Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

AbstractObjective:The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients' body mass index.Materials and Methods:The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality.Results:An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes.Conclusion:The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.

Barriers and Motivators for Using Open Educational Resources in Schools

In an explorative study, we investigated on German schoolteachers how they use, reuse, produce and manage Open Educational Resources. The main questions in this research have been, what their motivators and barriers are in their use of Open Educational Resources, what others can learn from their Open Educational Practices, and what we can do to raise the dissemination level of OER in schools.

Bidding support for computational resources

Peer-reviewed

The use of future-oriented knowledge in regional innovation processes: Research on knowledge generation, transfer and conversion

The importance of the regional level in research has risen in the last few decades and a vast literature in the fields of, for instance, evolutionary and institutional economics, network theories, innovations and learning systems, as well as sociology, has focused on regional level questions. Recently the policy makers and regional actors have also began to pay increasing attention to the knowledge economy and its needs, in general, and the connectivity and support structures of regional clusters in particular. Nowadays knowledge is generally considered as the most important source of competitive advantage, but even the most specialised forms of knowledge are becoming a short-lived resource for example due to the accelerating pace of technological change. This emphasizes the need of foresight activities in national, regional and organizational levels and the integration of foresight and innovation activities. In regional setting this development sets great challenges especially in those regions having no university and thus usually very limited resources for research activities. Also the research problem of this dissertation is related to the need to better incorporate the information produced by foresight process to facilitate and to be used in regional practice-based innovation processes. This dissertation is a constructive case study the case being Lahti region and a network facilitating innovation policy adopted in that region. Dissertation consists of a summary and five articles and during the research process a construct or a conceptual model for solving this real life problem has been developed. It is also being implemented as part of the network facilitating innovation policy in the Lahti region.

Orthologous and heterologous expression of a protein from Saccharomyces cerevisiae: Optimization for a biotechnological application

In this thesis (TFG) the results of the comparison between different methods to obtain a recombinant protein, by orthologous and heterologous expression, are exposed. This study will help us to identify the best way to express and purify a recombinant protein that will be used for biotechnology applications. In the first part of the project the goal was to find the best expression and purification system to obtain the recombinant protein of interest. To achieve this objective, a system expression in bacteria and in yeast was designed. The DNA was cloned into two different expression vectors to create a fusion protein with two different tags, and the expression of the protein was induced by IPTG or glucose. Additionally, in yeast, two promoters where used to express the protein, the one corresponding to the same protein (orthologous expression), and the ENO2 promoter (heterologous expression). The protein of interest is a NAD-dependent enzyme so, in a second time, its specific activity was evaluated by coenzyme conversion. The results of the TFG suggest that, comparing the model organisms, bacteria are more efficient than yeast because the quantity of protein obtained is higher and better purified. Regarding yeast, comparing the two expression mechanisms that were designed, heterologous expression works much better than the orthologous expression, so in case that we want to use yeast as expression model for the protein of interest, ENO2 will be the best option. Finally, the enzymatic assays, done to compare the effectiveness of the different expression mechanisms respect to the protein activity, revealed that the protein purified in yeast had more activity in converting the NAD coenzyme.

The temporal dynamics of resource use by frugivorous birds: a network approach

Ecological network patterns are influenced by diverse processes that operate at different temporal rates. Here we analyzed whether the coupled effect of local abundance variation, seasonally phenotypic plastic responses, and species evolutionary adaptations might act in concert to shape network patterns. We studied the temporal variation in three interaction properties of bird species (number of interactions per species, interaction strength, and interaction asymmetry) in a temporal sequence of 28 plant frugivore interaction networks spanning two years in a Mediterranean shrubland community. Three main hypotheses dealing with the temporal variation of network properties were tested, examining the effects of abundance, switching behavior between alternative food resources, and morphological traits in determining consumer interaction patterns. Our results demonstrate that temporal variation in consumer interaction patterns is explained by short-term variation in resource and bird abundances and seasonal dietary switches between alternative resources (fleshy fruits and insects). Moreover, differences in beak morphology are associated with differences in switching behavior between resources, suggesting an important role of foraging adaptations in determining network patterns. We argue that beak shape adaptations might determine generalist and specialist feeding behaviors and thus the positions of consumer species within the network. Finally, we provide a preliminary framework to interpret phylogenetic signal in plant animal networks. Indeed, we show that the strength of the phylogenetic signal in networks depends on the relative importance of abundance, behavioral, and morphological variables. We show that these variables strongly differ in their phylogenetic signal. Consequently, we suggest that moderate and significant phylogenetic effects should be commonly observed in networks of species interactions. Read More: http://www.esajournals.org/doi/abs/10.1890/07-1939.1

Optimization of methodology to analyze ascorbic and dehydroascorbic acid in vegetables

In this study, different solutions to extract vitamin C were tested. High-performance liquid chromatography was chosen and the conditions were based on isocratic elution in reverse phase column. Dehydroascorbic acid was determined indirectly after its reduction using dithiothreitol. The use of metaphosphoric acid to stabilize the vitamin C was shown to be required and it was necessary to neutralize the pH of the extract to apply dithiothreitol. The average recovery was 90% in collard and tomato samples. The presence of oil did not interfere in extraction and the methodology can be used to analyze stir fried vegetables.

