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Articles 333331 - 333360 of 5167699
Full-Text Articles in Entire DC Network
Psyx 230.50: Developmental Psychology, Jaida Lily
Psyx 230.50: Developmental Psychology, Jaida Lily
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Wldg 210.01: Pipe Welding, Daniel J. Pignotti
Wldg 210.01: Pipe Welding, Daniel J. Pignotti
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Writ 101.52: College Writing I, Blake M. Sherman
Writ 101.52: College Writing I, Blake M. Sherman
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Ahat 324.01: Assessment Of The Extremities, Melanie L. Mcgrath
Ahat 324.01: Assessment Of The Extremities, Melanie L. Mcgrath
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Atep 540.01: Practicum In Athletic Training I, Nick Cromidas, James Paul Capp, Taylor J. Purchio
Atep 540.01: Practicum In Athletic Training I, Nick Cromidas, James Paul Capp, Taylor J. Purchio
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Atep 581.01: Therapeutic Interventions I, Nick Cromidas
Atep 581.01: Therapeutic Interventions I, Nick Cromidas
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Csd 109.01: Slpeeps - A First Year Guide To Communication Sciences And Disorders, Coille A. Putman
Csd 109.01: Slpeeps - A First Year Guide To Communication Sciences And Disorders, Coille A. Putman
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Csd 110.50: Introduction To Speech, Language, And Audiology Online, Jennifer K. Schoffer Closson
Csd 110.50: Introduction To Speech, Language, And Audiology Online, Jennifer K. Schoffer Closson
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Not Feeling The Heat? Effects Of Dietary Protein On Satiation And Satiety In Mice Are Not Due To Its Impact On Body Temperature, Jazmin Osorio M, Sharon E Mitchell, Catherine Hambly, David B Allison, John R Speakman
Not Feeling The Heat? Effects Of Dietary Protein On Satiation And Satiety In Mice Are Not Due To Its Impact On Body Temperature, Jazmin Osorio M, Sharon E Mitchell, Catherine Hambly, David B Allison, John R Speakman
Children’s Nutrition Research Center Staff Publications
Dietary protein modulates food intake (FI) via unclear mechanism(s). One possibility is that higher protein leads to greater post-ingestive heat production (Specific dynamic action: SDA) leading to earlier meal termination (increased satiation), and inhibition of further intake (increased satiety). The influence of dietary protein on feeding behaviour in C57BL/6J mice was tested using an automated FI monitoring system (BioDAQ), simultaneous to body temperature (Tb). Total FI, inter meal intervals (IMI, satiety) and meal size (MS, satiation) were related to changes in Tb after consuming low (5%, LP), moderate (15%, MP) and high (30%, HP) protein diets. Diets were tested over …
Customer Service Revisited, Allen Vean Dmd
Customer Service Revisited, Allen Vean Dmd
Metro Denver Dental Society Articulator Magazine
MDDS Co-Editor, Dr. Allen Vean reflects on the importance of excellent customer service in dentistry. The article draws on personal experience and underscores the significance of patient retention, personal touches and creating a welcoming office environment.
Exploring Ada Commons: Discover What's New Across The Tripartite, Alisun Dekock
Exploring Ada Commons: Discover What's New Across The Tripartite, Alisun Dekock
Metro Denver Dental Society Articulator Magazine
The article details ADA Commons, a new open-access database that offers searchable access to a wide range of dental publications and archival materials from ADA State and Local Associations. ADA Commons allows member dentists to explore, search and contribute to a growing collection of dentistry-related content.
