The goal of this study is to advance the utility of functional brain imaging as a tool for the diagnosis and treatment of neurological disorders by creating a statistical database of functional MRI (fMRI) brain activation patterns collected from neurologically and psychiatrically unimpaired subjects. Continuous fMRI scans have been obtained from each subject while s/he performed a variety of cognitive tasks that are commonly found in standard neurological and cognitive assessment batteries. The collected fMRI data has been processed, analyzed, and converted into database which can be used as a reference of reliable indices of normal brain activity patterns for a wide range of cognitive functions.

Yes / Concrete with smart and functional properties (e.g., self-sensing, self-healing, and energy-harvesting) represents a transformative direction in the field of construction materials. Energy-harvesting concrete has the capability to store or convert the ambient energy (e.g., light, thermal, and mechanical energy) for feasible uses, alleviating global energy and pollution problems as well as reducing carbon footprint. The employment of energy-harvesting concrete can endow infrastructures (e.g., buildings, railways, and highways) with energy self-sufficiency, effectively promoting sustainable infrastructure development. This paper provides a systematic overview on the principles, fabrication, properties, and applications of energy-harvesting concrete (including light-emitting, thermal-storing, thermoelectric, pyroelectric, and piezoelectric concretes). The paper concludes with an outline of some future challenges and opportunities in the application of energy-harvesting concrete in sustainable infrastructures.

Portability of web applications between web servers of different organizations can be challenging and can complicate sharing and collaborative use of such tools. Given the distributed nature of the web, this lack of portability is usually not a concern because a user in one organization can link to and use a web application hosted by another organization. However, access control or differentiation may be needed by an organization in terms of area of interest, input data, analytical techniques, access control, presentation, branding, and language. This is true for many government organizations, and their associated web sites, and servers. In such cases, there are compelling political, branding, security, and privacy motivations that require each organization or agency to host and manage web applications on their own servers rather than using third party web sites over which they have little or no control. Also, web applications are classically developed by setting up a local software development and testing environment which can be challenging for new developers, be restricted by the software and hardware availability, cost significantly to obtain software development licenses and compatible hardware and is prone to code and data loss due to hardware damage or software corruptions. To simplify the discovery, deployment of web-based applications, I present the design, development, and testing of a system for discovering, installing, and configuring environmental analysis web applications on localized web servers. The system works with applications developed using Tethys Platform, which is an open-source software stack for creating geospatially enabled web-based applications. The developed Tethys App Store includes a Tethys application user interface that allows a server manager to retrieve applications from the central repository and install them on a local server with relatively simplicity, similar to the installation of a mobile application to a mobile device from a mobile application store. Next, I present the design concept of a cloud-based web application development platform, Tethys App Nursery, that attempts to overcome the above hurdles associated with localized development environments. A prototype of this system is developed and presented which is tightly integrated with Tethys platform and various cloud technologies provided by Amazon Web Services. The developed app nursery allows users to register for new Tethys portal instances in the cloud, develop new applications and test existing applications, without installing any local dependencies or development tools. Various cloud components used in this service's development as well as their associated costs are described. These systems were developed to support development of water and environmental analysis web apps for the international Group on Earth Observations (GEO) Global Water Sustainability (GEOGloWS) initiative of the National Aeronautics and Space Administration (NASA) and several partner organizations.

