cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Additional file 1 of Effective contribution ratio of the molar during sequential distalization using clear aligners and micro-implant anchorage: a finite element study
Creators: name: Liu, Xulin
name: Wu, Junjie
name: Cheng, Yuxun
name: Gao, Jie
name: Wen, Yi
name: Zhang, Yubohan
name: Luo, Houzhuo
name: Jin, Zuolin
name: Ma, Yanning
Publisher: name: figshare
Year: 2023
Subjects: subject: Biophysics
subject: Biochemistry
subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Biotechnology

description: Additional file 1. Three-dimensional displacement values for the posterior teeth (mm).
Supplemental Material, Online_Table_Z - Policy or person? The electoral value of policy positions and personal attributes in the Finnish open-list system
Creators: name: Schoultz, Åsa von
name: Papageorgiou, Achillefs
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 160607 International Relations
subject: FOS: Political science

description: Supplemental Material, Online_Table_Z for Policy or person? The electoral value of policy positions and personal attributes in the Finnish open-list system by Åsa von Schoultz and Achillefs Papageorgiou in Party Politics
Class Conditional Filter Pruning Based on Clustering of The Ranks of Feature Maps
Creators: Razavi, Soroush
Publisher: name: University of Alberta Library
Year: 2024

The success of deep learning is partly due to the sheer size of modern models. However, such large models strain the capabilities of mobile or resourceconstrained devices. Ergo, reducing the resource demands of AI models is essential before AI can be deployed on such devices. One promising solution to this challenge is filter pruning, which aims to streamline models without sacrificing performance. We propose a new approach to filter pruning that extends feature-map ranking to consider the class-by-class rank of each map. These feature vectors are clustered, and automated decision rules select the filters to be pruned. This makes our work one of the few pruning methods that is fully automated and does not require any human labor from end to end. Experiments using VGG and ResNet networks on the CIFAR-10 and ImageNet datasets show that our pruned models are more accurate than the well-known HRank algorithm and perform similarly on the CIFAR-100 dataset. In addition, we see significant reductions in power usage of models post-pruning. Finally, ethical pruning requires that an algorithm does not favor some group of data over others. We have verified that our algorithm follows the ethical pruning approach.
Supplementary document for Rapid identification of pathogens in blood serum via Raman tweezers in combination with advanced processing methods - 6585316.pdf
Creators: name: Vaculik, Ondrej
name: Bernatova, Silvie
name: Rebrosova, Katarína
name: Samek, Ota
name: Silhan, Lukas
name: Ruzicka, Filip
name: Sery, Mojmir
name: Siler, Martin
name: Jezek, Jan
name: Zemanek, Pavel
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplement 1
Additional file 3 of Bacteroides-derived isovaleric acid enhances mucosal immunity by facilitating intestinal IgA response in broilers
Creators: name: Wang, Xinkai
name: Hu, Yifan
name: Zhu, Xiaoyan
name: Cai, Liyuan
name: Farooq, Muhammad Zahid
name: Yan, Xianghua
Publisher: name: figshare
Year: 2024
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Immunology
subject: FOS: Clinical medicine

description: Additional file 3: Table S3. RT-qPCR primers in this study
How Data Sound: Sonification in Artistic Context
Creators: Ghayem, Nina
Publisher: name: University of Alberta Library
Year: 2024

This thesis investigates the use of sonification—transforming data into auditory representations—as an innovative approach to data interpretation within the Digital Humanities. As data continues to grow in complexity and volume, traditional methods of visualization are often insufficient to fully grasp the underlying patterns and insights. Sonification presents a promising alternative by providing an auditory dimension that not only complements visual analysis but also offers new avenues for understanding and engagement. This research-creation project focuses on sonification art, an arts practice that translates data from observations of real-world phenomena into musical parameters using mapping methods, with sound as a key medium for expression. By developing a comprehensive framework for sonification in artistic contexts, this thesis aims to bridge the gap between art, science, and technology. The project employs parameter mapping and algorithm development to translate various data dimensions into sound, creating a portfolio of sonified artworks that demonstrates the capability of auditory representations to uncover hidden patterns in a dataset and enrich data analysis. Through this interdisciplinary approach, this thesis contributes to the field of Digital Humanities by advancing the understanding of data representation and expanding the possibilities of artistic expression. By combining auditory and visual data representations, the project seeks to inspire new forms of creative exploration and dialogue, pushing the boundaries of how data can be perceived and utilized. The outcomes highlight the transformative potential of sonification in enhancing both the interpretative and aesthetic dimensions of data, emphasizing its role in fostering innovation and collaboration across diverse domains.
Quantifying Flood Depth: Remote Estimation of Flood Depths with Fast Response Tools
Creators: Escobar Mou, Roberto Javier
Publisher: name: University of Alberta Library
Year: 2024

