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The True Complexities of “Standard” Family Medical Practice Unmasked: An Observational Cross-Sectional Study in Regina
No full textLord of the Meaning: An Examination of Interpretive Theories
Get PDFAn examination of interpretive theories using Tolkien's The Lord of the Rings as an example
Stories of Professional Identity Authored by Early Childhood Educators in Yukon
Get PDFIn the face of increased public interest and government investment, Canadian policy makers and
early childhood educators (ECEs) now have choices to make about the meaning and purpose of
early childhood education within this country. The choices made now will have a considerable
impact on the lives of our youngest children and those who devote their lives to learning with
them. This study fills a gap in research in the field of early childhood education and gives
visibility to Early Childhood Educator’s experiences that led them into the early learning field
and how they conceptualize and experience their work.
Grounded within a social constructivist perspective, this study dances with a bricolage
approach to research that weaves together feminist epistemology, ethnographic research, a
figured worlds framework, the hundred languages of children, a pedagogy of listening and a life
history approach to describe and gain meaning from stories of becoming and being an ECE in
Yukon. The findings make visible how dominant discourses, workplace contexts, and the larger
structures of the field of ECE and our society, interact with ECEs’ negotiation of their
professional identities. Prevalent within the stories of being an ECE in Yukon was a culture of
isolation that stemmed from the current governing system and the market model approach to
early learning that dominates the field. Findings aligned with previous research and revealed that
the image of early childhood education in Yukon is shaped by dominant discourses that are
steeped in issues related to gender, a persistent care vs education dichotomy, and economic
investment discourses (Arndt et al., 2021; Langford et al., 2017; Lightfoot & Frost, 2014;
MacDonell & McCorquodale, 2019; Moss, 2006; Moss 2004; Tukonic & Hardwood, 2016;
Tukonic & Hardwood, 2017; Woodrow, 2007). Participants' stories highlighted a pervasive
culture of isolation in the field, leading to feelings of being unseen and unheard, and ultimately, the rejection of an Early Childhood Educator professional identity in Yukon. The overarching
findings indicated that while current investments within the field have the potential positivity
influence societal perceptions and working conditions for ECEs there is still a long way to go
before the early childhood education in Yukon is recognized and valued as a profession.
Ultimately, ECEs in Yukon remain undervalued and underappreciated
LAW WITHOUT ORDER: LOWER COURT SENTENCING, THE APPLICATION OF GLADUE PRINCIPLES, AND JOINT SENTENCING PRACTICES IN CANADA
No full textThe abstract of this item is unavailable due to an embargo
Prescribing Opioids in Primary Care Settings: Experiences of Nurse Practitioners
Get PDFAbstract
Many Canadians access health care for the management of acute or chronic pain. Therapeutic pain management approaches provided by nurse practitioners (NPs) may involve non-pharmacological options and the prescription of medications. When opioids are prescribed by NPs, there is a need for awareness of the concerns for opioid abuse and development of dependence, misuse related to a lack of medication education, diversion of the medication for potential financial gain, and obtaining opioids illegally when prescriptions are tapered or discontinued: which all have been implicated for concerns regarding opioid prescribing and the present opioid crisis (Canadian Centre on Substance Use and Addiction, 2020).
The purpose of this study was to explore the experiences of the NPs who prescribe opioids in primary care settings within the province of Saskatchewan. The following question guided this study: What are the experiences of NPs who prescribe opioids in primary care settings? Interpretive Description was chosen as the guiding method for this inquiry: as interpretive description is most often used to explore practice based clinical questions. Through the use of the scaffolding approach in Interpretive Description (Thorne, 2016), a scoping review of the literature was performed that identified themes across a small number of peer reviewed articles from international studies, and a gap in the Canadian literature on the study phenomena.
The qualitative inductive approach of Interpretive Description was chosen to develop nursing knowledge about opioid prescribing by NPs using interview data collection and analysis. Information about the study and a link to a recruitment survey was distributed to NPs in collaboration with a provincial regulatory body. The recruitment survey asked respondents to complete demographic and practice questions about their practice of opioid prescribing and indicate their interest in participating in an interview on the topic. This purposive sampling method used a modified Dillman approach, recruited 21 volunteers to conduct semi - structured interviews (Dillman et al., 2014).
Constant comparative analysis of the interview data resulted in two focus areas of thematic development: the practice concerns involved in prescribing opioids and the decision-making process employed by NPs in addressing pain management. Findings from the thematic analysis of practice experiences when prescribing opioids identified three primary themes: learning to prescribe, gaining competence and confidence, and experiencing concerns for personal safety. A second descriptive thematic analysis explored the participants’ decision-making when prescribing opioids in primary care clinical settings. This analysis identified three themes that influence participant decision-making in practice: negotiating practice autonomy boundaries, applying clinical practice guidelines, and retribution from authorities.