<p> In this thesis we develop and evaluate automated "expert systems" for two applications: (i) gas/oil pipeline inspection using magnetic flux leakage information, (ii) treatment efficacy prediction and medical diagnosis using electroencephalograph (EEG) and clinical information. Both applications share the same methodology and procedure as they employ machine learning methods which learn their decision models using the training data (or past examples in real life/environment).</p> <p> The magnetic flux leakage (MFL) technique is commonly used for nondestructive testing (NDT) of oil and gas pipelines which are mostly buried underground. This testing involves the detection of metal defects and anomalies in the pipe wall, and the evaluation of the severity of these defects. The difficulty with the MFL method is the extent and complexity of the analysis of the MFL images. In this thesis we show how modern machine learning techniques can be used to considerable advantage in this respect.</p> <p> The problem of identifying in advance the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, an automated medical expert system is designed and then evaluated. The system is capable of predicting the treatment response for each individual patient at the outset of a therapy (i.e., using pre-treatment information) thus improving therapeutic efficiency and reducing personal and economic costs. Our experiments are focused on treatment planning and diagnosis of mood disorders and psychiatric illnesses. Through different experiments, we have shown that it is possible to predict treatment efficacy of a 'selective serotonin reuptake inhibitor' (SSRI) antidepressant and 'repetitive transcranial magnetic stimulation' (rTMS) therapies for patients with treatment-resistant major depressive disorder (MDD) or major depression. The predictions are based on pre-treatment quantitative EEG measurements. Also, prediction of post-treatment schizophrenia symptomatic scores, using pre-treatment EEG data, showed significant performance in patients treated with the drug clozapine. Clozapine is an antipsychotic medication of superior effectiveness in treating Schizophrenia but has several potentially severe side effects.</p> <p> Medical diagnosis is the second problem we consider in the neuroscience aspects of this thesis. In this research, an automated digital medical diagnosis methodology is developed to estimate/detect the type of a disease or illness that a patient is suffering. This intelligent diagnostic system can assist the physician/clinician by offering a second opinion on diagnosis. Several complex psychiatric illnesses may have many common symptoms and accurate diagnosis can, at times, be very difficult. Efficient diagnosis helps by avoiding prescription of wrong therapy /treatment to a patient. In our limited experiments, EEG data is used to make a diagnosis for distinguishing between various psychiatric illnesses including MDD, schizophrenia, and the depressed phase of bipolar affective disorder (BAD).</p> <p> In all problems considered in this thesis, specifically the neuroscience problem, a large number of candidate features are extracted from measurement data but most candidate features are found to be irrelevant and have little or no discriminative power. Finding a few most discriminating features that guarantee numerical efficiency and obtain a smooth and generalizable decision function, is a major challenge in this research. In this thesis, feature selection methods based on mutual information or Kullback-Leibler (KL) distance is employed to find the most statistically relevant features. For the multi-class diagnosis problem, to improve performance, a feature selection procedure denoted as feature combination feature selection is used which first finds discriminating features in all binary classification combinations, and then combines them into a larger feature subset to make a final multi-class decision. The two-dimensional (2D) representation of the feature data is also found to be useful for clustering analysis. The overall method was evaluated using a nested cross-validation procedure for which over 80% average prediction performance is obtained in all experiments. The results indicate that machine learning methods hold considerable promise in solving the challenging problems encountered in the two applications of concern.</p> / Thesis / Doctor of Philosophy (PhD)

<p> The single selective inversion recovery experiment, developed by Bain and Cramer, has been used with great success in elucidating the molecular dynamics of three systems.</p> <p> The isomerization of d,l bis(1-indenyl)dimethylsilane to its meso isomer proceeds through sequential [1,5]-suprafacial shifts; ΔH+ for the process was evaluated as 21.9 ± 0.5 kcal/mol. There is only one mechanism operating at a detectable rate below about 150°C. Below 100°C this process is too slow to be detected by DNMR, but it is readily followed by classical kinetics methods. Above 100°C, the isomerization may be followed by 1D selective inversion experiments. The isoindene intermediate is conveniently trapped as its double Diels-Alder adduct showing that the rearrangement occurs relatively rapidly on the chemical time-scale.</p> <p> The barrier to hindered rotation about the Mn - C(4) sigma bond in (n^1 -Cpp)Mn(CO)3(PEt3)2 was measured. The observed value of ΔH+ was 13.1 ± 0.2 kcal/mol. ΔS+ was determined to be -11.2 ± 0.7 eu. As the compound is thermally sensitive, it would have been impossible to use lineshape analysis to determine the barrier. 1D selective inversion recovery experiments were used.</p> <p> A combination of 13C NOESY, 13C single selective inversion, and 13C lineshape analysis experiments identified the exchange pathways and determined temperature-dependent rate constants for the N,N'-[dimethyl-(2,2'dithiobisacetyl)]ethylenediamine (DADS) system. DADS exists as five exchanging rotamers in solution. Two of the conformers are symmetric, with C2 symmetry (ZZ1 and ZZ2). The other three conformers are asymmetric, with one amide group cis and the other trans (ZE1, ZE2, ZE3).</p> <p> The NOESY experiments gave a site-to-site map of the exchange processes at several temperatures. At room temperature, ZE1 is exchanging with both ZE2 and ZE3, but there appears to be no exchange between ZE2 and ZE3. This process seems to occur via hindered rotation about the disulfide bond, with ΔH+ = 15.3 ± 0.4 kcal/mol, and ΔS+ = -6.3 ± 1.1 eu.</p> <p> At higher temperatures, ZZ1 and ZZ2 start to exchange with ZE1 via hindered rotation about the amide bonds. ΔH+ for the process was determined to be 19.8 ± 0.4 kcal/mol, and ΔS+ was found to be 0.7 ± 1.2 eu. The barrier agrees quite well with that measured for the uncyclized precursor to DADS. ΔH+ was found to be 19.3 ± 0.7 kcal/mol, while ΔS+ was determined to be 2.5 ± 2.1 eu.</p> / Thesis / Master of Science (MSc)

