cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Additional file 1 of The survival of Amblyomma sculptum ticks upon blood-feeding depends on the expression of an inhibitor of apoptosis protein
Creators: name: Nassar, Marcelly
name: Martins, Larissa A.
name: de Assis, Josiane Betim
name: Esteves, Eliane
name: Sá-Nunes, Anderson
name: Labruna, Marcelo B.
name: Daffre, Sirlei
name: Fogaça, Andrea C.
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Microbiology
subject: FOS: Biological sciences
subject: Cell Biology
subject: Molecular Biology
subject: Chemical Sciences not elsewhere classified
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: Developmental Biology
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology

description: Additional file 1: Table S1. Accession numbers of IAP sequences used to perform the multiple sequence alignment and generate a phylogenetic tree are displayed in Figure 2.
Cross-Lingual and Cross-Modal Limitations of Large Language Models
Creators: Li, Senyu
Publisher: name: University of Alberta Library
Year: 2024

Large Language Models (LLMs), including Vision Large Language Models (VLLMs), herald the coming of a new research epoch in machine learning and computational linguistics. Despite most LLMs being predominantly trained on English, their proficiency in various languages has been confirmed by many studies. Nonetheless, critical questions remain about their performance consistency across different languages. A similar concern is raised for VLLMs regarding their performance disparities across various modalities. Moreover, while the remarkable competence of LLMs in solving downstream tasks is widely acknowledged, they still fall short of satisfactory performance in several tasks, requiring further experimentation for deeper insights. In this thesis,  we investigate the phenomenon of cross-language generalization in LLMs by employing a novel prompt back-translation method. We investigate the interactions and comparisons between text and image modalities by introducing a new concept called cross-modal consistency and propose a quantitative evaluation framework based on this concept. Additionally, we evaluate the performance of an LLM on two specific linguistic tasks: Lexicalization Generation and Lexical Gap Detection. We have also developed a novel algorithmic approach for comparative analysis. The findings reveal that LLMs face challenges in providing accurate results for translation-variant tasks, reveal a significant inconsistency between vision and language modalities within GPT, and show that ChatGPT underperforms in the two evaluated downstream tasks, being significantly outperformed by our rule-based method.
Additional file 1 of Testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali (LAKANA): study protocol for a cluster-randomized, placebo-controlled, double-blinded, parallel-group, three-arm clinical trial
Creators: name: Adubra, Laura
name: Alber, Dagmar
name: Ashorn, Per
name: Ashorn, Ulla
name: Cheung, Yin Bun
name: Cloutman-Green, Elaine
name: Diallo, Fatoumata
name: Ducker, Camilla
name: Elovainio, Riku
name: Fan, Yue-Mei
name: Gates, Lily
name: Gruffudd, Gwydion
name: Haapaniemi, Tiia
name: Haidara, Fadima
name: Hallamaa, Lotta
name: Ihamuotila, Rikhard
name: Klein, Nigel
name: Luoma, Juho
name: Martell, Owen
name: Sow, Samba
name: Vehmasto, Taru
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Pharmacology
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 1. Informed consent materials.
Low Statin Persistence Over 36-months is a High-Risk Marker in Adults with Diabetes
Creators: Doma, Andrew
Publisher: name: University of Alberta Library
Year: 2024

Statin therapy prevents cardiovascular disease (CVD) in adults with diabetes. There is on-going inconsistency between clinical practice guidelines on whether specific LDL-C levels should be targeted in those on statin therapy. Additionally, real world persistence with statin therapy appears to have plateaued.

To examine the real-world effects of statin use and persistence, and LDL-C levels, on CVD risk, we performed a retrospective cohort study using Alberta administrative health data. We included adults with diabetes and no previous history of CVD, who were 50 years old on April 1, 2012, and followed them until March 31, 2019 for a primary composite outcome of MI, stroke, and revascularization. Statin persistence was defined as the number of 6-month periods in the preceding 3 years during which there were one or more statin dispensations with the first documented window of statin use between April 1, 2009 to September 30, 2009. LDL-C levels (categorized as  or > 2.0 mmol/L) were obtained from linked laboratory results. We conducted a time-varying Cox proportional hazards regression with adjustment for age, sex, income, intensity of diabetes therapy, and other comorbidities.

We included 72,541 individuals (mean age = 65.4 (SD 8.9), 47.6% female). The overall primary outcome rate was 10.4 per 1,000 person-years. Independent of statin use and other variables, LDL-C  2.0 mmol/L was strongly associated with reduced CVD (adjusted hazard ratio [HR] 0.64 [95% Confidence Interval (CI) 0.59–0.69], p  2.0 mmol/L and documented statin use in only 1-2 six-month periods in the preceding 3 years are at elevated CVD risk, and may benefit from recall for additional CVD risk reduction.
The economy is essentially for people to live happily(本来人々が幸せに暮らせるための経済)
Creators: name: Fumiyoshi, Tamura
Publisher: name: Zenodo
Year: 2025

description: When we question the fundamentals of why people live, it is time for us to reconsider that money is nothing more than a promise between people in a given region, and that it is the country's responsibility to fulfill that promise. So that we can live happily.