Flood depth modelling has seen significant improvements in recent years. Historically, it relied heavily on large datasets, which were difficult to gather and handle. Simple, fast response methods, such as RICorDE and FwDET, are potentially suitable for assessments of flood scenarios where detailed hydraulic data might not be available or necessary. In this study, the performance of flood depth estimation algorithms RICorDE v1.0.1 and FwDET v2.1 was assessed for the 2020 Fort McMurray ice jam flood event. To assess their performance, the models were calibrated using a hand drawn case study event flood extent, and the resulting depth outputs from the fast response models were compared against a calibrated HEC-RAS model from Alberta Environment and Protected Areas (EPA) as well as high water mark (HWM) depths collected for the case study event, also from EPA. In the comparative assessment, the fast response RICorDE model achieved an R² value of 0.69 when compared to the calibrated HEC-RAS model, while FwDET achieved a value of 0.86. In relation to the surveyed HWM-derived depths, the fast response tools established point connections with fewer data points than the calibrated HEC-RAS model. In the surveyed depths assessment, RICorDE exhibited a Root Mean Square Error (RMSE) value of 0.58 meters, and FwDET had an RMSE of 0.20 meters. The calibrated HEC-RAS model, to which both fast response models were compared, presented a high point connection with an RMSE difference of 0.41 meters. Additionally, we assessed the Height Above Nearest Drainage (HAND) maps integrated into the fast response model RICorDE as a basis for flood depth estimations. HAND maps represent the elevation of a point on the landscape relative to the nearest stream or drainage network. In their assessment, the discrepancies in elevation points when creating HAND maps using either a stream or drainage network as reference points was evaluated. Specifically, the study investigated the impact of generating HAND maps based on these features on the accuracy of estimating flood extent. The findings indicate that defining drainage as a continuous streamline using flow accumulation algorithms yielded a more precise depiction of flood extent, in contrast to maps where drainage is delineated along the boundary between water and land. In conclusion, the study demonstrated that fast response flood models can generate flood depth estimations with high correlation to observations and physical models, especially in areas with flat topography and high-quality DEM data. These estimations are highly dependent on accurate delineation of flood extent, which can also be obtained from minimal data using HAND models.
Additional file 1 of A mobilization poster stimulates early in-hospital rehabilitation after cardiac surgery: a prospective sequential-group study
Creators: name: Halfwerk, Frank R.
name: Wielens, Nicole
name: Hulskotte, Stephanie
name: Brusse-Keizer, Marjolein
name: Grandjean, Jan G.
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Science Policy
subject: Mental Health

description: Additional file 1. Supplementary tables and figures.
AUT836380_Supplemental_Table__1 – Supplemental material for Familial confounding on the ability to read minds: A co-twin control study
Creators: name: Isaksson, Johan
name: Taylor, Mark J
name: Lundin, Karl
name: Neufeld, Janina
name: Bölte, Sven
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)
subject: FOS: Clinical medicine
subject: 111799 Public Health and Health Services not elsewhere classified
subject: FOS: Health sciences
subject: Education
subject: 130312 Special Education and Disability
subject: FOS: Educational sciences

description: Supplemental material, AUT836380_Supplemental_Table__1 for Familial confounding on the ability to read minds: A co-twin control study by Johan Isaksson, Mark J Taylor, Karl Lundin, Janina Neufeld and Sven Bölte in Autism
Supplementary document for Spatial multiplexing for robust optical vortex transmission with optical nonlinearity - 6585641.pdf
Creators: name: Fan, Weiru
name: Chen, Tianrun
name: Tang, Xiaobin
name: Xu, Xingqi
name: Yuan, Luqi
name: Yakovlev, Vladislav
name: Zhu, Shi-Yao
name: Wang, Da-Wei
name: Zhang, Delong
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplemental Material
Additional file 1 of Role of GRPR in Acupuncture Intervention in the “Itch-scratch Vicious Cycle” Spinal Circuit of Chronic Pruritus
Creators: name: Liu, Jia-jia
name: Li, Xuemei
name: Guo, Jing
name: Yu, Shuguang
name: Yang, Sha
Publisher: name: figshare
Year: 2024
Subjects: subject: Biophysics
subject: Cell Biology
subject: Physiology
subject: FOS: Biological sciences
subject: Biological Sciences not elsewhere classified
subject: Science Policy

description: Additional file 1. Search strategy.
Supplementary_material_RELIEVE_revised_20181219_xyz13441d6886433 - Conformity in Prescription and Administration of Respiratory Distress Protocols in a Tertiary Care Hospital in the Province of Quebec: RELIEVE Study
Creators: name: Dufort-Rouleau, Camille
name: Martin, Benjamin
name: Barré, Vincent
name: Bédard, Véronique
name: Émilie Dufort Rouleau
name: Marie-France Beauchesne
name: Quenneville, Julie
name: Berteau, Mathieu
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 111702 Aged Health Care
subject: FOS: Health sciences

description: Supplementary_material_RELIEVE_revised_20181219_xyz13441d6886433 for Conformity in Prescription and Administration of Respiratory Distress Protocols in a Tertiary Care Hospital in the Province of Quebec: RELIEVE Study by Camille Dufort-Rouleau, Benjamin Martin, Vincent Barré, Véronique Bédard, Émilie Dufort Rouleau, Marie-France Beauchesne, Julie Quenneville, and Mathieu Berteau in Journal of Palliative Care
Hypothermic and Subnormothermic Ex-situ Heart Perfusion: Examining Diverse Strategies  and Their Effects on Heart Function Preservation
Creators: Mainardi Aguiar da Silva, Guilherme
Publisher: name: University of Alberta Library
Year: 2024

The number of people suffering from heart failure grows annually. For those people who have advanced heart failure and are eligible for a heart transplant, this is the gold standard procedure to treat them. Allowing not only an improvement in quality of life but also an increase in survival.

