bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Youth‐Centered Health Messaging Posters for High School‐Based Health Clinics in Hawaii
Authors: McKay Elizabeth A. , Mattheus Deborah , Garney Whitney R. , Wilson Kelly L. , Fontenot Holly B.
Published: November 2023

BACKGROUND

Youth may be reluctant to seek health care from school health providers due to feeling embarrassed or stigmatized in the health office environment or worried about their confidentiality. The purpose of this project was to create a set of youth‐centered health posters that promote youth engagement with nursing staff and to standardize health messaging across high schools in Hawaii school‐based clinics.

METHODS

Two community advisory boards, 1 composed of 10 youth stakeholders (mean age 17 years) and the other of 7 adult stakeholders, informed poster development utilizing web‐based discussion groups. The discussions were transcribed, and additional data was collected using field notes and anonymous digital messages. Adult advisory board members also provided feedback on suggested poster text through an online survey.

RESULTS

Youth and adult advisory board participants identified 4 key health concerns facing youth: confidentiality, sexual health, relationships, and mental health. Based on input from the 2 advisory boards, 4 posters were developed, each centered on 1 key health issue.

IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY

School‐based posters can convey important messages to help youth understand their health care rights and responsibilities, as well as identify important issues open for discussion with nurses.

CONCLUSION

Posters are an underutilized tool for school health providers to create welcoming, inclusive health care environments and facilitate health‐related conversations with youth. This paper describes participant feedback about the characteristics of a memorable poster and briefly outlines current knowledge and recommendations for school health providers regarding each of the 4 health issues.
A review on stringiness property of cheese and the measuring technique
Authors: Lim Qai‐Yeing , Cheng Lai‐Hoong
Published: November 2023

This review paper provides a deep understanding of stringiness property in a cheese product. Stringiness is used to describe the extended continuous strand of a molten cheese, especially mozzarella cheese. Stringiness is often described quantitatively by stretch length, as well as qualitative definition which focuses on the dimension of strand and ease of extensibility. Very often, the scope of defining stringiness attributes is limited by the measuring techniques because a complete experimental setup is required to obtain information on both stretch quantity and stretch quality. Among the measuring methods, cheese extensibility rig stands out to be the best method to assess stringiness attribute of a cheese as it is an objective method. In addition, a detailed study on the molecular behavior and interactions among natural and imitation cheese components in delivering stringiness, and the challenges faced therein have been reviewed. Thus, the review provides a foundation for the development of vegan cheese or plant‐based cheese with stringiness properties.
Effect of dietary β‐glucan supplementation on growth performance, body composition, intestinal microbes, and capacity against pathogen of golden trevally (Gnathanodon speciosus, family Carangidae)
Authors: Do‐Huu Hoang , Huynh Sang Minh , Nguyen Hue Thi Nguyet , Pham Ky Xuan
Published: November 2023

The efficacy of dietary β‐glucan supplementation in golden trevally (Gnathanodon speciosus) was evaluated. The fish were fed five different diets supplemented with 0%, 0.05%, 0.10%, 0.20%, and 0.40% β‐glucan for 56 days. After 56 days of culture, survival was the highest when the fish were fed a 0.10% β‐glucan diet. Growth rates were higher in fish fed diets supplemented with all β‐glucan levels. Lymphocytes increased when the fish were fed a diet supplemented with 0.05% β‐glucan, and thrombocytes increased when the fish were fed 0.2% and 0.4% β‐glucan‐supplemented diets. The total aerobic bacteria count in the gut of golden trevally was higher (p < 0.05) and the total Vibrio counts in the gut of golden trevally were lower (p < 0.05) when the fish were fed any level of β‐glucan. Flesh protein content was higher and flesh lipid content was lower when fish were fed β‐glucan‐supplemented diets at levels greater than 0.1%. When challenged with Streptococcus iniae, fish fed diets containing 0.10% or 0.20% β‐glucan exhibited the highest survival rates. The current results suggest that supplementation with 0.05 to 0.2% β‐glucan in the diet would be beneficial for the culture of the golden trevally.
Structural equation modeling of factors associated with nursing students' professionalism during the COVID‐19 pandemic
Authors: Jang So‐Eun , Lee Yun Mi , Son Youn‐Jung
Published: November 2023