 

人が何のために生きているのか

その根本を問う時本来貨幣とはその地域での人々の約束事でしかなくその責任を果たすのが国であることを私たちは再度見直すべき時です

私たちが幸せに暮らすために
Honey Trap or Romantic Utopia: A Case Study of Final Fantasy XIV Players PII Disclosure in Intimate Partner-Seeking Posts
Creators: name: Zhou, Yihao
name: Sharma, Tanusree
Publisher: name: arXiv
Year: 2025
Subjects: subject: Computers and Society (cs.CY)
subject: Human-Computer Interaction (cs.HC)
subject: Multimedia (cs.MM)
subject: FOS: Computer and information sciences

description: Massively multiplayer online games (MMOGs) can foster social interaction and relationship formation, but they pose specific privacy and safety challenges, especially in the context of mediating intimate interpersonal connections. To explore the potential risks, we conducted a case study on Final Fantasy XIV (FFXIV) players intimate partner seeking posts on social media. We analyzed 1,288 posts from a public Weibo account using Latent Dirichlet Allocation (LDA) topic modeling and thematic analysis. Our findings reveal that players disclose sensitive personal information and share vulnerabilities to establish trust but face difficulties in managing identity and privacy across multiple platforms. We also found that players expectations regarding intimate partner are diversified, and mismatch of expectations may leads to issues like privacy leakage or emotional exploitation. Based on our findings, we propose design implications for reducing privacy and safety risks and fostering healthier social interactions in virtual worlds.
Artifact Removal From Sleep-Disordered EEG by Wavelet Enhanced Independent Component Analysis
Creators: Fan, Xinyi
Publisher: name: University of Alberta Library
Year: 2024

In the field of sleep research, the quantitative analysis of electroencephalography (EEG) data acquired during sleep offers invaluable insights. However, the presence of artifacts in such data can severely distort analytical outcomes. Therefore, this study aims to develop an innovative artifact detection and rejection tool to enhance the analysis of sleep EEG data from overnight polysomnography (PSG) in patients with sleep disorders.

While recent advancements have seen the trend of artifact removal using a hybrid method, these techniques typically require pre-labeled data for training machine learn- ing models, introducing a dependency on prior knowledge. Addressing this limitation, our research introduces a novel unsupervised learning approach, utilizing hierarchical clustering to identify artifactual components within wavelet-enhanced independent component analysis (ICA)-separated data. We present a unique set of features for clustering, including kurtosis, zero-crossing count, skewness, Hjorth parameters, and R ́enyi entropy, tailored to discern artifacts in EEG recordings.

Our methodology affords the flexibility of fully automated artifact removal or semi-automated processes involving visual inspection of hierarchical dendrograms. Comparative analyses demonstrate that this new method not only refines EEG signal quality but also surpasses traditional manual cleaning techniques in performance. The findings underscore the potential of hierarchical clustering in the unsupervised learning landscape for artifact detection, heralding a significant step forward in the preprocessing of EEG data for sleep studies.
Applications of Random Rotations in R^n to test for serial correlation in time series data
Creators: Biswas, Amitakshar
Publisher: name: University of Alberta Library
Year: 2024

Motivated by Elizabeth Meckes’ work on concentration inequalities using the group SO(n) (see [9]), this thesis explores the use of random rotations for detecting autocorrelation in time series data. Traditional tests like the Durbin Watson test assess autocorrelation by analyzing quadratic forms of residual vectors. Our new approach uses concentration inequalities associated with uniform measures on SO(n) to construct a test without strong distributional assumptions.

We propose a new test statistic for autocorrelation in AR(1) processes, utilizing random rotations of sample autocorrelation function. By establishing a subgaussian concentration inequality, we derive a one-sided test with an

upper bound for the p-value. Further refinement through beta adjustment enhances our p-value accuracy. We also generalize it to a two-sided test.

This thesis provides comprehensive background material on group invariance, random rotations, AR(1) processes, and the Durbin-Watson test. Key results, including the concentration inequality proof and beta transformation application, are presented in detail. A simulation study confirms the effectiveness of our rotation test, highlighting its potential in practical statistical applications.
BioSpark: Beyond Analogical Inspiration to LLM-augmented Transfer
Creators: name: Kang, Hyeonsu
name: Lin, David Chuan-en
name: Chen, Yan-Ying
name: Hong, Matthew K.
name: Martelaro, Nikolas
name: Kittur, Aniket
Publisher: name: arXiv
Year: 2025
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences

description: We present BioSpark, a system for analogical innovation designed to act as a creativity partner in reducing the cognitive effort in finding, mapping, and creatively adapting diverse inspirations. While prior approaches have focused on initial stages of finding inspirations, BioSpark uses LLMs embedded in a familiar, visual, Pinterest-like interface to go beyond inspiration to supporting users in identifying the key solution mechanisms, transferring them to the problem domain, considering tradeoffs, and elaborating on details and characteristics. To accomplish this BioSpark introduces several novel contributions, including a tree-of-life enabled approach for generating relevant and diverse inspirations, as well as AI-powered cards including 'Sparks' for analogical transfer; 'Trade-offs' for considering pros and cons; and 'Q&A' for deeper elaboration. We evaluated BioSpark through workshops with professional designers and a controlled user study, finding that using BioSpark led to a greater number of generated ideas; those ideas being rated higher in creative quality; and more diversity in terms of biological inspirations used than a control condition. Our results suggest new avenues for creativity support tools embedding AI in familiar interaction paradigms for designer workflows.
Expanding Biosensing Capabilities with Glucose Test Strips for Amperometric Determination of Diverse Analytes
Creators: Hossain, Faisal
Publisher: name: University of Alberta Library
Year: 2024

Biosensors employ biological materials as recognition units to analyze targets of interest, enhancing sensitivity and selectivity through the utilization of antibodies, enzymes, aptamers, and other biomolecules. This dissertation presents a versatile biosensing platform capable of quantifying various analytes by leveraging commercially available glucose test strips interfaced with a mini-potentiostat. The platform exhibits significantly improved sensitivity compared to conventional glucose meters and accommodates multiple types of test strips within the same experimental setup. Moreover, the use of off-the-shelf glucose test strips enables cost-effective analysis suitable for field applications, obviating the need for sensor fabrication steps. Chapter 1 provides an overview of sensors and biosensors, elucidating principles and recent advancements across various types. Furthermore, the chapter discusses the history of glucose sensing and the growing trend of the strips for non-glucose target analysis, particularly in resource-limited settings. Chapter 2 presents the development of an orthophosphate sensor utilizing enzymatic reactions of orthophosphate and maltose in the presence of maltose phosphorylase to generate equivalent amount of glucose to orthophosphate and finally measuring the glucose concentration with commercial glucose test strips connected with a hand-held potentiostat. This sensor provided ~400 times higher sensitivity than the commercial glucose meters in orthophosphate sensing from tap and river water. Building upon this sensor, Chapter 3 introduces a SARS-CoV-2 virus and anti-SARS-CoV-2 spike RBD antibody biosensor, demonstrating its application in artificial human serum and saliva analysis. Chapter 4 showcases the orthophosphate sensor's utility in quantifying single-stranded DNA (ssDNA), offering higher sensitivity for high nucleotide number ssDNAs. In Chapter 5, commercial glucose test strips are utilized for quantifying both glucose and fructose in beverages, providing insights into total sugar concentration and individual sugar concentrations in grape juice and wine samples. The dissertation concludes in Chapter 6 with a summary of the developed biosensing platform and outlines future research directions. Appendix A presents preliminary results of small molecule target quantification using the biosensor platform, while Appendix B offers preliminary data on an etalon-based sensor for naphthenic acid quantification in water, along with future study prospects.
“Feeling your emotions is an act of rebellion:” Exploring the emotional and psychological wellbeing of children and young people in the climate crisis
Creators: Cooper, Madison E
Publisher: name: University of Alberta Library
Year: 2024

Exposure to climate change is increasingly impacting the emotional and psychological wellbeing of children and young people. The disruption to ecosystems, built environments, economic systems, food systems, social support networks, culture and place-based identity is resulting in experiences of anxiety, grief, distress, isolation, post-traumatic stress disorder, substance use, and suicidality among younger generations. Understanding these complex impacts and how children and young people can be supported while growing up in a time riddled with current and imminent climatic changes is necessary for protecting mental health and wellbeing. Therefore, the purpose of this research was to explore children and youth mental health and wellbeing in the context of climate change.

This thesis begins with a systematic review that examined the nature, range, and extent of current academic literature published between 2010 and 2022 on climate-sensitive mental health outcomes, risk and protective factors, and coping strategies for children and young people. Articles explored clinical and subclinical mental health outcomes such as anxiety, depression, stress, post-traumatic stress disorder, and impacts to social/community wellbeing. Factors such as age, economic insecurity, displacement, and a lack of social support were identified in literature as those that amplify the vulnerability of children and young people to these impacts. Studies also explored how strong social support networks, education, and connection to culture can protect youth from these adverse outcomes.

Within the realm of social support, peer support is emerging as a coping strategy for young people in the context of climate change. This idea was explored in the second part of this dissertation. Youth who have attended climate cafés in Canada, a peer support space for reflecting on climate emotions, as well as climate café facilitators, participated in semi-structured interviews. Participants found that through active listening and shifting their focus from external action to their internal emotional experiences, climate cafés were helpful in processing emotion and building community and resilience. These feeling-centered healing spaces have the potential to positively influence feelings of self-worth, and help youth manage burnout.