Findings from the analyses suggests that participants with more years of experience felt their educational preparation was appropriate; however, participants with fewer years of experience felt hesitant and underprepared for the associated level of accountability and responsibility. The outcomes identified a need for increased knowledge and support for NPs when prescribing opioids and a need for policy change within electronic health records to identify clients with opioid contracts to mitigate the potential of opioid prescription abuse, misuse, and diversion
Robust Model Predictive Control for Linear Parameter Varying Systems along with Exploration of its Application in Medical Mobile Robots
Get PDFThis thesis seeks to develop a robust model predictive controller (MPC) for Linear Parameter Varying (LPV) systems. LPV models based on input-output display are employed. We aim to improve robust MPC methods for LPV systems with an input-output display. This improvement will be examined from two perspectives. First, the system must be stable in conditions of uncertainty (in signal scheduling or due to disturbance) and perform well in both tracking and regulation problems. Secondly, the proposed method should be practical, i.e., it should have a reasonable computational load and not be conservative.
Firstly, an interpolation approach is utilized to minimize the conservativeness of the MPC. The controller is calculated as a linear combination of a set of offline predefined control laws. The coefficients of these offline controllers are derived from a real-time optimization problem. The control gains are determined to ensure stability and increase the terminal set.
Secondly, in order to test the system's robustness to external disturbances, a free control move was added to the control law. Also, a Recurrent Neural Network (RNN) algorithm is applied for online optimization, showing that this optimization method has better speed and accuracy than traditional algorithms. The proposed controller was compared with two methods (robust MPC and MPC with LPV model based on input-output) in reference tracking and disturbance rejection scenarios. It was shown that the proposed method works well in both parts. However, two other methods could not deal with the disturbance.
Thirdly, a support vector machine was introduced to identify the input-output LPV model to estimate the output. The estimated model was compared with the actual nonlinear system outputs, and the identification was shown to be effective. As a consequence, the controller can accurately follow the reference.
Finally, an interpolation-based MPC with free control moves is implemented for a wheeled mobile robot in a hospital setting, where an RNN solves the online optimization problem. The controller was compared with a robust MPC and MPC-LPV in reference tracking, disturbance rejection, online computational load, and region of attraction. The results indicate that our proposed method surpasses and can navigate quickly and reliably while avoiding obstacles
Investigation of Nuclear Motion Effects in NEXAFS Spectroscopy
Get PDFNear Edge X-ray Absorption Spectroscopy (NEXAFS) is a widely used tool for the chemical analysis of organic materials. Sensitivity of this spectroscopic technique is based on spectral relationships such as functional group identity, oxidation states and electronic structures which are interpreted in terms of electronic transitions from core electrons to unoccupied levels. Recent research shows nuclear motion in the form of thermally populated vibrations, gauche defects, conformational changes, etc., contributing to the shape of specific lines in NEXAFS spectra.
Previous work on nuclear motion effects in NEXAFS focused on n-alkane systems. The work in this project expanded to study polymer and conjugated aromatic systems. Experimental NEXAFS spectra and MD-DFT simulations were examined at temperatures ranging from room temperature down to liquid nitrogen temperatures. Three molecular systems were examined: molecules with an isotopic/atomic substitution, molecules with and without low energy vibrations as well as molecules with vibrations presumed to be localized to a moiety.
MD-DFT simulations highlight nuclear motion effects in the form of lower peak intensity and peak broadening at higher temperatures due to a lower energy onset of the rising edge of the NEXAFS peak. Experimental NEXAFS spectra also show temperature dependent effects in the form of peak widths differing across temperature although these results are not consistent as a function of temperature.
