bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retrospective evaluation and review of approaches for nonspecific lameness in dogs presented to an emergency service (2013–2014): 134 cases
Authors: Ramos Meghan T. , Hartzell Alexandra M. , Otto Cynthia M. 
Published: November 2023

AbstractObjectiveThis retrospective study aimed to characterize and evaluate the emergency approach, diagnosis, management, treatment, and follow‐up of nonspecific canine lameness cases.DesignRetrospective case series from September 25, 2013 to September 25, 2014.SettingThe study was conducted at an urban university teaching hospital.AnimalsA consecutive sample of dogs presenting to the emergency service with nonspecific lameness in the designated timeframe was used to identify 134 cases. Owners were contacted to participate in the follow‐up survey; dogs that died prior to data collection were excluded from the survey. Medical records were reviewed for lameness localization, etiology of lameness, diagnostics obtained, medications prescribed, and owner recommendations.InterventionsBased on review of the medical records, the lameness localization, presumptive source of lameness (joint, soft tissue, neurological, or bone), diagnostics obtained, medications prescribed, and owner recommendations were recorded. Survey data included duration of lameness, perceived response to treatment, and activity level.Measurements and Main ResultsDefinitive diagnoses were not assigned in 88.8% of lameness cases. A presumptive diagnosis of soft tissue injury was assigned in 45.3% of cases. Single limb lameness was more prevalent than multiple limb lameness. Owners whose dogs were treated with medication were significantly more likely to report that the lameness resolved (P = 0.049). Dogs with injury localized to ≥1 of the joints were significantly less likely to have resolution of lameness (P = 0.037). Treatment recommendations were predominantly pain control and activity restriction.ConclusionsNonspecific lameness represents approximately 4% of canine urban emergency cases. Highlighting the points of clinical care considerations in understanding the etiology of lameness in dogs represents an opportunity for improved patient care and growth in emergency referral and follow‐up.
Regional associations between inspiratory tongue dilatory movement and genioglossus activity during wakefulness in people with obstructive sleep apnoea
Authors: Jugé Lauriane , Liao Angela , Yeung Jade , Knapman Fiona L. , Bull Christopher , Burke Peter G.R. , Brown Elizabeth C. , Gandevia Simon C. , Eckert Danny J. , Butler Jane E. , Bilston Lynne E. 
Published: November 2023

AbstractInspiratory tongue dilatory movement is believed to be mediated via changes in neural drive to genioglossus. However, this has not been studied during quiet breathing in humans. Therefore, this study investigated this relationship and its potential role in obstructive sleep apnoea (OSA). During awake supine quiet nasal breathing, inspiratory tongue dilatory movement, quantified with tagged magnetic resonance imaging, and inspiratory phasic genioglossus EMG normalised to maximum EMG were measured in nine controls [apnoea–hypopnea index (AHI) ≤5 events/h] and 37 people with untreated OSA (AHI >5 events/h). Measurements were obtained for 156 neuromuscular compartments (85%). Analysis was adjusted for nadir epiglottic pressure during inspiration. Only for 106 compartments (68%) was a larger anterior (dilatory) movement associated with a higher phasic EMG [mixed linear regression, beta = 0.089, 95% CI [0.000, 0.178], t(99) = 1.995, P = 0.049, hereafter EMG↗/mvt↗]. For the remaining 50 (32%) compartments, a larger dilatory movement was associated with a lower phasic EMG [mixed linear regression, beta = −0.123, 95% CI [−0.224, −0.022], t(43) = −2.458, P = 0.018, hereafter EMG↘/mvt↗]. OSA participants had a higher odds of having at least one decoupled EMG↘/mvt↗ compartment (binary logistic regression, odds ratio [95% CI]: 7.53 [1.19, 47.47] (P = 0.032). Dilatory tongue movement was minimal (>1 mm) in nearly all participants with only EMG↗/mvt↗ compartments (86%, 18/21). These results demonstrate that upper airway dilatory mechanics cannot be predicted from genioglossus EMG, particularly in people with OSA. Tongue movement associated with minimal genioglossus activity suggests co‐activation of other airway dilator muscles.
imageKey points
Inspiratory tongue movement is thought to be mediated through changes in genioglossus activity. However, it is unknown if this relationship is altered by obstructive sleep apnoea (OSA).
During awake supine quiet nasal breathing, inspiratory tongue movement, quantified with tagged magnetic resonance imaging (MRI), and inspiratory phasic genioglossus EMG normalised to maximum EMG were measured in four tongue compartments of people with and without OSA.
Larger tongue anterior (dilatory) movement was associated with higher phasic genioglossus EMG for 68% of compartments.
OSA participants had an ∼7‐times higher odds of having at least one compartment for which a larger anterior tongue movement was not associated with a higher phasic EMG than controls. Therefore, higher genioglossus phasic EMG does not consistently translate into tongue dilatory movement, particularly in people with OSA.
Large dilatory tongue movements can occur despite minimal genioglossus inspiratory activity, suggesting co‐activation of other pharyngeal muscles.
Journey Mapping the Virtual Design Thinking Experience: Engaging Students Across Disciplines in Human-Centered Design
Authors: Moore George , Rao Vivek , Goucher-Lambert Kosa , Agogino Alice 
Published: November 2023