As youth continue to learn how to live in a time of constant environmental change, it is necessary to explore and understand the complex ways in which climate change impacts mental health and wellbeing. This understanding is needed to recognize varying manifestations of climate-sensitive mental health outcomes and potential risk and protective factors, as well as to actualize coping strategies that build connection and empower children and young people.
Theoretical and Numerical Study of SIR with variable susceptibility
Creators: Wagner, Connor J
Publisher: name: University of Alberta Library
Year: 2024

We begin with a survey of mathematical epidemic modelling from its inception to present day. We present up-to-date research on the field of variable susceptibility SIR (Susceptible-Infected-Removed system of differential equations model), which takes the classic SIR model and adds another dimension: susceptibility. The susceptible population here is grouped into categories according to their likelihood to contract a disease upon exposure and each of these is governed by differential equations that are identical except for each group's susceptibility coefficient, which appears in a product with the infectivity coefficient $\beta$. This model is studied numerically, and the resultant course of epidemic behaviour (cumulative infections) follows the pattern of the Gompertz function of the form $f(t)=Me^{-e^{b-at}}$. This function also fits closely with observed historical epidemic data. The implications of changing factors such as the number of groups and average susceptibility are studied extensively. A few other connections to the literature regarding the variable susceptibility and classic models are also explored numerically. Two proofs are provided that the deterministic model can only generate one course of epidemic behaviour based on a fixed set of initial conditions and parameters, one of which does not rely on continuity of the solution functions. An algorithm is described which, in theory, could retrieve these initial conditions from total or even early epidemic behaviour. A short conclusion and discussion of future directions concludes the thesis.
Supplementary document for Influence of the interaction geometry on the fidelity of the two-qubit Rydberg blockade gate - 6592421.pdf
Creators: name: Vybornyi, Ivan
name: Gerasimov, Leonid
name: Kupriyanov, Dmitriy
name: Straupe, Stanislav
name: Tikhonov, Kirill
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplement 1
Predicting Tropical Cyclone Track Forecast Errors using a Probabilistic Neural Network
Creators: name: Fernandez, M. A.
name: Barnes, Elizabeth A.
name: Barnes, Randal J.
name: DeMaria, Mark
name: McGraw, Marie
name: Chirokova, Galina
name: Lu, Lixin
Publisher: name: arXiv
Year: 2025
Subjects: subject: Atmospheric and Oceanic Physics (physics.ao-ph)
subject: Machine Learning (cs.LG)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: A new method for estimating tropical cyclone track uncertainty is presented and tested. This method uses a neural network to predict a bivariate normal distribution, which serves as an estimate for track uncertainty. We train the network and make predictions on forecasts from the National Hurricane Center (NHC), which currently uses static error distributions based on forecasts from the past five years for most applications. The neural network-based method produces uncertainty estimates that are dynamic and probabilistic. Further, the neural network-based method allows for probabilistic statements about tropical cyclone trajectories, including landfall probability, which we highlight. We show that our predictions are well calibrated using multiple metrics, that our method produces better uncertainty estimates than current NHC approaches, and that our method achieves similar performance to the Global Ensemble Forecast System. Once trained, the computational cost of predictions using this method is negligible, making it a strong candidate to improve the NHC's operational estimations of tropical cyclone track uncertainty.
description: 26 (single column) pages + 8 figures (appended supplemental: 20 pages + 17 figures)
Additional file 1 of The rate and assessment of muscle wasting during critical illness: a systematic review and meta-analysis
Creators: name: Fazzini, Brigitta
name: Märkl, Tobias
name: Costas, Christos
name: Blobner, Manfred
name: Schaller, Stefan J.
name: Prowle, John
name: Puthucheary, Zudin
name: Wackerhage, Henning
Publisher: name: figshare
Year: 2024
Subjects: subject: Space Science
subject: Medicine
subject: Physiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified
subject: Science Policy