However, the number of heart transplants performed per year in Canada and around the world is smaller than the number of people on the waiting list for a donated organ. In addition, one of the determining factors for this deficit between donated organs and transplants performed is the current method of organ preservation.

Ex-situ heart perfusion (ESHP) has proven to be a more effective method than the current one, static cold storage (SCS). However, there are different types of ESHP, being the hypothermic and subnormothermic the least complex in relation to normothermic for several reasons that will be addressed in this thesis.

The creation of protocols to make ESHP uniform are essential for the dissemination of this method of organ preservation. Since this method can extend the preservation time prior to transplantation, it can improve preservation and hence increase the number of organs available for transplantation.

The first study presented evaluated the ideal temperature to be applied during hypothermic ESHP using UW machine perfusion solution (UWMPS). It was seen that the lowest temperature studied was the one that obtained better heart function preservation after 12 hours of perfusion. The results were compared to the current preservation method.

The second study sought to optimize UWMPS with the aim of enhancing heart function preservation. Two modifications were applied in the perfusate studied, the addition of amino acids and the addition of some ions (as these components are presented in Somah). The results obtained in this study were compared with UWMPS as a control.

The results presented in these two studies can be used to guide new studies and build new protocols for ESHP. This strengthens the use of ESHP as a gold standard method and increases the number of heart transplants performed.
PPIs_in_SA_Bacteremia_Strobe – Supplemental material for Proton-pump inhibitors do not influence clinical outcomes in patients with Staphylococcus aureus bacteremia
Creators: name: Caffrey, Aisling R.
name: Timbrook, Tristan T.
name: Ali, Syed Raza
name: Nizet, Victor
name: Sakoulas, George
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 111199 Nutrition and Dietetics not elsewhere classified
subject: FOS: Health sciences
subject: 111299 Oncology and Carcinogenesis not elsewhere classified
subject: FOS: Clinical medicine
subject: 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified

description: Supplemental material, PPIs_in_SA_Bacteremia_Strobe for Proton-pump inhibitors do not influence clinical outcomes in patients with Staphylococcus aureus bacteremia by Aisling R. Caffrey, Tristan T. Timbrook, Syed Raza Ali, Victor Nizet and George Sakoulas in Therapeutic Advances in Gastroenterology
Real-time Quality Control for Offsite LGS Frame Manufacturing using Vision-based Deep Learning
Creators: Nader, George
Publisher: name: University of Alberta Library
Year: 2024

Efficiency and accuracy are crucial in offsite panelized construction, including in the production of light-gauge steel frames. Maintaining consistent screw fastening is an ongoing challenge in the construction industry, and defective screw fastening can lead to quality problems in panelized construction projects. To address this issue, this research introduces a light-gauge steel framing machine that integrates a computer-vision system for precise quality control. This framework is developed and tested on real panelized construction projects. This innovative approach equips the light-gauge steel framing machine with visual perception capabilities, enabling real-time image capture and analysis of the framing process. By employing advanced imaging technology and YOLOv8n machine learning architecture, the computer-vision system provides immediate feedback to the machine’s control system. This process facilitates precise decision-making regarding screw- fastening operations. The implementation of YOLOv8n on the light-gauge steel framing machine uses Python and the OpenCV library to process visual data in real -time, determining optimal methods to mitigate defects. The experimental results demonstrate that the computer-vision system substantially improves the integrity and precision of light-gauge steel frames. The results indicate a reduction in defects and rework, as well as significant enhancements to operational efficiency and material utilization. These enhancements underscore the promising potential of integrating real-time computer vision and artificial intelligence with the manufacturing processes of panelized construction, establishing a foundation for future innovations in autonomous systems within this industrial sector.
Proteins of the heart: understanding proteome and degradome changes in cardiac ischemia-reperfusion injury and hypertrophy using mass spectrometry
Creators: Hartley, Bridgette
Publisher: name: University of Alberta Library
Year: 2024

