Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Development of Bio-Based Polymers for Use in Asphalt, TR-639, 2014

Asphalt binder is typically modified with poly type (styrene-butadiene-styrene or SBS) polymers to improve its rheological properties and performance grade. The elastic and principal component of SBS polymers is butadiene. For the last decade, butadiene prices have fluctuated and significantly increased, leading state highway agencies to search for economically viable alternatives to butadiene based materials. This project reports the recent advances in polymerization techniques that have enabled the synthesis of elastomeric, thermoplastic, block-copolymers (BCPs) comprised of styrene and soybean oil, where the “B” block in SBS polymers is replaced with polymerized triglycerides derived from soybean oil. These new breeds of biopolymers have elastomeric properties comparable to well-established butadiene-based styrenic BCPs. In this report, two types of biopolymer formulations are evaluated for their ability to modify asphalt binder. Laboratory blends of asphalt modified with the biopolymers are tested for their rheological properties and performance grade. Blends of asphalt modified with the biopolymers are compared to blends of asphalt modified with two commonly used commercial polymers. The viscoelastic properties of the blends show that biopolymers improve the performance grade of the asphalt to a similar and even greater extent as the commercial SBS polymers. Results shown in this report indicate there is an excellent potential for the future of these biopolymers as economically and environmentally favorable alternatives to their petrochemically-derived analogs.

Low Cost Techniques of Base Stabilization, HR-312, 1994

This project was initiated in 1988 to study the effectiveness of four different construction techniques for establishing a stable base on a granular surfaced roadway. After base stabilization, the roadway was then seal coated, eliminating dust problems associated with granular surfaced roads. When monies become available, the roadway can be surfaced with a more permanent structure. A 2.8 mi (4.5 km) section of the Horseshoe Road in Dubuque County was divided into four divisions for this study. This report discusses the procedures used during construction of these different divisions. Problems and possible solutions have been analyzed to better understand the capabilities of the materials and construction techniques used on the project. The project had the following results: High structural ratings and soil K factors for the BIO CAT and Consolid bases did not translate to good roadway performance; the macadam base had the best overall performance; the tensar fabric had no noticeable effect on the macadam base; and the HFE-300 performed acceptably.

Optimization and Management of Materials in Earthwork Construction, TR-501, 2010

As a result of forensic investigations of problems across Iowa, a research study was developed aimed at providing solutions to identified problems through better management and optimization of the available pavement geotechnical materials and through ground improvement, soil reinforcement, and other soil treatment techniques. The overall goal was worked out through simple laboratory experiments, such as particle size analysis, plasticity tests, compaction tests, permeability tests, and strength tests. A review of the problems suggested three areas of study: pavement cracking due to improper management of pavement geotechnical materials, permeability of mixed-subgrade soils, and settlement of soil above the pipe due to improper compaction of the backfill. This resulted in the following three areas of study: (1) The optimization and management of earthwork materials through general soil mixing of various select and unsuitable soils and a specific example of optimization of materials in earthwork construction by soil mixing; (2) An investigation of the saturated permeability of compacted glacial till in relation to validation and prediction with the Enhanced Integrated Climatic Model (EICM); and (3) A field investigation and numerical modeling of culvert settlement. For each area of study, a literature review was conducted, research data were collected and analyzed, and important findings and conclusions were drawn. It was found that optimum mixtures of select and unsuitable soils can be defined that allow the use of unsuitable materials in embankment and subgrade locations. An improved model of saturated hydraulic conductivity was proposed for use with glacial soils from Iowa. The use of proper trench backfill compaction or the use of flowable mortar will reduce the potential for developing a bump above culverts.

Optimization of the procedure for removing iron deposits on ceramic filter media

In this thesis, cleaning of ceramic filter media was studied. Mechanisms of fouling and dissolution of iron compounds, as well as methods for cleaning ceramic membranes fouled by iron deposits were studied in the literature part. Cleaning agents and different methods were closer examined in the experimental part of the thesis. Pyrite is found in the geologic strata. It is oxidized to form ferrous ions Fe(II) and ferric ions Fe(III). Fe(III) is further oxidized in the hydrolysis to form ferric hydroxide. Hematite and goethite, for instance, are naturally occurring iron oxidesand hydroxides. In contact with filter media, they can cause severe fouling, which common cleaning techniques competent enough to remove. Mechanisms for the dissolution of iron oxides include the ligand-promoted pathway and the proton-promoted pathway. The dissolution can also be reductive or non-reductive. The most efficient mechanism is the ligand-promoted reductive mechanism that comprises two stages: the induction period and the autocatalytic dissolution.Reducing agents(such as hydroquinone and hydroxylamine hydrochloride), chelating agents (such as EDTA) and organic acids are used for the removal of iron compounds. Oxalic acid is the most effective known cleaning agent for iron deposits. Since formulations are often more effective than organic acids, reducing agents or chelating agents alone, the citrate¿bicarbonate¿dithionite system among others is well studied in the literature. The cleaning is also enhanced with ultrasound and backpulsing.In the experimental part, oxalic acid and nitric acid were studied alone andin combinations. Also citric acid and ascorbic acid among other chemicals were tested. Soaking experiments, experiments with ultrasound and experiments for alternative methods to apply the cleaning solution on the filter samples were carried out. Permeability and ISO Brightness measurements were performed to examine the influence of the cleaning methods on the samples. Inductively coupled plasma optical emission spectroscopy (ICP-OES) analysis of the solutions was carried out to determine the dissolved metals.