This study aimed to determine the factors associated with nursing professionalism among Korean nursing students. This cross‐sectional study was carried out using a convenient sample comprising 247 students enrolled in a four‐year Bachelor of Science Nursing program from September 6–27, 2021. A self‐reported structured questionnaire was employed to explore the relationships among ego‐resilience, self‐leadership, clinical learning environment, academic satisfaction, clinical competency, and nursing professionalism by utilizing structural equation modeling. The modified model exhibited good fit indices. Learning‐related factors, including clinical learning environments, academic satisfaction, and clinical competency, directly affected nursing professionalism. Self‐leadership and the clinical learning environment were indirectly associated with nursing professionalism via both academic satisfaction and clinical competency. Regarding ego‐resilience, it only indirectly affected nursing professionalism via academic satisfaction. Creating a student‐centered learning environment may be vital to improve students' major and clinical performance, thereby boosting nursing professionalism. Furthermore, nurse educators should consider individual psychological aspects of students when designing the nursing curriculum to foster nursing professionalism. Longitudinal studies are needed to determine if our model is available to explain the development of professionalism among nursing students.
Rapid mini‐chromosome divergence among fungal isolates causing wheat blast outbreaks in Bangladesh and Zambia
Authors: Liu Sanzhen , Lin Guifang , Ramachandran Sowmya R. , Daza Lidia Calderon , Cruppe Giovana , Tembo Batiseba , Singh Pawan Kumar , Cook David , Pedley Kerry F. , Valent Barbara
Published: November 2023

The fungal pathogen, Magnaporthe oryzae Triticum pathotype, causing wheat blast disease was first identified in South America and recently spread across continents to South Asia and Africa. Here, we studied the genetic relationship among isolates found on the three continents.

Magnaporthe oryzae strains closely related to a South American field isolate B71 were found to have caused the wheat blast outbreaks in South Asia and Africa. Genomic variation among isolates from the three continents was examined using an improved B71 reference genome and whole‐genome sequences.

We found strong evidence to support that the outbreaks in Bangladesh and Zambia were caused by the introductions of genetically separated isolates, although they were all close to B71 and, therefore, collectively referred to as the B71 branch. In addition, B71 branch strains carried at least one supernumerary mini‐chromosome. Genome assembly of a Zambian strain revealed that its mini‐chromosome was similar to the B71 mini‐chromosome but with a high level of structural variation.

Our findings show that while core genomes of the multiple introductions are highly similar, the mini‐chromosomes have undergone marked diversification. The maintenance of the mini‐chromosome and rapid genomic changes suggest the mini‐chromosomes may serve important virulence or niche adaptation roles under diverse environmental conditions.
A novel UVA‐associated circUBE2I mediates ferroptosis in HaCaT cells
Authors: Yi Peng , Huang Yan , Zhao Xin , Qin Zhengshan , Zhu Danli , Liu Li , Zheng Yuxi , Feng Jianguo , Long Menghong
Published: November 2023

Alternative splicing of precursor messenger RNA (pre‐mRNA), including linear splicing and back splicing, produces multiple isoforms that lead to diverse cell fates in response to stimuli including ultraviolet radiation (UVR). Although UVR‐induced linear gene splicing has been extensively studied in skin cells, the UVR‐induced gene back‐splicing events that lead to the production of circular RNAs (circRNAs) have not been thoroughly investigated. The present study used circRNA transcriptome sequencing to screen the differentially expressed circRNAs in human keratinocytes (HaCaT) after UVA irradiation. A total of 312 differentially expressed circRNAs were found in HaCaT cells post‐UVR. Among the UVA‐induced differentially expressed circRNAs, circUBE2I—a novel circRNA formed by exons 2–6 of the UBE2I gene—was the most significantly upregulated circRNA. RT–qPCR assay further confirmed the increase of circUBE2I level in HaCaT cells after UVA irradiation or H2O2 treatment. RNase R digestion experiment revealed the stability of circUBE2I. Overexpression of circUBE2I in keratinocytes induced ferroptosis after UVA or H2O2, preventable by the ferroptosis inhibitor ferrostatin‐1. Our study provides new insights into the role of circular RNAs in UVA‐induced skin cell damage and suggests that circUBE2I could be a therapeutic target in UVR‐aroused ferroptosis in skin cells.
Are there really any dual‐character concepts?
Authors: Phillips Jonathan , Plunkett David
Published: November 2023