The objective of this project was to see if a predictive model could be established to describe nuclear motion effects in NEXAFS spectra. A simplified model was used from previous work on nuclear motion effects in n-alkane systems to attempt to describe the effects observed in this project. The results have shown that the current models do not provide the answers for all the observations in both MD-DFT simulations and experimental NEXAFS spectra
Anatomical Classification of the Gastrointestinal Tract Using Ensemble Transfer Learning
Get PDFEndoscopy is a procedure used to visualize disorders of the gastrointestinal (GI) lumen. GI disorders can occur without symptoms, which is why gastroenterologists often recommend routine examinations of the GI tract. It allows a doctor to directly visualize the inside of the GI tract and identify the cause of symptoms, reducing the need for exploratory surgery or other invasive procedures. It can also detect the early stages of GI disorders, such as cancer, enabling prompt treatment that can improve outcomes. Endoscopic examinations generate significant numbers of GI images. Because of this vast amount of endoscopic image data, relying solely on human interpretation can be problematic. Artificial intelligence is gaining popularity in clinical medicine. Assist in medical image analysis and early detection of diseases, help with personalized treatment planning by analyzing a patient’s medical history and genomic data, and be used by surgical robots to improve precision and reduce invasiveness. It enables automated diagnosis, provides physicians with assistance, and may improve performance. One of the significant challenges is defining the specific anatomic locations of GI tract abnormalities. Clinicians can then determine appropriate treatment options, reducing the need for repetitive endoscopy. Due to the difficulty of collecting annotated data, very limited research has been conducted on the localization of anatomical locations by classification of endoscopy images. In this study, we present a classification of GI tract anatomical localization based on transfer learning and ensemble learning. Our approach involves the use of an autoencoder and the Xception model. The autoencoder was initially trained on thousands of unlabeled images, and the encoder then separated and used as a feature extractor. The Xception model was also used as a second model to extract features from the input images. The extracted feature vectors were then concatenated and fed into a Convolutional Neural Network for classification. This combination of models provides a powerful and versatile solution for image classification. By using the encoder as a feature extractor that can transfer the learned knowledge, it is possible to improve learning by allowing the model to focus on more relevant and useful data, which is extremely valuable when there are not enough appropriately labelled data. On the other hand, the Xception model provides additional feature extraction capabilities. Sometimes, one classifier is not enough in machine learning, as it depends on the problem we are trying to solve and the quality and quantity of data available. With ensemble learning, multiple learning networks can work together to create a stronger classifier. The final classification results are obtained by combining the information from both models through the CNN model. This approach demonstrates the potential for combining multiple models to improve the accuracy of image classification tasks in the medical domain. The HyperKvasir dataset is the main dataset used in this study. It contains 4,104 labelled and 99,417 unlabeled images taken at six different locations in the GI tract, including the cecum, ileum, pylorus, rectum, stomach, and Z line. After dataset preprocessing, which includes noise deduction and similarity removal, 871 labelled images remained for the purpose of this study. Our method was more accurate than state-of-the-art studies and had a higher F1 score while categorizing the input images into six different anatomical locations with less than a thousand labelled images. According to the results, feature extraction and ensemble learning increase accuracy by 5%, and a comparison with existing methods using the same dataset indicate improved performance and reduced cross entropy loss. The proposed method can therefore be used in the classification of endoscopy images
EVALUATING THE NITROUS OXIDE MITIGATION POTENTIAL OF ENHANCED EFFICIENCY NITROGEN FERTILIZER PRODUCTS IN A SASKATCHEWAN IRRIGATED CEREAL PRODUCTION SYSTEM
Get PDFNitrogen fertilizers added to agricultural field crops are a significant source of nitrous oxide (N2O) emissions from Canadian soils. Irrigated cropping systems are of particular concern due to intensive management and higher fertilizer rates corresponding to higher yield potential, which result in higher N2O emissions. Fall fertilizer applications are also at risk of greater N2O-N loss due to the length of time between application and crop uptake in the subsequent growing season. Enhanced efficiency nitrogen fertilizers (EENFs) can be used to mitigate environmental losses that contribute to greenhouse gas (GHG) emissions by slowing the release rate of N. Nitrous oxide emissions experience spatial and temporal variability and are highly dependent on management practice, thus, it is important to evaluate mitigation techniques across different geographies and cropping systems.
Over the course of two growing seasons and the subsequent spring thaw periods, fall and spring applications of conventional fertilizers (CF) and EENFs were evaluated in spring wheat under irrigation in south-central Saskatchewan. Nutrient supply rate of nitrate (NO3-) and ammonium (NH4+) were measured using PRS® probes and N2O emissions were collected from non-steady state vented chambers that were placed both on and off the fertilizer bands. Treatments included an unfertilized check, two conventional N sources (urea and anhydrous ammonia), a polymer-coated urea (ESN), two nitrification inhibitors (eNtrench, N-Serve), a dual−action urease inhibitor (Limus), and a dual (nitrification + urease) inhibitor (SuperU).
In this study, the supply rate of NO3- and NH4+ from EENFs was consistent with the mode of action of the product. Polymer-coated urea and products containing a urease inhibitor (UI) reduced the supply rate of NH4+ compared to CFs and products containing a nitrification inhibitor (NI) reduced the supply rate of NO3-. Interestingly, increased supply rates of bioavailable N were observed in all treatments over the winter when the soil was frozen. Unsurprisingly, the greatest N2O emissions fluxes corresponded with the spring melt periods and the period shortly following spring fertilization. Up to 75% of the annual, cumulative N2O flux occurred during the spring thaw. Enhanced efficiency nitrogen fertilizer N2O emission reductions were inconsistent when applied in the fall, whereas, spring applications of EENFs were much more consistent at reducing N2O emissions. Fall-applied SuperU (U/NI) and eNtrench (NI) reduced N2O emissions compared to untreated urea but only in the second field season. Spring-applied SuperU (U/NI), eNtrench (NI) and Limus (DAUI) consistently and significantly reduced N2O emissions across both field seasons (78-99%). The PCU (ESN) and AA-based NI (N-Serve) successfully reduced N2O emissions (43% and 68%, respectively) in the second field season only. Although environmental benefits are clear, specifically from using EENFs in a spring application of N, an agronomic benefit of increased yield was not observed in any of the N source treatments or application timings