description: Additional file 1. Table 1. Quality and risk of bias assessment using the Newcastle-Ottawa Scale (NOS) for observational studies assessing muscle wasting. Table 2. Quality and risk of bias assessment using the Newcastle-Ottawa Scale (NOS) for observational studies assessing ICU-acquired weakness. Figure 1. Risk of Bias.
Scalable solution chemical synthesis and comprehensive analysis of Bi2Te3 and Sb2Te3
Creators: name: Hamawandi, Bejan
name: Parsa, Parva
name: Pudza, Inga
name: Pudzs, Kaspars
name: Kuzmin, Alexei
name: Ballikaya, Sedat
name: Welter, Edmund
name: Szukiewicz, Rafal
name: Kuchowicz, Maciej
name: Toprak, Muhammet S.
Publisher: name: arXiv
Year: 2025
Subjects: subject: Applied Physics (physics.app-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Thermoelectric (TE) materials can directly convert heat into electrical energy. However, they sustain costly production procedures and batch-to-batch performance variations. Therefore, developing scalable synthetic techniques for large-scale and reproducible quality TE materials is critical for advancing TE technology. This study developed a facile, high throughput, solution-chemical synthetic technique. Microwave-assisted thermolysis process, providing energy-efficient volumetric heating, was used for the synthesis of bismuth and antimony telluride (Bi2Te3, Sb2Te3). As-made materials were characterized using various techniques, including XRPD, SEM, TEM, XAS, and XPS. Detailed investigation of the local atomic structure of the synthesized Bi2Te3 and Sb2Te3 powder samples was conducted through synchrotron radiation XAS experiments. The sintered TE materials exhibited low thermal conductivity, achieving the highest TE figure-of-merit values of 0.7 (573 K) and 0.9 (523 K) for n-type Bi2Te3 and p-type Sb2Te3, respectively, shifted significantly to the high-temperature region when compared to earlier reports, highlighting their potential for power generation applications. The scalable, energyand time-efficient synthetic method developed, along with the demonstration of its potential for TE materials, opens the door for a wider application of these materials with minimal environmental impact.
CooperOpenPracticesDisclosure_rev – Supplemental material for Memories Fade: The Relationship Between Memory Vividness and Remembered Visual Salience
Creators: name: Cooper, Rose A.
name: Kensinger, Elizabeth A.
name: Ritchey, Maureen
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)
subject: Neuroscience

description: Supplemental material, CooperOpenPracticesDisclosure_rev for Memories Fade: The Relationship Between Memory Vividness and Remembered Visual Salience by Rose A. Cooper, Elizabeth A. Kensinger and Maureen Ritchey in Psychological Science
Additional file 1 of What are the experiences, preparation, and support needs of early career clinical educators within an Australian tertiary health service?: a qualitative study
Creators: name: Stirling, Victoria
name: Fitzgerald, Deborah
name: Moores, Alis
name: Wenke, Rachel
Publisher: name: figshare
Year: 2024
Subjects: Medicine
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Science Policy

description: Supplementary Material 1
AUT838950_Lay_Abstract – Supplemental material for Altered bodily self-consciousness and peripersonal space in autism
Creators: name: Cari-Lène Mul
name: Cardini, Flavia
name: Stagg, Steven D
name: Shabnam Sadeghi Esfahlani
name: Kiourtsoglou, Dimitrios
name: Cardellicchio, Pasquale
name: Aspell, Jane Elizabeth
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, AUT838950_Lay_Abstract for Altered bodily self-consciousness and peripersonal space in autism by Cari-lène Mul, Flavia Cardini, Steven D Stagg, Shabnam Sadeghi Esfahlani, Dimitrios Kiourtsoglou, Pasquale Cardellicchio and Jane Elizabeth Aspell in Autism
Supplementary document for Analysis of rotational Doppler shift with multi-ring vortex beams - 6592743.pdf
Creators: name: zhu, xiagnyang
name: Ding, You
name: Tang, Ruoyu
name: Liu, Tong
name: Chen, Xiaocen
name: qiu, song
name: Liu, Zhengliang
name: ren, yuan
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplemental experimental results
Additional file 2 of Testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali (LAKANA): study protocol for a cluster-randomized, placebo-controlled, double-blinded, parallel-group, three-arm clinical trial
Creators: name: Adubra, Laura
name: Alber, Dagmar
name: Ashorn, Per
name: Ashorn, Ulla
name: Cheung, Yin Bun
name: Cloutman-Green, Elaine
name: Diallo, Fatoumata
name: Ducker, Camilla
name: Elovainio, Riku
name: Fan, Yue-Mei
name: Gates, Lily
name: Gruffudd, Gwydion
name: Haapaniemi, Tiia
name: Haidara, Fadima
name: Hallamaa, Lotta
name: Ihamuotila, Rikhard
name: Klein, Nigel
name: Luoma, Juho
name: Martell, Owen
name: Sow, Samba
name: Vehmasto, Taru
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Pharmacology
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 2. World Health Organization Trial Registration Data Set.
Assessing spider (Araneae) diversity and pitfall trap retention in canola (Brassica napus L.) agroecosystems in north-central Alberta, Canada
Creators: Kent, Kirra
Publisher: name: University of Alberta Library
Year: 2024