Abstract
Practitioners’ and students’ experiences while engaging in design thinking and human-centered design activities is well understood to shape outcomes of those activities. However, an understanding of the trajectory of experiences that characterizes the design thinking process, and relates experiences to outcomes, is still emerging. To contribute to this knowledge area, we examine six student teams engaged in a project-based learning course, and seek to understand each participant and team’s experiences with the design thinking process across each design phase, through discrete assessments, and holistically, through reflections on the entire process: what we term journey mapping the students’ experiences. This approach reveals two preliminary findings about the trajectory of novices participating in design thinking work. First, we note that the beginning, research-oriented phases of the design thinking process appear to offer a less positive experience than later phases. Second, we note that students of engineering and non-engineering backgrounds have differing retrospective reflections on their design thinking experiences. These findings suggest that deeper engagement with particular design thinking phases, and an awareness of disciplinary experience, can positively shape the experiences of design thinking practitioners. Also, these results suggest that the significant factors impressing upon a participant’s design thinking experience may change throughout the process.
Assessing Learning of Manual Assembly Processes Using Wrist-Worn Inertial Measurement Units
Authors: Renu Rahul Sharan , Johnson Kirk , Smith Nathaniel , Dawkins Jerel , Righter James 
Published: November 2023

Abstract
The objective of the research presented here is to study the use of Inertial Measurement Units to assess how consistently a person performs a manual assembly process. In conjunction with this objective, the research also explores the use of two novel metrics to plot learning curves — cycle-to-cycle consistency, and consistency with average.
These new metrics allow for insight into the progress a person is making while learning how to perform an assembly process. This is a deeper level of insight than the prevalent approach of using cycle times as a metric to plot learning curves. Experiments are conducted where three co-authors performed the assembly of two products fifteen times each. They wore IMUs on both wrists which allowed the difference in consistency between dominant and non-dominant hand to be analyzed.
Pearson Correlation Coefficient between the consistency-based learning curves and the cycle time-based learning curves were computed. It was found that these learning curves are weakly correlated, thus indicating the need for both to be considered individually while evaluating whether a trainee is ready for a live assembly line or not.
This research needs to be strengthened by performing experimental tests where the participants are not related to the study, by collecting more cycles of data for a larger variety of products, and by including a metric of correctness. This is needed to ensure that people perform the correct process consistently.
Design and User Experience Evaluation of 3D Product Information in XR Shopping Application
Authors: Qin Kaitong , Zhen Yankun , Dong Tianshu , Chen Liuqing , Zhang Ting , Zhang Yumou , Zhou Tingting 
Published: November 2023

Abstract
Current 3D product information pages are believed to enrich the online shopping experience since it provides a more immersive experience. However, existing solutions still retain the 2D UI elements in the product information design, preventing users from fully immersing themselves in the virtual environment and further degrading the shopping experience. Therefore, how to redesign the presentation of product information in a virtual environment is an essential challenge. In this work, we first construct a design space based on previous design cases of product information design in virtual environments, which contains three dimensions: visual presentation, user interaction and spatial relation. Then nine new 3D information design solutions are produced by combining elements in the design space. After that, we devised a user study to compare these solutions and investigate how different dimensions affect users’ shopping experience and task efficiency of the primary objective in shopping. The results reveal that users’ spatial memory and task efficiency are both impacted by how information is organized in terms of visual presentation dimension, and that users’ hedonic experiences are influenced by the differences in the constituent elements of information. It is found that the different spatial relationship between 3D information and 3D product lead to differences in pragmatic quality.
Detection of Singularities in Finite Element Simulations: A 3D Deep Learning Approach
Authors: Bickel Sebastian , Goetz Stefan , Wartzack Sandro 
Published: November 2023