Cardiovascular diseases represent one of the primary causes of death worldwide. Numerous forms of heart disease result in changes in the proteome and degradome of the heart. Mass spectrometry is a robust approach to investigate these changes. My main objective is to assess the proteome and degradome changes in two cardiovascular pathologies common in cardiovascular diseases: cardiac ischemia-reperfusion (IR) injury and pressure-overload hypertrophy. To do this, I have employed label-free proteome quantification and subtiligase-mediated N-terminomic. In Chapter 2, we investigate the proteome changes in isolated rat hearts following IR injury using data-independent acquisition (DIA) mass spectrometry. We then investigate the degradome changes using subtiligase-mediated N-terminomic labelling. In Chapter 3, a deeper dive into the substrate cleavage sites by matrix metalloproteinase-2 (MMP-2) is investigated. We designed a novel, constitutively active MMP-2-Fc fusion protein that we expressed and purified from mammalian cells. Using this protease, we proteolyzed ventricular extracts from the isolated hearts and used subtiligase-mediated N-terminomic labelling to identify cleavage sites. In Chapter 4, we adapted many of these methods to investigate the molecular mechanisms of pressure overload cardiomyopathy and the role of disintegrin and metalloproteinases 15 (ADAM15). We also assessed the proteome changes in the hearts of wildtype and ADAM15 knockout mice. Furthermore, we investigated the degradome changes using subtiligase-based N-terminomic labelling. These findings uncover new information on the pathology of myocardial IR injury and pressure overload cardiomyopathy. In both approaches, we have uncovered the protein abundance of thousands of proteins and identified potential novel proteolytic targets. Understanding the intracellular mechanisms of myocardial injury is crucial for translational medicine, as knowledge gaps prevent preclinical data from being translated into clinical practice. This research is a valuable foundation for future investigations into implicated proteases, inhibitor design, and other therapeutic strategies.
UNDERSTANDING ECOCULTURE: PROMOTING SUSTAINABLE PRACTICES FOR ENVIRONMENTAL AND HUMAN WELL-BEING
Creators: name: Oteniyazova, Gulzada
Publisher: name: Zenodo
Year: 2024

description: Ecoculture, often referred to as ecological agriculture or sustainable farming, represents a crucial approach in modern agricultural practices. It integrates ecological principles with cultural and economic considerations to enhance sustainability and promote environmental health. This article explores the fundamentals of ecoculture, its importance in preserving biodiversity, improving soil health, and ensuring food security amidst global environmental challenges.
Are Large Language Models Good Essay Graders?
Creators: Kundu, Anindita
Publisher: name: University of Alberta Library
Year: 2024

We evaluate the effectiveness of Large Language Models (LLMs) in assessing essay quality, focusing on their alignment with human grading processes.  Specifically, we investigate the applicability of LLMs such as GPT-3.5T and Llama-2 in the Automated Essay Scoring (AES) task, a crucial natural language processing (NLP) application in education.  Our study explores both zero-shot and few-shot learning approaches, employing various prompting techniques to enhance performance.

Utilizing the ASAP dataset, a well-known dataset for the AES task, we compare the numeric grade provided by the LLMs to human rater-provided scores.  Our research reveals that both approaches GPT-3.5T and Llama-2 generally assign lower scores compared to those provided by the human raters. Furthermore, neither LLM correlates well with the human scores. In particular, GPT-3.5T tends to be harsher and further misaligned with human evaluations compared to Llama-2. On the other hand, both LLMs not only can reliably detect spelling and grammar mistakes but also seem to take those mistakes into account when computing their score. Additionally, we extended our analysis to include the most recent release, Llama-3, which shows promising improvements in alignment with human scores. This suggests that newer generations of LLMs have the potential to be more effective in AES tasks. Overall, our results offer a cautiously optimistic view of using LLMs as tools to assist in the grading of written essays, highlighting both their current limitations and their future potential.
ONLAYN MULOQOTNING VUJUDGA KELISHI
Creators: name: To'lanboyeva, Gulsanam
name: Roziqova, Gulbahor
Publisher: name: Zenodo
Year: 2024

description: Muloqot insoniyat hayotidagi eng muhim faoliyat turlaridan biri bo‘lib, qolgan barcha faoliyat turlari muloqot bilan bevosita bog‘liq. Dastlabki muloqot qay tarzda shakllangan va bugungi kundagi eng ko‘p murojaat etilayotgan onlayn muloqot qanday vujudga kelgan. Onlayn muloqotning shakllanishi, uning afzalliklari va kamchiliklari, hamda tilshunoslikdagi nechog‘lik ahamiyatli ekani haqida ushbu maqolada so‘z yurtiladi.
Refining the geochronology and paleoenvironmental significance of key tephra beds in Yukon and Alaska
Creators: Buryak, Serhiy D.
Publisher: name: University of Alberta Library
Year: 2024

Developing precise analytical tools for dating young volcanic deposits (under 3 million years old) is essential for constructing Quaternary chronological frameworks. This dissertation presents an improved method for determining eruption ages of volcanic ash (tephra) deposits in the ice-age sediments of unglaciated Yukon and Alaska (eastern Beringia). These regions, largely unglaciated during the Quaternary Period (last 2.6 million years), preserve a unique sedimentary record crucial for reconstructing past climate and environmental changes. Abundant tephra beds in these sediments are key to dating past climate changes, evaluating megafauna extirpation hypotheses, and understanding climate-landscape linkages.

However, radiometric dating of these relatively young tephra deposits is difficult. Some tephra can be directly dated with glass fission-track techniques, but relatively low precision of this technique has hindered progress in deciphering the sedimentary record of eastern Beringia. In the last decade, major improvements in instrumentation and other methodological advances are offering new opportunities to revisit this outstanding problem. Here a combination of U-Pb and/or U-series zircon dating via laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is used to resolve eruption age uncertainty for important Quaternary tephra deposits. U-Pb zircon dating is commonly used to date much older geological materials, but there is a pressing need to adapt these techniques for application to more recent periods of time that are directly relevant to issues of global environmental change.