Little is understood about the role of spiders (Araneae), their community composition, and predator-prey interactions in canola agroecosystems. Understanding these relationships may inform management decisions to effectively use spiders as biological control agents against insect pests. In 2021-22, a study was conducted to assess spider diversity in canola (Brassica napus L.) fields in the aspen parkland region of Alberta. The initial sampling regime installed traps on the edge and within the field interior, with few spiders captured. To overcome this, additional experiments in 2023 tested modified pitfall trap designs, to improve the retention rates of all spiders. Modified trap designs consisted of a combination of three factors: trap size, presence/absence of polytetrafluoroethylene (PTFE), and presence/absence of preservative fluid (propylene glycol). PTFE is a substance used for creating non-stick surfaces, which causes spider silk to fail to adhere effectively. Traps with and without preservative were included to test if PTFE could improve the retention of live spiders. Glass beads were used as they provided hiding spaces without damaging the traps inner walls. Beads were only employed in the 24-hour sampling periods, all 7-day sampling periods employed only preservative filled traps, which were treated or untreated with PTFE. Traps were installed in two habitat types, herbaceous edges, and woody tree edges. Across all years of this study, the spider community in canola was dominated by two species in the family Lycosidae: Pardosa distincta (Blackwall, 1846) and Pardosa moesta Banks, 1892. Trap diameter, PTFE application and preservation method impacted the abundance, diversity and richness of spiders collected. Large trap sizes treated with PTFE increased the abundance, diversity and richness of spiders captured, but only in tree-edge habitat. Taken collectively, this research will further our understanding of the role of abundant spider species in the aspen parkland-canola agroecosystem and offer a novel technique for improving the passive-live collection of spiders.
Joint Level Generation and Translation Using Gameplay Videos
Creators: Mirgati, Seyyede Negar
Publisher: name: University of Alberta Library
Year: 2024

Procedural Content Generation via Machine Learning (PCGML) faces a significant hurdle that sets it apart from other ML problems, such as image or text generation, which is limited annotated data. For example, many existing methods for level generation via machine learning specifically require a secondary representation beyond level images. However, the current methods for obtaining such representations are laborious and time-consuming, which contributes to the limited data problem.

 In this work, we aim to address the limited game level data problem by utilizing gameplay videos of human-annotated games to train a novel multi-tail framework to perform simultaneous level translation and generation. The translation tail of our framework can convert gameplay video frames to an equivalent secondary representation, while its generation tail can produce novel level segments. Evaluation results and comparisons between our framework and baselines suggest that combining the level generation and translation tasks can lead to improved performance for both tasks. Additionally, we have conducted experiments to evaluate the generalizability of our model across different scenarios. Our findings represent a possible solution to limited annotated level data, and we demonstrate the potential for future iterations of our model to generalize to unseen games.
Transforming Healthcare Data Engineering: Driving Scalable, Accurate, and Impactful Decision-Making
Creators: name: Hallur, Jayanna
Publisher: name: figshare
Year: 2025
Subjects: classificationCode: 460501
subject: Data engineering and data science
classificationCode: 460102
subject: Applications in health
classificationCode: 420302
subject: Digital health
classificationCode: 420304
subject: General practice
classificationCode: 420305
subject: Health and community services
classificationCode: 420306
subject: Health care administration
classificationCode: 420308
subject: Health informatics and information systems

description: The healthcare industry creates a huge amount of data every day, from patient records, enrollments, medical devices data to insurance claims and lab results. Many healthcare systems find it hard to manage this data because of problems like outdated technology, heterogeneous systems, data silos, and issues with data quality. These challenges make it difficult to use the data effectively for better decision-making and improved patient care. This article explores how modern data engineering is helping healthcare organizations handle their data better. New tools like cloud systems, real-time data processing, and artificial intelligence are making it easier to combine and clean data from different sources. With these advancements in data engineering, the healthcare providers can make faster and more accurate decisions. This process improves patient care, reduces costs, and helps manage resources more efficiently. Examples like predicting patient readmissions and monitoring ICU patients in real-time show how this approach can make a big difference. The article also looks at new ideas like using AI that can explain its decisions and faster data processing with edge computing. Modernizing healthcare data systems is critical for creating better outcomes for everyone.
Supplemental Material, Neck_pain_and_migraine_-_association_or_cause_supplement - Neck pain and migraine: Association or cause?—A narrative review of the literature
Creators: name: Albisser, Arlette
name: Clec’h, Yann Le
name: Sprott, Haiko
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine

description: Supplemental Material, Neck_pain_and_migraine_-_association_or_cause_supplement for Neck pain and migraine: Association or cause?—A narrative review of the literature by Arlette Albisser, Yann Le Clec’h, and Haiko Sprott in Clinical and Translational Neuroscience
FDCT: Frequency-Aware Decomposition and Cross-Modal Token-Alignment for Multi-Sensor Target Classification
Creators: name: Sami, Shoaib Meraj
name: Hasan, Md Mahedi
name: Nasrabadi, Nasser M.
name: Rao, Raghuveer
Publisher: name: arXiv
Year: 2025
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: In automatic target recognition (ATR) systems, sensors may fail to capture discriminative, fine-grained detail features due to environmental conditions, noise created by CMOS chips, occlusion, parallaxes, and sensor misalignment. Therefore, multi-sensor image fusion is an effective choice to overcome these constraints. However, multi-modal image sensors are heterogeneous and have domain and granularity gaps. In addition, the multi-sensor images can be misaligned due to intricate background clutters, fluctuating illumination conditions, and uncontrolled sensor settings. In this paper, to overcome these issues, we decompose, align, and fuse multiple image sensor data for target classification. We extract the domain-specific and domain-invariant features from each sensor data. We propose to develop a shared unified discrete token (UDT) space between sensors to reduce the domain and granularity gaps. Additionally, we develop an alignment module to overcome the misalignment between multi-sensors and emphasize the discriminative representation of the UDT space. In the alignment module, we introduce sparsity constraints to provide a better cross-modal representation of the UDT space and robustness against various sensor settings. We achieve superior classification performance compared to single-modality classifiers and several state-of-the-art multi-modal fusion algorithms on four multi-sensor ATR datasets.
description: 12 pages Accepted in the IEEE Transactions on Aerospace and Electronic Systems
Efficient Procurement and Trading of Electric Vehicle Charging Flexibility
Creators: Sales-Ortiz, Javier C
Publisher: name: University of Alberta Library
Year: 2024