<p> The rationale for this project is based on the recognition that chemistry courses tend to be taught too much from a theoretical standpoint, with little reference to everyday life. This is one of the reasons that a majority of students think that chemistry is difficult, boring, tedious, and uninteresting (Worthy, 1982). If they have the choice, many students would rather not take a chemistry course, and if they do, it will probably be their last course in Chemistry.</p> <p> It is the intent of the Ontario Curriculum Guidelines to provide some science-technology-society connections. The aim of this project is to provide supplemental science-technology society connections, and selected concrete examples of practical, everyday chemistry for teachers, so that they may enrich their classes, motivate their students, and put theory into an appropriate context. If classes are more interesting and relevant to the world of the students, then more students could be motivated to take chemistry courses and consider continuing to more advanced classes. A second purpose for this project is to stimulate a typical non-science student's interest in chemistry and science. It is even more necessary to motivate these students by providing interesting connections with the real world and suitable applications of theory and principles. These connections with the real world are important for such students, so that they will be better able to make informed decisions as scientifically literate citizens, managers, or politicians, not only for themselves, but for the benefit of society as a whole.</p> <p> To accomplish the aims of this project, two or three short hand-outs of practical everyday chemistry were prepared for each of the core topics in the Grade 11 (SCH 3A) and Chemistry OAC (SCH OA) courses. A few of the examples included Dental Chemistry, Culinary Chemistry, Insect Pheromones, and Teflon.</p> <p> Results of the survey taken from chemistry teachers showed that these hand-outs would better motivate students to study chemistry. Teachers think it is useful for their classes. They would like a compilation of these examples, if one were to be made available.</p> / Thesis / Master of Science (Teaching)

<p> This thesis is concerned with 2,21 -dimercaptodiethyl sulfide. In particular, the work reported herein deals with the stability of the reagent in both its pure form and in its solutions; the determination of its acid dissociation constants; its reactivity towards metal ions; the nature of its metal complexes with Co(II), Co(III), Ni(II) and Pd(II); and its application as a potentially useful analytical reagent for the spectrophotometric determination of Ni(II) and Pd(II). </p> / Thesis / Master of Science (MSc)

No

Applications for Wireless Sensor Networks can be updated dynamically by means of wireless upgrade mechanisms. Current research efforts in wireless upgrade mechanisms for WSN have focused on transmitting application packets for upgrades via wireless medium. However, these schemes require significant overhead involved in sending and receiving application packets that affect the sensor operation, in addition to bringing the nodes down to reprogram and restart them. By designing applications in a way that allows dynamic functionality changes during operation, the overhead and sensor delays can be eliminated. Dynamically Controllable Application (DCA) is a novel scheme for designing WSN applications whose behavior can be rapidly and dynamically changed during operation. The results indicate that a veritable functionality change is achieved in a span of a few milliseconds.

No description available.