There has been growing excitement in recent years about “dual‐character” concepts. Philosophers have argued that such concepts can help us make progress on a range of philosophical issues, from aesthetics to law to metaphysics. Dual‐character concepts are thought to have a distinctive internal structure, which relates a set of descriptive features to an abstract value, and which allows people to use either the descriptive features or the abstract value for determining the extension of the concept. Here, we skeptically investigate the central argument in favor of their existence. Across three new empirical studies, we systematically demonstrate that the linguistic patterns that dual‐character concepts were originally posited to explain are likely better explained by much more general features of language use.
Influence of arbuscular mycorrhizal fungi density on growth and metabolism of Handroanthus serratifolius (Vahl) S.O. Grose seedlings
Authors: da Sousa Ludyanne da Silva , Correia Tatiane Santos , dos Farias Frank dos Santos , Santana Marcos Diones Ferreira , Lara Túlio Silva
Published: November 2023

Studies on the relationship between Handroanthus serratifolius and arbuscular mycorrhizal fungi (AMF) are limited in the literature. The influence of AMF spore density on plant development is fundamental information to determining the degree of benefits in this relationship. Therefore, the objective of this study was to investigate the effects of different AMF spore densities on thirty‐day‐old H. serratifolius seedlings, focusing on growth and biochemical parameters using a completely randomized experimental design with three different spore densities and control. The spore densities were classified as low, medium, and high, with 1.54, 3.08, and 12.35 spores g−1, respectively. Plant growth analysis, mycorrhizal colonization, nitrogen compound concentration, and carbohydrate analysis were performed. The medium spore density treatment showed the greatest increases in biomass, height, leaf area, and root volume. Furthermore, greater absorption of phosphorus and better dynamics in nitrogen metabolism were observed in mycorrhizal plants compared to the control since the ammonium and nitrate compounds were rapidly incorporated into protein and chlorophyll compounds. The carbohydrate analysis revealed the influence of source‐sink dynamics on sugar concentration in different plant parts. These findings support the importance of determining the appropriate spore density for assessing the symbiotic relationship between forest species and AMF.
Adaptive social protection in Indonesia: Stress‐testing the effect of a natural disaster on poverty and vulnerability
Authors: Gasior Katrin , Wright Gemma , Barnes Helen , Noble Michael
Published: November 2023

Indonesia is among the countries with the highest exposure to natural disasters, and risks are expected to increase due to climate change. Natural disasters and other shocks require well‐developed social protection systems that can cushion the economic consequences for those most vulnerable to these events. International stakeholders advocate for ‘Adaptive Social Protection’ which links social policy with strategies on disaster risk reduction and climate change adaptation. This article uses the tax‐benefit microsimulation model INDOMOD to analyse the adaptiveness of the Indonesian social protection system by simulating an income shock caused by a natural disaster and testing reforms to the existing social protection system. We find that the existing system generally performs well in lifting people out of poverty in normal times but does not sufficiently help them to prepare for and cope with shocks. This is especially the case for large households, households with more than two children, people in their 20s and 80s and individuals with a disability. The tested hypothetical reforms reduce the impact of the shock and better target those identified as needing more support but require a substantial increase in social spending.
Oral administration of hyaluronic acid to improve skin conditions via a randomized double‐blind clinical test
Authors: Gao Yan‐Rui , Wang Rui‐Ping , Zhang Lu , Fan Yuan , Luan Jin , Liu Zhe , Yuan Chao
Published: November 2023

Objective

To evaluate the impact of oral intake of Hyaluronic Acid (HA) on skin health.

Background

HA, an endogenous substance in the human body, plays a key role in skin health. However, its concentration in the skin decreases significantly with age. Previous studies suggested that oral intake of HA can supplement the body's HA level, but did not reveal the effects on different age groups and skin types.

Methods

A double‐blind, randomized clinical trial with 129 female participants, covering young and elderly groups and differnet skin types, was conducted to assess the efficacy of orally administered HA on skin health.

Results

Oral administration of HA significantly promoted skin hydration after 2‐8 weeks among both young and elderly groups. Skin tone improvement was observed after 4‐8 weeks, while an increase in epidermal thickness was noted after 12 weeks.