This thesis studies a virtual power plant (VPP) that trades the bidirectional charging flexibility of privately owned plug-in electric vehicles (EVs) in a real-time electricity market to maximize its profit. The main contribution of this thesis is the development of scalable and efficient algorithms for the procurement and scheduling of this flexibility. Specifically, to incentivize EVs to allow bidirectional charging, we design incentive-compatible, variable-term contracts between the VPP and EVs. Through deliberate aggregation of the energy storage capacity of individual EVs, we construct an abstraction of the aggregate flexibility that can be provided by the connected EVs. This abstraction is called a virtual battery and its operation is scheduled in real-time by learning a reinforcement learning (RL) policy. This policy efficiently trades the available flexibility, independent of the number of accepted contracts and connected

EVs. The proposed aggregation method ensures the satisfaction of individual EV charging requirements by constraining the optimal action returned by the RL policy within certain bounds. We then develop a disaggregation scheme to allocate power to bidirectional chargers. We formulate this as a resource allocation problem, in which the total amount of energy traded in the market is distributed in a proportionally fair manner among the connected EVs. Evaluation on a real-world dataset demonstrates robust performance of the proposed method despite high variability of electricity prices and shifts in the distribution of EV mobility.
Supplementary_Table_1 - End-of-Life Health-Care Cost of Patients With Lung Cancer: A Retrospective Study
Creators: name: Souliotis, Kyriakos
name: Kani, Chara
name: Marioli, Androniki
name: Aggeliki Kamboukou
name: Prinou, Aikaterini
name: Syrigos, Konstantinos
name: Markantonis, Sophia
Publisher: name: SAGE Journals
Year: 2019
Subjects: subject: Medicine
subject: 111799 Public Health and Health Services not elsewhere classified
subject: FOS: Health sciences

description: Supplementary_Table_1 for End-of-Life Health-Care Cost of Patients With Lung Cancer: A Retrospective Study by Kyriakos Souliotis, Chara Kani, Androniki Marioli, Aggeliki Kamboukou, Aikaterini Prinou, Konstantinos Syrigos and Sophia Markantonis in Health Services Research and Managerial Epidemiology
Developing a GPU based Real-Time Particle Image Velocimetry System for Active Flow Control
Creators: Friesen, Ivy O
Publisher: name: University of Alberta Library
Year: 2024

The objective of this work was to create a Graphical Processing Unit (GPU)-based Real-Time Particle Image Velocimetry (RT-PIV) system for use in Active Flow Control (AFC) of a Turbulent Boundary Layer (TBL), and to evaluate the effect of effect of the flow control on the boundary layer. The experiment involved using the Cross-Correlation (CC) method utilizing Fast Fourier Transform (FFT) to compute particle displacement between two image pairs. The FFT method was chosen for its low computational cost, and ability to implement calculations on the GPU. Computations were done in MATLAB using a NVIDIA GeForce GTX 1080 Ti Graphical Processing Unit (GPU). The calculated RT-PIV vector fields were size 3 × 30, with 3 vectors in the streamwise direction and 30 vectors in the wall-normal direction. The average time for the RT-PIV code to process on the GPU was found to be 1.20 ms, with a standard deviation of 0.07 ms. The RTPIV AFC system was tested at 25 Hz in the University of Alberta wind tunnel. The time limiting factor for this test was the laser, the New Wave Research Gemini 30 Hz PIV Nd:YAG Laser system. A voice-coil actuator was used as the active surface actuator for flow control. This actuator was mounted flush to the floor of the wind tunnel and had a range of motion of ± 3 mm displacement. One streamwise vector from each vector field was used as the input to the controller. The calculated particle velocity between two frames was filtered using a first order Butterworth filter and a proportional control law was used to determine the signal sent to the actuator. This filter was used to attenuate higher frequency noise from the measured velocity. A parametric study was done on varying the filter cutoff frequency (5 Hz or 10 Hz) of the lowpass Butterworth filter, as well as the location of the vector used for flow control (8 mm or 11 mm above the wind tunnel floor). The Reynolds shear stress plots for each of the four experiment iterations were plotted and compared with and without actuation. The trial using a filter cutoff frequency of 5 Hz and input vector 11 mm from the wind tunnel floor showed the most promising results with a decrease in Reynolds shear stress when actuation was occurring, however, more tests are needed to ensure these results are statistically significant. Future work includes using a higher frequency, higher powered laser for better PIV image results, using a NVIDIA RTX 3090 GPU for faster algorithm speed, using an actuator with higher range of motion, and utilizing different control laws.
Reinforcement Learning for Home Energy Management
Creators: Tchir, Zachary J
Publisher: name: University of Alberta Library
Year: 2024