The Social Evaluation Of Accents And Perceived Social Influence In Singapore: A Comparison Of American And Singaporean English Accents, Matthew H. S. Ng, Chi-Ying Cheng
The Social Evaluation Of Accents And Perceived Social Influence In Singapore: A Comparison Of American And Singaporean English Accents, Matthew H. S. Ng, Chi-Ying Cheng
Research Collection School of Social Sciences
Accents are an important differentiator between groups which influence social perception and interaction, especially in a diverse country like Singapore. Social identity theory suggests that individuals would exhibit favoritism towards their own accents. However, the accent prestige theory demonstrates instances whereby foreign accents are perceived as more prestigious than one's own accent and are associated with more positive characteristics. This paper sought to explore which of these two theories is more prevalent in Singapore by comparing the perceptions of American English accents and local Singaporean English accents along the competence-warmth paradigm of the Stereotype Content Model. Further, the current research …
The Link Between People's Social Perceptions Of Cultivated Meat Eaters And Their Acceptance Of Cultivated Meat, Xiaoyu Dai, Angela K. Y. Leung, Mark Chong
The Link Between People's Social Perceptions Of Cultivated Meat Eaters And Their Acceptance Of Cultivated Meat, Xiaoyu Dai, Angela K. Y. Leung, Mark Chong
Research Collection School of Social Sciences
Low consumer acceptance emerges as one important barrier to the introduction of cultivated meat, a novel food which offers an opportunity for more sustainable and ethical meat production. Due to the motives for impression management and self-esteem, one factor that could contribute to people's acceptance of cultivated meat is their perceptions of other individuals who consume cultivated meat. In the current research, two online survey studies with 393 Singaporean undergraduate students and 401 American adults were conducted to explore the perceptions of cultivated meat eaters. In both studies, participants were randomly assigned to read one of three profiles that described …
To Whom Thou Art Bound: Bicultural Identity Integration Moderates The Influence Of Conspiracy Beliefs On Chinese Americans’ Ingroup Bias, Edison Tan, Chi-Ying Cheng, Angela K. Y. Leung, Sheila X. R. Wee
To Whom Thou Art Bound: Bicultural Identity Integration Moderates The Influence Of Conspiracy Beliefs On Chinese Americans’ Ingroup Bias, Edison Tan, Chi-Ying Cheng, Angela K. Y. Leung, Sheila X. R. Wee
Research Collection School of Social Sciences
Endorsing conspiracy beliefs about an outgroup typically fosters ingroup bias. However, the response of bicultural individuals to conspiracy theories about one of their ingroups remains understudied. We posited that bicultural individuals’ display of ingroup bias in such situations hinges on their levels of bicultural identity integration (BII). Two studies involving Chinese American participants revealed that conspiracy beliefs about China were associated with lower Chinese ingroup bias among those with higher BII levels. In Study 1, high BII Chinese Americans who endorsed conspiracy theories about China reported less favorable perceptions of the Chinese ingroup, but not among low BII Chinese Americans. …
Do Pedestrian Safety Improvements Affect Older Adults' Health And Social Outcomes Equitably? A Quasi Experiment In Singapore, Shin Bin Tan, William Tov, Paulin Tay Straughan
Do Pedestrian Safety Improvements Affect Older Adults' Health And Social Outcomes Equitably? A Quasi Experiment In Singapore, Shin Bin Tan, William Tov, Paulin Tay Straughan
Research Collection School of Social Sciences
Pedestrian-friendly neighborhoods are believed to encourage greater social participation, community engagement, and sense of social inclusion, which are important to older individuals at higher risk of being socially isolated. However, most studies on neighborhood walkability, social participation and social inclusion are cross-sectional, making it difficult to robustly establish causal links. Much research on neighborhood walkability is also based in North America and Europe, leaving a knowledge gap on the impact of walkability within other geographic contexts. Furthermore, there is a lack of empirical evidence about whether benefits from traffic calming schemes are distributed equitably. To reduce these empirical gaps, our …
Pias: Privacy-Preserving Incentive Announcement System Based On Blockchain For Internet Of Vehicles, Yonghua Zhan, Yang Yang, Hongju Cheng, Xiangyang Luo, Zhuangshuang Guan, Robert H. Deng