Química Sem Fronteiras: o desafio da energia

Coal, natural gas and petroleum-based liquid fuels are still the most widely used energy sources in modern society. The current scenario contrasts with the foreseen shortage of petroleum that was spread out in the beginning of the XXI century, when the concept of "energy security" emerged as an urgent agenda to ensure a good balance between energy supply and demand. Much beyond protecting refineries and oil ducts from terrorist attacks, these issues soon developed to a portfolio of measures related to process sustainability, involving at least three fundamental dimensions: (a) the need for technological breakthroughs to improve energy production worldwide; (b) the improvement of energy efficiency in all sectors of modern society; and (c) the increase of the social perception that education is a key-word towards a better use of our energy resources. Together with these technological, economic or social issues, "energy security" is also strongly influenced by environmental issues involving greenhouse gas emissions, loss of biodiversity in environmentally sensitive areas, pollution and poor solid waste management. For these and other reasons, the implementation of more sustainable practices in our currently available industrial facilities and the search for alternative energy sources that could partly replace the fossil fuels became a major priority throughout the world. Regarding fossil fuels, the main technological bottlenecks are related to the exploitation of less accessible petroleum resources such as those in the pre-salt layer, ranging from the proper characterization of these deep-water oil reservoirs, the development of lighter and more efficient equipment for both exploration and exploitation, the optimization of the drilling techniques, the achievement of further improvements in production yields and the establishment of specialized training programs for the technical staff. The production of natural gas from shale is also emerging in several countries but its production in large scale has several problems ranging from the unavoidable environmental impact of shale mining as well as to the bad consequences of its large scale exploitation in the past. The large scale use of coal has similar environmental problems, which are aggravated by difficulties in its proper characterization. Also, the mitigation of harmful gases and particulate matter that are released as a result of combustion is still depending on the development of new gas cleaning technologies including more efficient catalysts to improve its emission profile. On the other hand, biofuels are still struggling to fulfill their role in reducing our high dependence on fossil fuels. Fatty acid alkyl esters (biodiesel) from vegetable oils and ethanol from cane sucrose and corn starch are mature technologies whose market share is partially limited by the availability of their raw materials. For this reason, there has been a great effort to develop "second-generation" technologies to produce methanol, ethanol, butanol, biodiesel, biogas (methane), bio-oils, syngas and synthetic fuels from lower grade renewable feedstocks such as lignocellulosic materials whose consumption would not interfere with the rather sensitive issues of food security. Advanced fermentation processes are envisaged as "third generation" technologies and these are primarily linked to the use of algae feedstocks as well as other organisms that could produce biofuels or simply provide microbial biomass for the processes listed above. Due to the complexity and cost of their production chain, "third generation" technologies usually aim at high value added biofuels such as biojet fuel, biohydrogen and hydrocarbons with a fuel performance similar to diesel or gasoline, situations in which the use of genetically modified organisms is usually required. In general, the main challenges in this field could be summarized as follows: (a) the need for prospecting alternative sources of biomass that are not linked to the food chain; (b) the intensive use of green chemistry principles in our current industrial activities; (c) the development of mature technologies for the production of second and third generation biofuels; (d) the development of safe bioprocesses that are based on environmentally benign microorganisms; (e) the scale-up of potential technologies to a suitable demonstration scale; and (f) the full understanding of the technological and environmental implications of the food vs. fuel debate. On the basis of these, the main objective of this article is to stimulate the discussion and help the decision making regarding "energy security" issues and their challenges for modern society, in such a way to encourage the participation of the Brazilian Chemistry community in the design of a road map for a safer, sustainable and prosper future for our nation.