Conclusion

This study provides direct evidence supporting the clinical efficacy of oral intake of HA in promoting skin health.
An Overview of Wastewater Treatment and Reuse in The Gulf Cooperation Council Countries
Authors: Saleem Haleema , Mohammad Khan Maryam , Alkaabi Moza , Boudjema Noura , Alshowaikh Fatema , Javaid Zaidi Syed
Published: November 2023

The human population generates a substantial amount of waste, and if it is discarded without any treatment it can lead to environmental degradation. This is commonly executed by discharging substantial amount of untreated wastewater in the waterways. Wastewater can be generated from numerous locations but for this review the principal areas concerned are municipalities and industries. The focus of the current study relies on performing a thorough review on expressing the benefits of treating wastewater, assessing Gulf Cooperation Council (GCC) reuse regulations associated with wastewater reuse, identifying different wastewater treatment technologies, and evaluating previous research implemented on this field across the GCC region. Various case studies about treatment technologies and reuse regulations are analyzed in this review for each country within the GCC. The findings show that treating wastewater holds many benefits such as reducing environmental pollution and can aid in helping nations with limited access to fresh water to meet their demand. The technologies for treating wastewater are discussed, such as: conventional filtration, chemical, biological treatment, and different membrane technologies. The review conveys that although treating water has many benefits, there are still many challenges associated with the cost, public perception, and management policies that need to be resolved. To improve wastewater treatment policies effective management can show greater potential for mitigating the freshwater shortage in the GCC countries. Also, since each GCC country has different policies regarding wastewater management, more research should be conducted in the future to adapt as the GCC territory is competing to produce new wastewater treatment plants to accommodate their growing demand for fresh water.
An Underactuated Cable-Driven Parallel Robot for Marine Automated Launch and Recovery Operations
Authors: Angelini Michele , Ida' Edoardo , Bertin Daniele , Carricato Marco , Mantovani Enrico , Bazzi Davide , Orassi Vincenzo
Published: November 2023

This paper presents the feasibility study and preliminary testing of an underactuated cable-driven parallel robot for automated launch and recovery operations on the sea surface. The robot frame is mounted onto a primary vessel (PV) subject to sea-induced motions. During launch, the end-effector (EE) is required to deploy a secondary vessel (SV) by lowering it from the PV onto the sea surface. During recovery, the EE has to track and grasp a SV and the EE-SV assembly needs to be stabilized during lifting from the sea surface to the PV. Sea conditions and the underactuated nature of the EE influence the operational feasibility and the overall robot performance. The paper presents the conceptual design and the robot model, as well as the methodologies for winch dimensioning and robot control. An extensive simulation campaign is conducted to optimize performances and assess the system’s behavior.
Methods for Creating Additive Printing Paths on Nonplanar Surfaces
Authors: Rudd Liam , Faghihrasoul Zahra , Campbell Matthew I.
Published: November 2023

One of the ways that additive manufacturing technology continues to improve is the addition of a fourth or fifth degree-of-freedom. Adding rotational axes to the printer head or to the print bed can lead to improvement in the time, cost of printing as well as the quality of the print. We have witnessed similar improvements in subtractive CNC machining as well. The added axes require new computational methods to automatically define toolpaths. In additive, slicer software creates planar cross-sections through the part and automatically defines these toolpaths. With added rotational axes, toolpaths on nonplanar surfaces will be required to fully utilize the advantages of multi-axis printing. This paper reviews current work in nonplanar toolpaths and introduces three new concepts that advance the field. These three concepts are presented in three separate sections — each with their own related work and results. Firstly, we present methods for projecting or unwrapping a nonplanar surface to 2D polygons so that paths can be defined by conventional means. Then, the paths are projected or wrapped back onto the 3D surfaces. Next, two approaches are presented for creating perimeter paths and infill paths that do not transform the slices to 2D planes. These iterative methods simulate the toolpath as particles reacting to virtual forces that guide them to ideal positions. The third builds on an algorithm for creating biologically inspired undulating paths or membranes called differential line growth. These methods can be useful in defining paths for surfaces with high curvature since converting to 2D and back would likely produce too much distortion and paths would not maintain near-equal geodesic distances.
Build Orientation Optimization for Five-Axis 3D Printing
Authors: Alonayni Ghazi , Campbell Matthew I.
Published: November 2023