Pias: Privacy-Preserving Incentive Announcement System Based On Blockchain For Internet Of Vehicles, Yonghua Zhan, Yang Yang, Hongju Cheng, Xiangyang Luo, Zhuangshuang Guan, Robert H. Deng
Research Collection School Of Computing and Information Systems
More vehicles are connecting to the Internet of Things (IoT), transforming Vehicle Ad hoc Networks (VANETs) into the Internet of Vehicles (IoV), providing a more environmentally friendly and safer driving experience. Vehicular announcement networks show promise in vehicular communication applications. However, two major issues arise when establishing such a system. Firstly, user privacy cannot be guaranteed when messages are forwarded anonymously, thus the reliability of these messages is in question. Secondly, users often lack interest in responding to announcements. To address these problems, we introduce a Blockchain-based incentive announcement system called PIAS. This system enables anonymous message commitment in a …
Solving Fractional Differential Equations On A Quantum Computer: A Variational Approach, Fong Yew Leong, Dax Enshan Koh, Jian Feng Kong, Siong Thye Goh, Jun Yong Khoo, Wei Bin Ewe, Hongying Li, Jayne Thompson, Dario Poletti
Solving Fractional Differential Equations On A Quantum Computer: A Variational Approach, Fong Yew Leong, Dax Enshan Koh, Jian Feng Kong, Siong Thye Goh, Jun Yong Khoo, Wei Bin Ewe, Hongying Li, Jayne Thompson, Dario Poletti
Research Collection School Of Computing and Information Systems
We introduce an efficient variational hybrid quantum-classical algorithm designed for solving Caputo time-fractional partial differential equations. Our method employs an iterable cost function incorporating a linear combination of overlap history states. The proposed algorithm is not only efficient in terms of time complexity but also has lower memory costs compared to classical methods. Our results indicate that solution fidelity is insensitive to the fractional index and that gradient evaluation costs scale economically with the number of time steps. As a proof of concept, we apply our algorithm to solve a range of fractional partial differential equations commonly encountered in engineering …
Neuron Sensitivity Guided Test Case Selection, Dong Huang, Qingwen Bu, Yichao Fu, Yuhao Qing, Xiaofei Xie, Junjie Chen, Heming Cui
Neuron Sensitivity Guided Test Case Selection, Dong Huang, Qingwen Bu, Yichao Fu, Yuhao Qing, Xiaofei Xie, Junjie Chen, Heming Cui
Research Collection School Of Computing and Information Systems
Deep Neural Networks (DNNs) have been widely deployed in software to address various tasks (e.g., autonomous driving, medical diagnosis). However, they can also produce incorrect behaviors that result in financial losses and even threaten human safety. To reveal and repair incorrect behaviors in DNNs, developers often collect rich, unlabeled datasets from the natural world and label them to test DNN models. However, properly labeling a large number of datasets is a highly expensive and time-consuming task. To address the above-mentioned problem, we propose NSS, Neuron Sensitivity Guided Test Case Selection, which can reduce the labeling time by selecting valuable test …
Certified Continual Learning For Neural Network Regression, Hong Long Pham, Jun Sun
Certified Continual Learning For Neural Network Regression, Hong Long Pham, Jun Sun
Research Collection School Of Computing and Information Systems
On the one hand, there has been considerable progress on neural network verification in recent years, which makes certifying neural networks a possibility. On the other hand, neural network in practice are often re-trained over time to cope with new data distribution or for solving different tasks (a.k.a. continual learning). Once re-trained, the verified correctness of the neural network is likely broken, particularly in the presence of the phenomenon known as catastrophic forgetting. In this work, we propose an approach called certified continual learning which improves existing continual learning methods by preserving, as long as possible, the established correctness properties …
Imbalanced Graph Classification With Multi-Scale Oversampling Graph Neural Networks, Rongrong Ma, Guansong Pang, Ling Chen
Imbalanced Graph Classification With Multi-Scale Oversampling Graph Neural Networks, Rongrong Ma, Guansong Pang, Ling Chen
Research Collection School Of Computing and Information Systems