The enhanced tephrochronological framework, combined with paleoenvironmental and paleobiological data, offers a better understanding of eastern Beringian sediment deposition over the last 3 million years. This research presents zircon ages for 14 key tephra layers providing critical temporal anchors for Marine Isotope Stages 5 to 8 and older sediments in eastern Beringia. This includes improved dates for Old Crow, Sheep Creek - Fairbanks, HP, Gold Run, PA, Quartz Creek, Lost Chicken, GI tephra, and new chronology for Woodchopper Creek, Snag, Biederman PAL, and 80 Pup tephra. The dissertation also addresses statistical challenges in evaluating complex zircon populations and proposes refined age calculation methods. Additionally, it examines the preservation of volcanogenic zircon grains in sediment, highlighting the relationship between age, grain morphology, and recovery methods, thus improving the identification of syn-depositional grains in detrital sediments. This research revises the chronology of volcanism in Alaska and Yukon and refines methods for dating young volcanic deposits.
Supplemental material for Dectin-1 and Dectin-2 promote control of the fungal pathogen Trichophyton rubrum independently of IL-17 and adaptive immunity in experimental deep dermatophytosis
Creators: name: Yoshikawa, Fabio SY
name: Yabe, Rikio
name: Iwakura, Yoichiro
name: Almeida, Sandro R De
name: Saijo, Shinobu
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 110306 Endocrinology
subject: FOS: Clinical medicine

description: Supplemental Material for Dectin-1 and Dectin-2 promote control of the fungal pathogen Trichophyton rubrum independently of IL-17 and adaptive immunity in experimental deep dermatophytosis by Fabio SY Yoshikawa, Rikio Yabe, Yoichiro Iwakura, Sandro R de Almeida and Shinobu Saijo in Innate Immunity
Appendix_A – Supplemental material for Nonfatal Assault Injury Trends in California, 2005 to 2015
Creators: name: Rowe, Christopher L.
name: Ellicott C. Matthay
name: Ahern, Jennifer
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 160299 Criminology not elsewhere classified
subject: FOS: Law

description: Supplemental material, Appendix_A for Nonfatal Assault Injury Trends in California, 2005 to 2015 by Christopher L. Rowe, Ellicott C. Matthay and Jennifer Ahern in Journal of Interpersonal Violence
Explorations in the Foundations of Value-based Reinforcement Learning
Creators: De Asis, Kris
Publisher: name: University of Alberta Library
Year: 2024

Value-based reinforcement learning is an approach to sequential decision making in which decisions are informed by learned, long-horizon predictions of future reward. This dissertation aims to understand issues that value-based methods face and develop algorithmic ideas to address these issues. It details three areas of contribution toward improving value-based methods. The first area of contribution extends temporal difference methods for fixed-horizon predictions. Regardless of problem setting, using fixed-horizon approximations of the return avoids the well-documented stability issues which plague off-policy temporal difference methods with function approximation. The second area of contribution introduces a framework of value-aware importance weights for off-policy learning and derives a minimum-variance instance of them. This alleviates variance concerns of importance sampling-based off-policy corrections. Lastly, the third area of contribution acknowledges a discrepancy between the discrete-time and continuous-time returns when viewing one as an approximation of the other, and proposes a modification to better align the objectives. This provides improved prediction targets, and when faced with variable time-discretization, improves control performance in terms of an underlying integral return.
MSJ838205_supplementary_figures – Supplemental material for Impairment of odor discrimination and identification is associated with disability progression and gray matter atrophy of the olfactory system in MS
Creators: name: Bsteh, Gabriel
name: Steiger, Ruth
name: Tuovinen, Noora
name: Hegen, Harald
name: Berek, Klaus
name: Wurth, Sebastian
name: Auer, Michael
name: Pauli, Franziska Di
name: Gizewski, Elke R
name: Deisenhammer, Florian
name: Berger, Thomas
name: Scherfler, Christoph
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: 111702 Aged Health Care
subject: FOS: Health sciences

description: Supplemental material, MSJ838205_supplementary_figures for Impairment of odor discrimination and identification is associated with disability progression and gray matter atrophy of the olfactory system in MS by Gabriel Bsteh, Ruth Steiger, Noora Tuovinen, Harald Hegen, Klaus Berek, Sebastian Wurth, Michael Auer, Franziska Di Pauli, Elke R Gizewski, Florian Deisenhammer, Thomas Berger and Christoph Scherfler in Multiple Sclerosis Journal
A Generative Transformer-Based Approach to Automated Essay Scoring: Evaluating GPT-2’s Performance with Pre- and Post- Data Augmentation
Creators: Gunduz, Aysegul
Publisher: name: University of Alberta Library
Year: 2024

Recent advancements in artificial intelligence and language modeling have revolutionized the domain of educational technology, with a special focus on the utility of automated essay scoring (AES) systems. The potential of GPT-based model architectures, including different versions or iterations of the ChatGPT tool, has become an important research topic. My research is designed to investigate the performance of the GPT-2 small model in AES and examine how the back translation technique between English and Turkish can improve its performance on the Hewlett-sponsored ASAP dataset (https://www.kaggle.com/c/asap-aes).  The evaluation is based on both Cohen's kappa and Quadratic Weighted Kappa (QWK) for agreement reliability, with additional metrics such as accuracy, precision, sensitivity, and the F-1 score providing further insight into the classification accuracy. Findings indicate a QWK range of 0.60 to 0.80 across most ASAP essay sets, with Essay Set 5 reaching a peak QWK of 0.77.  Back Translation techniques showed a significant increase in the model's performance, especially in Essay Set 8, where there was a QWK score increase of 33%. The study highlights the limited capacity of GPT-2 small model and emphasizes the importance of conducting future research with more advanced GPT versions. It also underscores the importance of balanced class distributions to achieve high QWK scores, where the use of balanced essay sets is recommended for future research to enhance AES performance.