Use of multivariate experimental designs for optimizing the reductive degradation of an azo dye in the presence of redox mediators

The optimization of the anaerobic degradation of the azo dye Remazol golden yellow RNL was performed according to multivariate experimental designs: a 2² full-factorial design and a central composite design (CCD). The CCD revealed that the best incubation conditions (90% color removal) for the degradation of the azo dye (50 mg L- 1) were achieved with 350 mg L- 1 of yeast extract and 45 mL of anaerobic supernatant (free cell extract) produced from the incubation of 650 mg L- 1 of anaerobic microorganisms and 250 mg L- 1 of glucose. A first-order kinetics model best fit the experimental data (k = 0.0837 h- 1, R² = 0.9263).

Ydinvoimalaitoksen vuosihuoltoajankohdan optimointi

Viimeaikoina ydinvoima on ollut vahvasti esillä mediassa. Keskustelut lisäydinvoimasta, sähköntuotantomuodoista, Olkiluodon kolmannen ydinvoimalaitosyksikön rakennustöistä, sähkön kulutuksen tulevaisuudesta ja nykyisestä taloustilanteesta ovat vaikuttaneet tarpeeseen tutkia sähkön tuotantokustannuksia ydinvoiman osalta. Tutkimuksessa keskitytään erityisesti ydinvoimalaitosyksiköiden vuosihuolto- ja polttoainekustannuksiin, jotka muodostavat suurimman suunnitellun yksittäisen kustannuserän ydinvoiman käyttöön liittyen. Työ tehdään Teollisuuden Voima Oyj:lle, joka pääsääntöisesti toimii Eurajoen Olkiluodossa. Työssä optimoidaan jokaiselle Olkiluodon ydinvoimalaitosyksikölle mahdollisimman edullinen vuosihuoltoajankohta. Optimaalisin ajankohta määrittyy edullisimman sähkön hinnan, ihanteellisimman käyttöjakson pituuden sekä resurssien saatavuuden perusteella. Ydinvoimalaitosyksiköiden vuosihuoltoajankohdat suunnitellaan siten, että vuosihuollot ovat kokonaisuudessaan ja laitosyksikkökohtaisesti optimaaliset. Työn lopputuloksena on esitys Olkiluodon ydinvoimalaitosyksiköiden optimaalisista vuosihuoltoajankohdista. Työn tuloksien myötä Teollisuuden Voima Oyj:llä on mahdollisuus pienentää vuosihuoltokustannuksiaan ja osaltaan vaikuttaa ydinvoimalla tuotetun sähkön kannattavuuteen. Vuosihuoltoajankohdan optimointi palvelee myös Teollisuuden Voima Oyj:n osakkaiden vaatimuksia.

Use of experimental design in the optimisation of a solid phase preconcentration system for Cobalt determination by GFAAS

In this work is proposed a solid phase preconcentration system of Co2+ ions and its posterior determination by GFAAS in which fractional factorial design and response surface methodology (RSM) were used for optimization of the variables associated with preconcentration system performance. The method is based on cobalt extraction as a complex Co2+-PAN (1:2) in a mini-column of polyurethane foam (PUF) impregnated with 1-(2-pyridylazo)-naphthol (PAN) followed by elution with HCl solution and its determination by GFAAS. The chemical and flow variables studied were pH, buffer concentration, eluent concentration and preconcentration and elution flow rates. Results obtained from fractional factorial design 2(5-1) showed that only the variables pH, buffer concentration and interaction (pH X buffer concentration) based on analysis of variance (ANOVA) were statistically significant at 95% confidence level. Under optimised conditions, the method provided an enrichment factor of 11.6 fold with limit of detection and quantification of 38 and 130 ng L-1, respectively, and linear range varying from 0.13 to 10 µg L-1. The precision (n = 9) assessed by relative standard deviation (RSD) was respectively 5.18 and 2.87% for 0.3 and 3.0 µg L-1 cobalt concentrations.

Use Of Systems Approach with Total Quality Management in Industrial Organizations

The objective of the work has been to study why systems thinking should be used in combination with TQM, what are the main benefits of the integration and how it could best be done. The work analyzes the development of systems thinking and TQM with time and the main differences between them. The work defines prerequisites for adopting a systems approach and the organizational factors which embody the development of an efficient learning organization. The work proposes a model based on combination of an interactive management model and redesign to be used for application of systems approach with TQM in practice. The results of the work indicate that there are clear differences between systems thinking and TQM which justify their combination. Systems approach provides an additional complementary perspective to quality management. TQM is focused on optimizing operations at the operational level while interactive management and redesign of organization are focused on optimization operations at the conceptual level providing a holistic system for value generation. The empirical study demonstrates the applicability of the proposed model in one case study company but its application is tenable and possible also beyond this particular company. System dynamic modeling and other systems based techniques like cognitive mapping are useful methods for increasing understanding and learning about the behavior of systems. The empirical study emphasizes the importance of using a proper early warning system.

Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.