One main challenge in imbalanced graph classification is to learn expressive representations of the graphs in under-represented (minority) classes. Existing generic imbalanced learning methods, such as oversampling and imbalanced learning loss functions, can be adopted for enabling graph representation learning models to cope with this challenge. However, these methods often directly operate on the graph representations, ignoring rich discriminative information within the graphs and their interactions. To tackle this issue, we introduce a novel multi-scale oversampling graph neural network (MOSGNN) that learns expressive minority graph representations based on intra- and inter-graph semantics resulting from oversampled graphs at multiple scales - …
Cluster-Wide Task Slowdown Detection In Cloud System, Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
Cluster-Wide Task Slowdown Detection In Cloud System, Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
Research Collection School Of Computing and Information Systems
Slow task detection is a critical problem in cloud operation and maintenance since it is highly related to user experience and can bring substantial liquidated damages. Most anomaly detection methods detect it from a single-task aspect. However, considering millions of concurrent tasks in large-scale cloud computing clusters, it becomes impractical and inefficient. Moreover, single-task slowdowns are very common and do not necessarily indicate a malfunction of a cluster due to its violent fluctuation nature in a virtual environment. Thus, we shift our attention to cluster-wide task slowdowns by utilizing the duration time distribution of tasks across a cluster, so that …
Editorial: Dsaa 2023 Journal Track On Theoretical And Practical Data Science And Analytics., Bin Yang, Feida Zhu, Wei Wei
Editorial: Dsaa 2023 Journal Track On Theoretical And Practical Data Science And Analytics., Bin Yang, Feida Zhu, Wei Wei
Research Collection School Of Computing and Information Systems
This special issue of the International Journal of Data Science and Analytics includes the DSAA 2023 Journal Track papers, which cover advances in both theoretical and practical aspects of data science and analytics, with a particular focus on trustworthy data science and analytics. The track contains nine papers, all of which underwent rigorous review by the guest editors and invited reviewers.
Quantum Relaxation For Solving Multiple Knapsack Problems, Monit Sharma, Jin Yan, Hoong Chuin Lau, Rudy Raymond
Quantum Relaxation For Solving Multiple Knapsack Problems, Monit Sharma, Jin Yan, Hoong Chuin Lau, Rudy Raymond
Research Collection School Of Computing and Information Systems
Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variational approaches such as QAOA, most problems addressed are unconstrained (such as Max-Cut). In this study, we investigate a hybrid quantum-classical method for constrained optimization problems, particularly those with knapsack constraints that occur frequently in financial and supply chain applications. Our proposed method relies firstly on relaxations to local quantum Hamiltonians, defined through commutative maps. Drawing inspiration from quantum random access code (QRAC) concepts, particularly Quantum Random Access Optimizer (QRAO), we explore QRAO's potential in solving large constrained …
Developer Reactions To Protestware In Open Source Software: The Cases Of Color.Js And Es5.Ext, Youmei Fan, Dong Wang, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula
Developer Reactions To Protestware In Open Source Software: The Cases Of Color.Js And Es5.Ext, Youmei Fan, Dong Wang, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula
Research Collection School Of Computing and Information Systems
There is growing concern about maintainers self-sabotaging their work in order to take political or economic stances, a practice referred to as “protestware”. Our objective is to understand the discourse around discussions on such an attack, how it is received by the community, and whether developers respond to the attack in a timely manner. We study two notable protestware cases i.e., colors.js and es5-ext. Results indicate that protestware discussions are spread more quickly on the GitHub platform, while security vulnerabilities are faster on social media. By establishing a taxonomy of protestware discussions, we identify posts that express stances and provide …
Sound And Complete Witnesses For Template-Based Verification Of Ltl Properties On Polynomial Programs, Krishnendu Chatterjee, Amir Goharshady, Ehsan Goharshady, Mehrdad Karrabi, Dorde Zikelic
Sound And Complete Witnesses For Template-Based Verification Of Ltl Properties On Polynomial Programs, Krishnendu Chatterjee, Amir Goharshady, Ehsan Goharshady, Mehrdad Karrabi, Dorde Zikelic
Research Collection School Of Computing and Information Systems