Abstract
The growing digitalization trend has a great influence and impact on the entire product development domain. The new algorithms and methods transform and improve many established processes and workflows. In addition to converting existing know-how into the new processes, available data can also be used to implement various models to enhance the development process. At the same time, the lack of experienced engineers leads to an increasing number of novice engineers from the field of 3D design, who have to perform tasks from the simulation department. Therefore, support for these less experienced users of product development software through newly available methods from the field of data-driven methods is reasonable. Correspondingly, the goal of this paper is to present a method for singularity detection in Finite Element (FE) simulations that detects the presence of a singularity in a computed simulation with the help of Deep Learning. For this purpose, a dataset of calculated simulations with several components with and without singularities is first generated. Then, a new approach based on PointNet and labeled datasets of FE simulations is proposed. Afterwards, the new procedure is compared against a classic Machine Learning approach, whereby different parameter settings were investigated for both approaches.
Thinking Beyond the Default User: The Impact of Gender and Stereotypes on Designers’ Interpretation of Users and Their Needs
Authors: Schauer Anastasia M. K. , Nunn Margaret , Schaufel Hunter , Fu Katherine 
Published: November 2023

Abstract
Throughout the mechanical design process, designers, the majority of whom are men, often fail to consider the needs of women, resulting in consequences ranging from inconvenience to increase risk of death or serious injury. Although these biases are well-studied in other fields of research, the mechanical design field lacks formal investigation into this phenomenon. In this study, undergraduate engineering students (n = 151) took a survey in which they read a Persona describing a student makerspace employee and a Walkthrough describing their interaction with the makerspace while completing a project. During the Walkthrough, the user encountered various obstacles, or Pain Points. Participants were asked to recall and evaluate the Pain Points that the user encountered, then evaluated their perceptions of the makerspace and user. Six different experimental conditions were used to investigate the impact of gender-stereotyped tasks and the gender of a user on designers’ interpretation of them and their needs. In addition to finding that the gender of a user impacted the way a task environment was perceived, results confirmed the presence of androcentrism, or “default man” assumptions, in the way designers view end users of unknown gender. Future work will explore methodologies of overcoming this bias so that designers are able to consider the diverse needs of a range of users.
Case Study: Rapid Design Process for a High-Velocity and Accurate Linear Stage in an Optomechanical Device
Authors: Kresie Scott W. 
Published: November 2023

Abstract
This paper showcases how the design process execution in a challenging environment where cost, time, and COVID-19 induced supply chain factors are significant considerations. The design process was executed in six phases: defining SMART (specific, measurable, attainable, relevant, time-bound) requirements, concept development, concept selection, risk reduction prototyping, final design, and verification testing. Defining SMART requirements is critical to quickly define the design scope which allows for a time-efficient and targeted approach during the subsequent phases. Positional accuracy and speed requirements were the most critical functional requirements. Next, we engaged in a concept development phase, which involved exploring existing designs and novel concepts, with input from subject matter experts familiar with the design space. Two concepts emerged as reasonable approaches: a direct-drive linear motor-based design and a lead-screw based design which were initially developed in parallel. To narrow down the design space, a concept selection phase was used to analyze the advantages and disadvantages of each concept, factoring in the weighted relative importance of each design requirement. The linear motor-based design was determined to best fit the design requirements and proceeded into risk reduction prototyping. Risk reduction prototyping involves design and creation of limited prototypes to learn the key limitations of a design with respect to the requirements, and iterate the deficient qualities in a short feedback loop. By leveraging readily available components a stage assembly representative of the final design was constructed and demonstrated that critical design requirements could be met. The final design was created and fabricated followed by verification testing to ensure the final stage design met the SMART requirements defined in the outset.
Data-Driven Multifidelity Topology Design With a Latent Crossover Operation
Authors: Kii Taisei , Yaji Kentaro , Fujita Kikuo , Sha Zhenghui , Seepersad Carolyn C. 
Published: November 2023

Abstract
Topology optimization is one of the most flexible structural optimization methodologies. However, in exchange for its high degree of design freedom, typical topology optimization cannot avoid multimodality, where multiple local optima exist. This study focuses on developing a gradient-free topology optimization framework to avoid being trapped in bad local optima. Its core is a data-driven multifidelity topology design (MFTD) method, in which design candidates generated by solving low-fidelity topology optimization problems are updated based on evolutionary algorithms (EAs) through high-fidelity evaluation. The key component of the data-driven MFTD is a deep generative model that compresses the dimension of the original data into a low-dimensional manifold, i.e., the latent space. In the original framework, convergence variability and premature convergence problems arise as the generative process is performed randomly in the latent space. Inspired by a popular crossover operation, we propose a data-driven MFTD framework incorporating a new crossover operation called latent crossover. We apply the proposed method to a maximum stress minimization problem in 2D structural mechanics. The results demonstrate that the latent crossover improves convergence stability compared to the original method. Furthermore, the optimized designs exhibit performance comparable to or better than that in conventional gradient-based topology optimization using the P-norm measure.
Multi-Material Topology Optimization Considering the Bounding Box Dimension Constraint and Assemblability Based on the Extended Level Set Method in Two Dimensions
Authors: Feng Yukun , Noguchi Yuki , Yamada Takayuki 
Published: November 2023