Key words: artificial intelligence, language modeling, automated essay scoring (AES), GPT-based models, ChatGPT, GPT-2, data augmentation, back translation, ASAP
Figure_S5_xyz15370cb890805 – Supplemental material for A Pathway-Based Strategy to Identify Biomarkers for Lung Cancer Diagnosis and Prognosis
Creators: name: Sheng, Mengying
name: Xie, Xueying
name: Wang, Jun
name: Gu, Wanjun
Publisher: name: SAGE Journals
Year: 2019
Subjects: Cell Biology

description: Supplemental material, Figure_S5_xyz15370cb890805 for A Pathway-Based Strategy to Identify Biomarkers for Lung Cancer Diagnosis and Prognosis by Mengying Sheng, Xueying Xie, Jun Wang and Wanjun Gu in Evolutionary Bioinformatics
Supplementary_tables – Supplemental material for Association of Life’s Simple 7 with reduced clinically manifest abdominal aortic aneurysm: The ARIC study
Creators: name: Abayomi O Oyenuga
name: Folsom, Aaron R
name: Lutsey, Pamela L
name: Weihong Tang
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: Cardiology
subject: 110323 Surgery
subject: FOS: Clinical medicine

description: Supplemental material, Supplementary_tables for Association of Life’s Simple 7 with reduced clinically manifest abdominal aortic aneurysm: The ARIC study by Abayomi O Oyenuga, Aaron R Folsom, Pamela L Lutsey and Weihong Tang in Vascular Medicine
Integrating Conversational Pathways with a Chatbot Builder Platform
Creators: Prakash, Varshini
Publisher: name: University of Alberta Library
Year: 2024

MIRA, a Mental Health Virtual Assistant, was developed during the COVID-19 pandemic to address rising mental health concerns and the demand for support and services. As a task-oriented chatbot, MIRA connected healthcare workers seeking mental health support with trusted services and programs. It achieved this by integrating Natural Language Processing (NLP) within a structured conversation flow, designed by experts in our multidisciplinary team to cater to healthcare workers. This work extends MIRA across diverse populations to improve accessibility to mental health services. The pilot version of MIRA was implemented in Python using an open-source chatbot development framework. Its conversational logic was hard-coded, and minor changes to the conversation flow necessitated extensive changes to the code base. Such a rigid system made it challenging to extend the functionalities of MIRA to cater to other languages or new populations, such as first responders, Veterans, Indigenous communities, or youth. In addition, building relevant and effective solutions that cater to community-specific needs requires insights from subject matter experts and close collaboration with a multidisciplinary team, including psychiatrists, domain experts and people with lived experience. Scaling MIRA’s functionalities to serve diverse populations requires being able to easily integrate additional conversational pathways without changes at the code level. Hence, we introduce a chatbot builder platform and a conversation flow visualizer to simplify the creation and modification of conversational flows by non-technical experts. Our tools support multidisciplinary collaboration on MIRA’s development process by enabling iterative improvements and rapid modifications to the conversation flow. Our work has been successfully deployed and is available for public use.
Preventable errors in the performance and reporting of echocardiography and right heart catheterization can lead to diagnosis errors for pulmonary hypertension with significant implications for patients
Creators: Saunders, Alexandra
Publisher: name: University of Alberta Library
Year: 2024

Pulmonary hypertension (PH) is common and PH subgroups have vastly different mortality and treatment, particularly pulmonary arterial hypertension (PAH) versus PH secondary to heart failure with preserved ejection fraction (HFpEF). Both transthoracic echocardiography (TTE) and right heart catheterization (RHC) are needed, as diagnosis requires mean pulmonary artery pressure (mPAP) >20 mmHg either with pulmonary artery wedge pressure (PAWP) 15 mmHg for HFpEF. PAWP and mPAP can only be measured by RHC. However, TTE is what first identifies PH, triggering referral to a specialized PH center. We hypothesized that human errors in the performance and reporting of TTEs and RHC are prevalent, potentially leading to misdiagnosis of PH and its subgroups.

We re-analyzed TTEs and RHCs of 263 consecutive new patients referred to our PH program during a 5-year period. We also compared the inferred diagnosis from the referring TTE and the subsequent RHC reports to the diagnosis made after correcting for errors found. We identified numerous preventable errors in the performance and reporting of both tests. There was a poor correlation between the parameters measured by both tests (e.g., systolic PAP). The referral TTE reports missed or overcalled PH in 44 patients. The RHC, mostly by mistakes of the PAWP, led to misdiagnosis in 41 patients, (21 with true PAH labelled as HFpEF and 20 with true HFpEF labelled as PAH).

