Burocracia e crescimento : uma avaliação empírica entre países

Monografia (graduação)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Departamento de Economia, 2015.A barreira à entrada de novas empresas no mercado vem sendo apontada como um grande limitador do crescimento econômico do Brasil. Um ambiente econômico competitivo gera a necessidade do setor privado a constantemente criar novos produtos ou processos para manter-se na ponta do processo produtivo. Nesse contexto, os países estão cada vez mais preocupados em manter um ecossistema de inovação equilibrado como forma de buscar um crescimento econômico de longo prazo e sustentável. São cada vez mais comuns estudos dos fatores desse ecossistema que estão gerando impacto e, principalmente, de indicadores que influenciam o setor privado, uma vez que este é apontado, pela literatura econômica, como um dos motores do crescimento

A mobilidade urbana de Brasília : um estudo descritivo em comparação com as propostas de uma cidade inteligente

Monografia (graduação)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Departamento de Administração, 2016.Este estudo tem como objetivo analisar a mobilidade urbana de Brasília, em comparação com os princípios de Cidades Inteligentes. Para tal, procedeu-se análise documental, de três entrevistas realizadas com especialistas na área de mobilidade urbana e de 203 questionários aplicados a moradores do Distrito Federal e do Entorno. A análise dos resultados revelou uma distância significativa entre o atual sistema de mobilidade de Brasília e o de Cidades Inteligentes. Em termos de gestão, há desalinhamento entre as dimensões organizacional e social e falta, sobretudo, participação pública nos planos de governo. Os investimentos tecnológicos são pontuais e não há infraestrutura física de qualidade ou sistema de mobilidade integrado, estável e sustentável. Diante de tais problemas, este trabalho torna-se um alerta aos que atuam não apenas na área de mobilidade urbana, mas a todos os setores abarcados pelas Cidades Inteligentes

Effects of the neuronal phosphoprotein synapsin I on actin polymerization. I. Evidence for a phosphorylation-dependent nucleating effect.

Synapsin I is a synaptic vesicle-specific phosphoprotein which is able to bind and bundle actin filaments in a phosphorylation-dependent fashion. In the present paper we have analyzed the effects of synapsin I on the kinetics of actin polymerization and their modulation by site-specific phosphorylation of synapsin I. We found that dephosphorylated synapsin I accelerates the initial rate of actin polymerization and decreases the rate of filament elongation. The effect was observed at both low and high ionic strength, was specific for synapsin I, and was still present when polymerization was triggered by F-actin seeds. Dephosphorylated synapsin I was also able to induce actin polymerization and bundle formation in the absence of KCl and MgCl2. The effects of synapsin I were strongly decreased after its phosphorylation by Ca2+/calmodulin-dependent protein kinase II. These observations suggest that synapsin I has a phosphorylation-dependent nucleating effect on actin polymerization. The data are compatible with the view that changes in the phosphorylation state of synapsin I play a functional role in regulating the interactions between the nerve terminal cytoskeleton and synaptic vesicles in various stages of the exoendocytotic cycle

Laser nano-neurosurgery from gentle manipulation to nano-incision of neuronal cells and scaffolds: an advanced neurotechnology tool

Current optical approaches are progressing far beyond the scope of monitoring the structure and function of living matter, and they are becoming widely recognized as extremely precise, minimally-invasive, contact-free handling tools. Laser manipulation of living tissues, single cells, or even single-molecules is becoming a well-established methodology, thus founding the onset of new experimental paradigms and research fields. Indeed, a tightly focused pulsed laser source permits complex tasks such as developing engineered bioscaffolds, applying calibrated forces, transfecting, stimulating, or even ablating single cells with subcellular precision, and operating intracellular surgical protocols at the level of single organelles. In the present review, we report the state of the art of laser manipulation in neuroscience, to inspire future applications of light-assisted tools in nano-neurosurgery