Abstract
This paper proposes a multi-material topology optimization method considering the bounding box dimension constraint and assemblability of the optimized structures in two dimensions. To handle multi-material topology optimization problems, we first introduce the concept of the extended level set method and the topological derivative. Second, we introduce the dimensional constraint of the two-dimensional bounding box and the assembly constraint for assemblability of the multi-material structure. We also elaborate their mathematical models. We then compute the design sensitivities of the two constraints based on the topological derivative and adjoint method. Third, we formulate the problem of multi-material topology optimization with constraints and explain the algorithm flow based on the finite element method. Finally, we verify our proposed algorithm on two numerical examples in two dimensions. The proposed method with two-dimensional geometry constraints on the optimized structures is applicable to machining methods. A representative application is milling, in which the largest and second-largest dimensions of the work-pieces are limited by the working area of the milling machine. In addition, our method is helpful for the assembly structure composed of multiple components. Traditional topology optimization method does not consider the assemblability, which makes the structure difficult to be assembled and decomposed in practical engineering. Our work will assist the manufacturability and assemblability of topology-optimized multi-material structures.
Evaluating the Dynamics of Designers’ Moods Throughout the Collaborative Design Process
Authors: Harris Megan , Toh Christine 
Published: November 2023

Abstract
In this paper, we use sentiment analysis to understand the change in moods of individual designers and teams throughout a collaborative design project. Although there is much research on design psychology, the impact of psychological and emotional characteristics on creativity, and group affective tone, there is limited longitudinal research on the dynamic nature of mood and affective tone over the course of a design project. This limited knowledge leaves a gap in our understanding of how the complex emotional states and interactions among team members affects the ability of the team to work together effectively, and ultimately, achieve expected design outcomes. Research that fills this gap can help improve design outcomes and educational strategies. Thus, a longitudinal study was conducted on student design teams using self-reflections collected from three different points over the course of a semester-long design project, in order to understand changes in designers’ moods during a collaborative project. Our results show that time was a significant predictor of change in moods amongst teams, but not necessarily for individuals. These results highlight the complex relationship between individual and team moods during different phases of the design process and provide a foundation for future systematic investigations of team-based affect on design outcomes.
Design and Evaluation of an Automatic Scheduling-Manual Operation Tool to Bring Precision Irrigation to Resource-Constrained Farmers
Authors: Van de Zande Georgia D. , Sheline Carolyn , Amrose Susan , Costello Jeffrey , Ghodgaonkar Aditya , Grant Fiona , Winter Amos G. 
Published: November 2023

Abstract
As populations increase and freshwater supplies decrease, adopting water- and energy-efficient irrigation practices is crucial, particularly in resource-constrained regions. Here, farmers are often unable to purchase the equipment used in precision irrigation, a practice that implements the automatic scheduling of irrigation events to achieve high efficiency. Currently, no irrigation methods exist that combine the automatic scheduling of irrigation events with the manual operation of valves, a common practice on low-income farms. This work introduces a design concept for an automatic scheduling and manual operation (AS-MO) tool that addresses the efficiency needs of resource-constrained farms and integrates into current manual practices. However, it is unknown how farmers would value such a tool. Through interviews and focus groups facilitated by a series of storyboards and a physical prototype, the proposed concept was evaluated by farmers and key market stakeholders in Kenya, Jordan, and Morocco. Results showed that farmers in Kenya and Jordan in particular valued the proposed AS-MO concept because they want increased efficiency on their farms but did not want to install automatic valves for cost and complexity concerns. A possible market was also found in Morocco, but a majority of interviewed farms preferred automatic valve operation due to large farm sizes. Interviewees provided feedback on how to improve the tool’s design in future iterations. If adopted at scale, this AS-MO tool could increase efficiency on farms that otherwise cannot afford current precision irrigation technology, improving sustainable agriculture worldwide.
Semi-Supervised Autoencoder With Joint Loss Learning for Bearing Fault Detection
Authors: Zhou Kai , Zhang Yang , Tang Jiong 
Published: November 2023

Abstract
Timely and accurate bearing fault detection plays an important role in various industries. Data-driven deep learning methods have recently become a prevailing approach for bearing fault detection. Despite the success of deep learning, fault diagnosis performance is hinged upon the size of labeled data, the acquisition of which oftentimes is expensive in actual practice. Unlabeled data, on the other hand, are inexpensive. To fully utilize a large amount of unlabeled data together with limited labeled data to enhance fault detection performance, in this research, we develop a semi-supervised learning method built upon the autoencoder. In this method, a joint loss is established to account for the effects of both the labeled and unlabeled data, which is subsequently used to direct the backpropagation training. Systematic case studies using the Case Western Reserve University (CWRU) rolling bearing dataset are carried out, in which the effectiveness of this new method is verified by comparing it with other benchmark models.