TTE errors may delay referrals and RHC errors may lead to misdiagnosis and applying wrong therapies to the wrong groups. As PAH therapies are extremely expensive, this also impacts the health care system. Primary care physicians need to be on alert for such errors and referral centers need to promote quality improvement programs that could eliminate these errors.
The Relationship Between Parenting Stress and Children’s Emotion Regulation and Social Skills in Early Childhood
Creators: Zukiwsky, Rachel D
Publisher: name: University of Alberta Library
Year: 2024

Well-developed social and emotional skills gained in early childhood are integral for independent functioning as children enter into school, especially emotion regulation abilities and social skills. Learned through parent-child interactions, researchers have identified parenting stress (i.e., the stress experienced regarding the parenting role) as a factor negatively associated with the development of emotion regulation abilities and social skills. However, the predictive relationship between parenting stress and the development of emotion regulation abilities and social skills, specifically in early childhood, is not well understood. Additionally, previous research in this area has focused mainly on mothers’ reports of their parenting stress and their children’s social and emotional functioning, disregarding fathers’ parenting stress and cross-contextual implications of parenting stress on children’s social and emotional functioning in the school setting. Through a quantitative correlational design, this study examined whether mother- and father-reported parenting stress when their child was in preschool would each predicted children’s emotion regulation abilities and social skills as rated by teachers in Grade 1. Despite significant negative correlations between parenting stress and children’s emotion regulation abilities and social skills, multiple regression analyses showed that high levels of father-reported parenting stress significantly predicted children’s poorer social skills in Grade 1. There were no significant predictive relationships between mother-reported parenting stress and emotion regulation abilities and social skills, nor between father-reported parenting stress and emotion regulation abilities. Limitations, implications, and future directions for research are discussed.
The Antinociceptive Effects of Cannabinoids and Terpenoids on a Zebrafish Model of Nociception
Creators: Kim, Andrew M
Publisher: name: University of Alberta Library
Year: 2024

With many communities affected by the opioid crisis, it has become of paramount importance to explore methods of pain management outside of treatments with opioids. One alternative treatment that has seen a recent surge in interest is cannabis and its related phytochemical-based treatments. Indeed, some cannabinoids and terpenoids have been demonstrated to show antinociceptive effects in various model systems. However, for the vast majority of terpenoids in cannabis, these effects remain unexplored. In this study I used a zebrafish model of nociception to test the antinociceptive effects of cannabinoids, terpenoids and a combination of the two compounds. Zebrafish provides a robust and high-throughput model system for such inquiry. Using behavioural assays, I confirmed the ability of acetic acid to elicit a change in locomotion in larval zebrafish. Exposure to low concentrations of acetic acid (0.001% - 0.01%) led to a four-fold increase in mean activity levels of 5-day old larvae. When zebrafish larvae were exposed to cannabidiol (CBD) at 2.5 mg/L and 5 mg/L and the terpenoids, trans-nerolidol and caryophyllene oxide at 10mg/L, the acetic acid-induced increase in activity was prevented. However, tetrahydrocannabinol (THC) and other terpenoids failed to prevent nociception from acetic acid. Combinations of the terpenoids with CBD did not lead to a greater antinociceptive effects compared with each individual compound. Using specific blockers, I determined that the process through which CBD, trans-nerolidol, and caryophyllene oxide display antinociceptive effects involves the transient receptor potential (TRP) cation channels, specifically TRPA1 and TRPV1 channels. On the other hand, intervention with specific blockers of µ-opioid receptor, δ-opioid receptor, and cannabinoid receptor types 1 and 2 was insufficient in preventing the acetic acid-induced activity. These findings lay the foundation for a more thorough investigation of the therapeutic effects of cannabinoids, terpenoids and combinations of the two, as well as a mechanistic understanding of how such effects arise at a cellular level.
Coaches’ Experience Using Canada Basketball’s Athlete Development Model
Creators: Leong, Douglas
Publisher: name: University of Alberta Library
Year: 2024

Sport coaches in Canada wield significant influence over physical activity levels, which are crucial for lifelong development across all stages of life. In Canada, the Long-Term Development in Sport and Physical Activity (LTDSPA) framework was developed to guide coaches; however, gaps persist in understanding its long-term effectiveness and application. The LTDSPA framework, aimed at promoting lifelong physical activity and achieving sporting excellence, has been adopted by 54 National Sport Organizations (NSOs) to meet Canada’s diverse sporting needs. Canadian coaches bear the responsibility of implementing the framework to shape and elevate all athletes. However, a review of the literature on the application and implementation of the LTDSPA in Canada revealed several gaps, including concerns about the framework’s long-term effectiveness, accessibility, and coaches’ resource needs.

    Canada Basketball developed its version of the framework for basketball known as the Athlete Development Model (ADM), which serves as the focal point of this study. This leads to the research question: What has been the experience of coaches in incorporating Canada Basketball’s Athlete Development Model into their coaching practice in the Province of Alberta?