We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formulas in which atomic propositions can be polynomial constraints and turn our focus to polynomial arithmetic programs, i.e. programs in which every assignment and guard consists only of polynomial expressions. For this setting, we provide an efficient algorithm to automatically synthesize such LTL witnesses. Our synthesis procedure is both …
Text-Driven Video Prediction, Xue Song, Jingjing Chen, Bin Zhu, Yu-Gang Jiang
Text-Driven Video Prediction, Xue Song, Jingjing Chen, Bin Zhu, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Current video generation models usually convert signals indicating appearance and motion received from inputs (e.g., image and text) or latent spaces (e.g., noise vectors) into consecutive frames, fulfilling a stochastic generation process for the uncertainty introduced by latent code sampling. However, this generation pattern lacks deterministic constraints for both appearance and motion, leading to uncontrollable and undesirable outcomes. To this end, we propose a new task called Text-driven Video Prediction (TVP). Taking the first frame and text caption as inputs, this task aims to synthesize the following frames. Specifically, appearance and motion components are provided by the image and caption …
Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw
Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous work presents a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mining topic representations at a large scale while seeking to mitigate bias from sampling, enabling the investigation of widely used automated coherence metrics via large corpora. Additionally, this article proposes a novel user study design, an amalgamation of different proxy tasks, to derive a finer insight into the human decision-making processes. This design subsumes the purpose of simple rating and outlier-detection user studies. Similar to the …
Probing Effects Of Contextual Bias On Number Magnitude Estimation, Xuehao Du, Ping Ji, Wei Qin, Lei Wang, Yunshi Lan
Probing Effects Of Contextual Bias On Number Magnitude Estimation, Xuehao Du, Ping Ji, Wei Qin, Lei Wang, Yunshi Lan
Research Collection School Of Computing and Information Systems
The semantic understanding of numbers requires association with context. However, powerful neural networks overfit spurious correlations between context and numbers in training corpus can lead to the occurrence of contextual bias, which may affect the network's accurate estimation of number magnitude when making inferences in real-world data. To investigate the resilience of current methodologies against contextual bias, we introduce a novel out-of- distribution (OOD) numerical question-answering (QA) dataset that features specific correlations between context and numbers in the training data, which are not present in the OOD test data. We evaluate the robustness of different numerical encoding and decoding methods …
Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie
Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie
Research Collection School Of Computing and Information Systems
Multi-agent systems (MASs) have achieved remarkable success in multi-robot control, intelligent transportation, and multiplayer games, etc. Thorough testing for MAS is urgently needed to ensure its robustness in the face of constantly changing and unexpected scenarios. Existing methods mainly focus on single-agent system testing and cannot be directly applied to MAS testing due to the complexity of MAS. To our best knowledge, there are fewer studies on MAS testing. While several studies have focused on adversarial attacks on MASs, they primarily target failure detection from an attack perspective, i.e., discovering failure scenarios, while ignoring the diversity of scenarios. In this …
Ft2ra: A Fine-Tuning-Inspired Approach To Retrieval-Augmented Code Completion, Qi Guo, Shangqing Liu, Xiaofei Xie, Ze Tang Tang
Ft2ra: A Fine-Tuning-Inspired Approach To Retrieval-Augmented Code Completion, Qi Guo, Shangqing Liu, Xiaofei Xie, Ze Tang Tang
Research Collection School Of Computing and Information Systems
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these models, especially large models, poses a significant challenge when it comes to fine-tuning them for specific downstream tasks. As an alternative approach, retrieval-based methods have emerged as a promising solution, augmenting model predictions without the need for fine-tuning. Despite their potential, a significant challenge is that the designs of these methods often rely on heuristics, leaving critical questions about what information should be stored or retrieved and how to interpolate such information for …