Covariance Matrix Estimation and Mean-Variance Optimization in application to International Diversification

Tutkimus keskittyy kansainväliseen hajauttamiseen suomalaisen sijoittajan näkökulmasta. Tutkimuksen toinen tavoite on selvittää tehostavatko uudet kovarianssimatriisiestimaattorit minimivarianssiportfolion optimointiprosessia. Tavallisen otoskovarianssimatriisin lisäksi optimoinnissa käytetään kahta kutistusestimaattoria ja joustavaa monimuuttuja-GARCH(1,1)-mallia. Tutkimusaineisto koostuu Dow Jonesin toimialaindekseistä ja OMX-H:n portfolioindeksistä. Kansainvälinen hajautusstrategia on toteutettu käyttäen toimialalähestymistapaa ja portfoliota optimoidaan käyttäen kahtatoista komponenttia. Tutkimusaieisto kattaa vuodet 1996-2005 eli 120 kuukausittaista havaintoa. Muodostettujen portfolioiden suorituskykyä mitataan Sharpen indeksillä. Tutkimustulosten mukaan kansainvälisesti hajautettujen investointien ja kotimaisen portfolion riskikorjattujen tuottojen välillä ei ole tilastollisesti merkitsevää eroa. Myöskään uusien kovarianssimatriisiestimaattoreiden käytöstä ei synnytilastollisesti merkitsevää lisäarvoa verrattuna otoskovarianssimatrisiin perustuvaan portfolion optimointiin.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Mapping the microstructure properties of the local tissues in the brain is crucial to understand any pathological condition from a biological perspective. Most of the existing techniques to estimate the microstructure of the white matter assume a single axon orientation whereas numerous regions of the brain actually present a fiber-crossing configuration. The purpose of the present study is to extend a recent convex optimization framework to recover microstructure parameters in regions with multiple fibers.

Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

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.

Search Engine Optimization Methods & Search Engine Indexing for CMS Applications

Search engine optimization & marketing is a set of processes widely used on websites to improve search engine rankings which generate quality web traffic and increase ROI. Content is the most important part of any website. CMS web development is now become very essential for most of organizations and online businesses to develop their online system and websites. Every online business using a CMS wants to get users (customers) to make profit and ROI. This thesis comprises a brief study of existing SEO methods, tools and techniques and how they can be implemented to optimize a content base website. In results, the study provides recommendations about how to use SEO methods; tools and techniques to optimize CMS based websites on major search engines. This study compares popular CMS systems like Drupal, WordPress and Joomla SEO features and how implementing SEO can be improved on these CMS systems. Having knowledge of search engine indexing and search engine working is essential for a successful SEO campaign. This work is a complete guideline for web developers or SEO experts who want to optimize a CMS based website on all major search engines.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Optimal design of 3R manipulators by using classical techniques and simulated annealin

In this paper, the optimum design of 3R manipulators is formulated and solved by using an algebraic formulation of workspace boundary. A manipulator design can be approached as a problem of optimization, in which the objective functions are the size of the manipulator and workspace volume; and the constrains can be given as a prescribed workspace volume. The numerical solution of the optimization problem is investigated by using two different numerical techniques, namely, sequential quadratic programming and simulated annealing. Numerical examples illustrate a design procedure and show the efficiency of the proposed algorithms.

Bio-ethanol valorization towards C4s including 1-butanol over metal modified alumina and zeolite catalysts

Bio-ethanol has been used as a fuel additive in modern society aimed at reducing CO2-emissions and dependence on oil. However, ethanol is unsuitable as fuel supplement in higher proportions due to its physico-chemical properties. One option to counteract the negative effects is to upgrade ethanol in a continuous fixed bed reactor to more valuable C4 products such as 1-butanol providing chemical similarity with traditional gasoline components. Bio-ethanol based valorization products also have other end-uses than just fuel additives. E.g. 1-butanol and ethyl acetate are well characterised industrial solvents and platform chemicals providing greener alternatives. The modern approach is to apply heterogeneous catalysts in the investigated reactions. The research was concentrated on aluminium oxide (Al2O3) and zeolites that were used as catalysts and catalyst supports. The metals supported (Cu, Ni, Co) gave very different product profiles and, thus, a profound view of different catalyst preparation methods and characterisation techniques was necessary. Additionally, acidity and basicity of the catalyst surface have an important role in determining the product profile. It was observed that ordinary determination of acid strength was not enough to explain all the phenomena e.g. the reaction mechanism. One of the main findings of the thesis is based on the catalytically active site which originates from crystallite structure. As a consequence, the overall evaluation of different by-products and intermediates was carried out by combining the information. Further kinetic analysis was carried out on metal (Cu, Ni, Co) supported self-prepared alumina catalysts. The thesis gives information for further catalyst developments aimed to scale-up towards industrially feasible operations.