    Interpretive inquiry informed by hermeneutics was employed in this study. A purposeful sample of six participants was interviewed using the “hermeneutic interview protocol” (Tine & Ellis, 2022) developed over a number of years in education graduate courses. Findings indicate that while the majority of coaches favor using the ADM, their adoption process varies due to diverse educational backgrounds, life experiences, and coaching contexts. Additionally, the ADM is not universally effective as a communication tool for all stakeholders. Coaches perceive the club system in Alberta as a barrier to province-wide acceptance of the ADM and call for more resources and urgency from Alberta Basketball to encourage its use.

    With no published literature on the implementation or application of Canada Basketball’s Athlete Development Model (ADM) from the perspective of basketball coaches or administrators, and only an unpublished doctoral thesis on the use of the ADM by basketball coaches across Canada, this study underscores the necessity for additional research in this area. Specifically, future research should investigate coaches’ learning sources and confidence levels in the ADM, evaluate coach education and implementation effectiveness of the ADM, understand barriers to and promotion of ADM adoption, explore the role of coaches in ADM promotion, and analyze ADM communication dynamics and strategies. These insights can inform future efforts to enhance coach education and support for the ADM, ultimately contributing to the development of athletes and promoting lifelong physical activity.
Experimental Studies and Multi-Scale Modelling of Advanced Ceramics: Fracture, Fragmentation, and Failure
Creators: Zheng, Jie
Publisher: name: University of Alberta Library
Year: 2024

The objectives of this thesis is to explores the mechanical behaviour of alumina ceramics, focusing on fracture and fragmentation response through a blend of experimental investigations and advanced computational modelling. To bridge the gap between micro-mechanisms and macroscopic material behaviors, the microstructure and mechanical properties of the CeramTec ALOTEC 98 SB (CeramTec 98\%) alumina ceramic are examined using microscopic characterization and mechanical testing under various strain-rate and stress-state loading conditions. The mechanical tests employs a modified split-Hopkinson pressure bar complemented by high-speed imaging and digital image correlation (DIC), to capture the fracture processes and stress fields. The testing results indicate that this ceramic exhibits superior mechanical properties to other commercial alumina ceramics, with strengths becoming stronger with higher strain rates. Further, a three-dimensional hybrid finite-discrete element model considering the flaw system of advanced ceramics is developed and validated against experimental data. These models successfully simulated crack initiation, propagation, and fragmentation processes, offering new perspectives on the failure process of alumina ceramics. Sensitivity analyses explore the influence of material properties, such as elastic modulus, fracture properties and flaws, on mechanical strength, including the tensile and compressive strength of advanced ceramics. By integrating experimental and computational approaches, this research advances the fundamental understanding of failure mechanisms of alumina ceramics. The findings provide valuable insights into the design and optimization of advanced ceramics, contributing to the development of next-generation advanced ceramic materials for defence and aerospace applications.
A Deep Learning Approach for Forecasting Construction Project Duration at Completion
Creators: Laura Portugal, Cristhian Felix
Publisher: name: University of Alberta Library
Year: 2024

Accurate forecasting of project duration is crucial during the execution phase as it affects its overall performance, timely decision-making, identification of potential delays, and resource allocation. This research proposes a proof of concept based on artificial intelligence, specifically using deep learning algorithms, demonstrating its potential application. These algorithms have shown remarkable results in finding patterns in large amounts of data and making accurate predictions. Moreover, the dataset provided to the model is treated as a time series, capturing the sequential nature of data collected throughout the execution phase. Additionally, predictions are yielded at work package level, providing to project managers granular information to make decisions.

The study follows these steps: (1) a comprehensive literature review was conducted to explore the latest advancements on related topics and underline current gaps. (2) A data acquisition model was elaborated founded on a consistent selection of duration-influencing factors. Then, actual data was collected and profiled from multiple projects using their work package names as links, thus creating datasets per work package. (3) The forecasting duration at completion model was developed, including data preprocessing and the computational deep-learning-based modelling per work package. After that, the overall project duration was modelled using the Critical Path Method and Precedence Diagramming Method and set in the Graphical User Interface. (4) The developed forecasting model was used to comparing three well-suited deep-learning algorithms with actual project data and consequently, selecting the most accurate. Next, the selected algorithm was incorporated into the Graphical User Interface. The study also was validated by comparing the proposed model with traditional methods, including the Earned Value Methodology (EVM) and Earned Schedule Methodology (ESM). Finally, the resultant model was verified through sensitivity analysis.

As a result, the forecasting model based on the Long Short-Term Memory (LSTM) algorithm demonstrated the best performance against Multi-Layer Perceptron and Convolutional Neural Network algorithms. Likewise, it performed better than intensive-used forecasting methods in the industry, such as Earned Value Methodology (EVM) and Earned Schedule Methodology (ESM). These promising results contributes to the foundation of Artificial Intelligence (AI) applicability in construction project duration at completion forecasting.
Searching In Light Curves
Creators: name: Vo Martin
Publisher: name: Zenodo
Year: 2017
Subjects: Data Mining, Big Data, Machine Learning, SAX, Light Curves

description: These slides were presented in COST BIG SKY EARTH WG meeting Bucharest, 3 July.
description: This research was supported by grant COST LD-15113 of the Ministry of
Education Youth and Sports of the Czech Republic.