As societies face the implications of climate change and the pressing need for sustainable energy solutions, this thesis introduces an innovative Home Energy Management System (HEMS) designed to tackle critical challenges in contemporary energy consumption and management of households. The system aims to fulfill three objectives: ensuring cost-efficiency for homeowners, optimizing the State of Charge (SoC) for electric vehicles (EVs) to alleviate range anxiety, and enhancing home security during power outages. The presented research results highlight the potential of HEMS in promoting sustainable living practices, economic benefits, and resilience against energy uncertainties.A key component of our research is the application of Reinforcement Learning (RL) to train agents within the HEMS framework. These agents demonstrate an exceptional ability to minimize monthly energy costs by effectively managing energy consumption, storage, and generation and leveraging off-peak electricity rates, solar power, and battery storage. The system's efficiency in reducing grid reliance is further enhanced by integrating Vehicle-to-Everything (V2X) technologies and engaging energy export mechanisms. Our research makes a significant contribution by addressing some of the common obstacles to entry into renewable technologies. Specifically, we tackle the issue of EV range anxiety and present a sophisticated approach to maintaining an optimal EV SoC that matches the preferences of the homeowner/driver(s). The HEMS ensures that EVs are adequately charged to meet daily transportation needs.\\Moreover, the thesis highlights the ability of an RL-based HEMS to ensure homeowner security during grid disruptions. Our system's capability to efficiently manage and allocate stored energy emphasizes its effectiveness in sustaining essential household functions during power outages. It demonstrates HEMS's importance and ability to cope with energy interruptions.   Our work shows the importance and potential of developing AI-based control techniques. It highlights their ability to significantly influence future intelligent energy management systems and lead them toward a more sustainable and human-centric solution.
Additional file 3 of Testing the effects of mass drug administration of azithromycin on mortality and other outcomes among 1–11-month-old infants in Mali (LAKANA): study protocol for a cluster-randomized, placebo-controlled, double-blinded, parallel-group, three-arm clinical trial
Creators: name: Adubra, Laura
name: Alber, Dagmar
name: Ashorn, Per
name: Ashorn, Ulla
name: Cheung, Yin Bun
name: Cloutman-Green, Elaine
name: Diallo, Fatoumata
name: Ducker, Camilla
name: Elovainio, Riku
name: Fan, Yue-Mei
name: Gates, Lily
name: Gruffudd, Gwydion
name: Haapaniemi, Tiia
name: Haidara, Fadima
name: Hallamaa, Lotta
name: Ihamuotila, Rikhard
name: Klein, Nigel
name: Luoma, Juho
name: Martell, Owen
name: Sow, Samba
name: Vehmasto, Taru
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Pharmacology
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 3. Reporting checklist for protocol of a clinical trial.
Consumer acceptance of cricket-based snacks
Creators: De Leon Siller, Susana
Publisher: name: University of Alberta Library
Year: 2024

Insects have been proposed as a more sustainable protein alternative to conventional meat sources. However, consumer acceptance of edible insects is still low in the western hemisphere. The purpose of this study was to examine how characteristics of a cricket-based product along with consumer beliefs influence the overall liking and willingness to try the cricket-based food product. An online survey was conducted in the province of Alberta, Canada. Participants (n=548) were asked to indicate their overall liking (OL) and willingness to try (WTT) a cricket-based snack in a conjoint analysis experiment. A 2x2x5 design was used for the product characteristics (type of product, presence of an image of the product, product benefit claims). Five product profiles were assigned to each participant using a balanced incomplete block design. The type of product (cricket chips and whole roasted crickets) was found to be the most important attribute for participants. Product benefit claims were not effective at increasing the OL or WTT of the cricket-based snacks presented to participants. Higher scores in the Entomophagy Attitude Scale, and previous experiences consuming insect-based food products positively influenced WTT and OL. The findings of this study underscore the significance of the type of product and personal attitudes towards entomophagy in shaping consumer preferences for sustainable protein sources and offer valuable insights for the development and marketing of insect-based food products in western markets.
Supplementary document for A compact effective surface plasmon polariton transmission line with undiminished bandwidth and enhanced field confinement - 6592748.pdf
Creators: name: Zhang, Anqi
name: Han, Donglin
name: Yi, Yang
name: Liu, Leilei
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: 1.Derivation of the dispersion relation of CESPPs 2. Analysis of the crosstalk suppression 3. Manufacturing process of CESPP TL on the SIW platform