model produced 291 optimal solutions compared to 98 and 148 of Wagners (1959) and Mannes (1960) models, respectively, and it was up to three orders of magnitude faster in the 300 small-size instances that were tested. A column-generation algorithm is also proposed to find near-optimal solutions for medium-size instances with up to 50 jobs and 10 machines. Unlike standard approaches, the proposed model is used instead of a dynamic programming algorithm to solve the pricing problem. For accelerating the convergence of the column-generation algorithm, various heuristics are proposed to generate the initial columns and solve the pricing problem. The hybrid column generation obtained an average gap and runtime of 2.71% and 930.48 s, respectively, compared to 34.78% and 2,490.37 s, respectively, of the proposed model. Results indicate that the proposed approaches are more effective in terms of both running time and solution quality

Improved Combinatorial Benders Decomposition for a Scheduling Problem with Unrelated Parallel Machines

This paper addresses the unrelated parallel machines scheduling problem with sequence and machine dependent setup times. Its goal is to minimize the makespan. The problem is solved by a combinatorial Benders decomposition. This method can be slow to converge. Therefore, three procedures are introduced to accelerate its convergence. The first procedure is a new method that consists of terminating the execution of the master problem when a repeated optimal solution is found. The second procedure is based on the multicut technique. The third procedure is based on the warm-start. The improved Benders decomposition scheme is compared to a mathematical formulation and a standard implementation of Benders decomposition algorithm. In the experiments, two test sets from the literature are used, with 240 and 600 instances with up to 60 jobs and 5 machines. For the first set the proposed method performs 21.85% on average faster than the standard implementation of the Benders algorithm. For the second set the proposed method failed to find an optimal solution in only 31 in 600 instances, obtained an average gap of 0.07%, and took an average computational time of 377.86 s, while the best results of the other methods were 57, 0.17%, and 573.89 s, respectively

CLF-1 or 3β,6β,16β-trihydroxy lup-20(29)-ene chemical structure isolated from <i>C</i>. <i>leprosum</i> leaves alcoholic extract [16].

CLF-1 or 3β,6β,16β-trihydroxy lup-20(29)-ene chemical structure isolated from C. leprosum leaves alcoholic extract [16].</p

Main histopathological findings of hamsters infected with <i>Leishmania braziliensis</i> and treated with CLF-1.

(A) Uninfected ear (200x). (B) Untreated infected ear (200x). (C and E) Infected ear treated with Glucantime (100x and 400x, respectively). (D and F) Infected ear topically treated with CLF-1 (400x). Arrows indicate areas of neovascularization, black circle show an area with a granuloma with activated macrophages.</p

Production of cytokines <i>in vitro</i> by <i>Leishmania braziliensis</i> infected macrophages treated with CLF-1 for 24 (A) and 48 (B) hours.

L. braziliensis infected macrophages were treated with CLF-1 and IL-12, TNF-α, IL-4 and IL-10 production were measured in the supernatant. MØ: macrophages; L.b: Leishmania braziliensis infected macrophages; Glu: Glucantime; p< 0,0001.</p