HDAC6 and RhoA are novel players in Abeta-driven disruption of neuronal polarity

n/

Optimization Loop Algorithm for Adsorbed Natural Gas Storage Systems

In the past few years, the development of inverse design and optimization methods has opened up new possibilities. The so-called Adjoint method is of great significance in that context, since it permits high fidelity to flow-physics at comparatively low computational costs. The present work is a sequel of a previous one presented in WCCM2018, called 'On the use of the Adjoint Method to evaluate sensitivities in adsorbed natural gas storage systems'. where one have developed and validated an Adjoint based approach to computing sensitivity derivatives for adsorbed natural gas (ANG) storage systems. The main goal of this work is to, by using the approach to compute sensitivities presented before, obtain and validate a basic structure of an optimization loop algorithm (OLA) for optimization of natural gas storage systems. Both flow and Adjoint solvers, which were previously developed, are assembled in FREEFEM++ platform. The OLA consists on solving sequential problems to achieve an optimal configuration of parameters that maximize/minimize an objective functional. It starts by solving the primal problem (flow solver), which consists in a physics flow solution, followed by the dual problem, based on the Adjoint Method. With both solutions, the OLA receives the sensitivity derivatives with respect to parameters and, if the configuration is not the optimal, a new values of parameters is obtained and the cycle restarts. To validate the OLA, we make use of the inverse design optimization, defining the objective functional as the mean square error, MSE, of the actual density of adsorption distribution q, with respect to an user--defined target distribution, qt. The strategy is generated a target distribution with a known filling flow curve and the OLA, starting the optimization cycles with other flow curve, minimizing the functional, finding the same curve as we use to generate qt. The results of the several tests showed that the OLA have the capacity to regenerate the original curves, proving the consistency of the source code. The next step for the future researchers is the application for the engineering purposes, by using operational requirements to optimize the process

A numerical analysis of CO2 storage by adsorption using ZIF-8

In 21st century, the reduction of CO2 concentration in the atmosphere is one of the most challenges of the humanity, specifically in the engineering. To start a possibility solution proposal, this work consisted in an analysis of carbon dioxide storage, using adsorption by ZIF8, a material that belongs to a class called Zeolitic Imidazolate Frameworks, which have high porosity, high thermal resistance and chemical stability. The main contribution of this work is to verify which parameters are relevant in the CO2 storage capacity by adsorption. To archive this goal, the study was made through computational simulations using the open source FreeFem++ software, inputting a specified quantity of pure CO2, entering in an 1,82 liter tank filled by the adsorbent until its internal pressure reached 1,0 MPa. First, the isothermal curve was validated with the literature, and after adjusting the parameters of adsorption model, called Dubinin Astakov (D-A). The simulations were performed, varying CO2 inlet flow, the tank’s aspect ratio with the values of 1; 1,9; 3; 5 and 7, and the external wall’s heat transfer coefficient with values of 5, 700 and 1000 W/m²K. Each simulation generated at each step the tank’s average and maximum temperatures, internal pressure, and the carbon dioxide adsorption density. All the simulations started with a standard temperature of 300 K and pressure of 100 kPa. Temperature and adsorption density distributions were generated to analyze in which part of the tank the adsorption is higher. The results showed that the regions where the temperatures are higher, the adsorption is lower, and in the end of the simulation, the simulations with the lower average temperatures had the higher adsorption density. The highest values of adsorption density were obtained with higher surface areas under the influence of forced convection, rather than natural convection, and with lower CO2 inlet flow. The highest adsorption density reached was 15,67 %, in a simulation with 50% of the tank’s volume per minute as CO2 inlet flow rate, aspect ratio of 7,0; and 700 W/m²K heat transfer coefficient. The average temperature obtained in the end of this simulation was 326,20 K and it took 3644 seconds for the tank to achieve the internal pressure of 1,0 MPa

motility flow and growth cone navigation analysis during in vitro neuronal development by long term bright field imaging

A long-term live-imaging workstation to follow the development of cultured neurons during the first few days in vitro (DIV) is developed. In order to monitor neuronal polarization and axonal growth by live imaging, we built a micro-incubator system that provides stable temperature, pH, and osmolarity in the culture dish under the microscope, while preserving environment sterility. We are able to image living neurons at 2 DIVs for 48 h with a temporal resolution of one frame for every 2 min. The main features of this system are its ability to adapt to every cell-culture support, to integrate in any optical microscope, because of the relatively small dimensions (9.5×6.5×2.5  cm ) and low weight of the system (<200  g ), and to monitor the physiological parameters in situ. Moreover, we developed an image-analysis algorithm to quantify the cell motility, in order to characterize its complex temporal-spatial pattern. The algorithm applies morphological image processing operations on the temporal variations occurring in the inspected region of interest. Here, it is used to automatically detect cellular motility in three distinct morphological regions of the neurons: around the soma, along the neurites, and in the growth cone