It is well understood that printing orientation plays a critical role in the quality of a final printed product and the total print time. In five-axis 3D printers, the added rotations can further reduce time and material, but initial orientation is still a significant factor. The build orientation is a critical factor in the printed part’s surface quality and the need for additional material as support structures. In this research, we develop build orientation sampling techniques and evaluate them based on their computational cost and accuracy. The evaluation of a build orientation is based on three criteria: the volume of the added support structure, the surface quality, and the stability of the part while rotating and tilting on the printing platform. The creation of the support structure uses Boolean polygon operations to compute the amount of material required as support. The surface quality and stability of a part at a given orientation are also calculated. Our proposed optimization scheme was tested on seven 3D parts and was found to only require a small number of evaluations to achieve a Pareto-optimal set of build orientations. This method can be utilized as a first step in planning the fabrication of parts printed on five-axis printers.
How Does Agency Impact Human-AI Collaborative Design Space Exploration? A Case Study on Ship Design With Deep Generative Models
Authors: Khan Shahroz , Kaklis Panagiotis , Goucher-Lambert Kosa
Published: November 2023

Typical parametric approaches restrict the exploration of diverse designs by generating variations based on a baseline design. In contrast, generative models provide a solution by leveraging existing designs to create compact yet diverse generative design spaces (GDSs). However, the effectiveness of current exploration methods in complex GDSs, especially in ship hull design, remains unclear. To that end, we first construct a GDS using a generative adversarial network, trained on 52,591 designs of various ship types. Next, we constructed three modes of exploration, random (REM), semi-automated (SAEM) and automated (AEM), with varying levels of user involvement to explore GDS for novel and optimised designs. In REM, users manually explore the GDS based on intuition. In SAEM, both the users and optimiser drive the exploration. The optimiser focuses on exploring a diverse set of optimised designs, while the user directs the exploration towards their design preference. AEM uses an optimiser to search for the global optimum based on design performance. Our results revealed that REM generates the most diverse designs, followed by SAEM and AEM. However, the SAEM and AEM produce better-performing designs. Specifically, SAEM is the most effective in exploring designs with a high trade-off between novelty and performance. In conclusion, our study highlights the need for innovative exploration approaches to fully harness the potential of GDS in design optimisation.
An Improved Shape Annealing Algorithm for the Generation of Coated DNA Origami Nanostructures
Authors: Babatunde Bolutito , Cagan Jonathan , Taylor Rebecca E.
Published: November 2023

In recent years, the field of structural DNA nanotechnology has advanced rapidly due to transformative design tools. Although these tools have been revolutionary, they still bear one overall limitation of requiring users to fully conceptualize their designs before designing. Recently, a simple computational casting technique was developed using generative optimization strategies to automate the design of DNA origami nanostructures. This approach employs a shape annealing algorithm, which creates a formal language of honeycomb DNA origami nanostructures with shape grammars and drives designs from the language towards a desired configuration using simulated annealing. This initial demonstration of the approach can generate novel scaffold routing schemes for creating solid or hollow structures constrained by boundaries of polyhedral meshes. The results from the initial approach, particularly from the hollow structures, reveal a challenging design space. This simple technique generates novel scaffold routing schemes that do not replicate the overall polyhedral mesh shape and is limited in its ability of controlling scaffold path exploration in the design space. This paper demonstrates an approach for varying effective wall thickness and improving quality of polyhedral mesh coverage for hollow structures that can be tuned and optimized by introducing a more refined computational casting technique. We achieve these improvements through changes in the simulated annealing algorithm by adding a Hustin move set algorithm that dynamically adjusts the performance of the overall design and redefining how these hollow designs are articulated. The results in this work illustrate how the shape annealing algorithm can navigate a challenging design space to generate effective hollow designs.
Safe Autonomous Vehicle Cooperative Cruise Control With Deep Reinforcement Learning
Authors: Yang James , Negash Natnael M.
Published: November 2023

Recently, intelligent control approaches through reinforcement learning have achieved robust performance. The practical complication of reinforcement learning in approximating complex functions is resolved through the introduction of deep learning into the framework. We developed such a deep reinforcement learning-based optimal vehicle cruise control. The most commonly used algorithm, deep deterministic policy gradient (DDPG), overestimates Q-functions that can lead to sub-optimal agent policy. We proposed the twin-delayed DDPG (TD3) algorithm, the extension of the DDPG algorithm. We have compared our proposed method with model-based control approaches and non-self-learning as physics-based car-following models to see the effectiveness of the proposed approach. The TD3 agent has achieved a minimum spacing error than MPC and PID. Moreover, the TD3 agent has shown effective tracking performance compared to physics-based models and risk assessments.
Route Based Fuel Savings of Freight Train Hybridization
Authors: Ahuja Nitisha , Martin Jay D. , Yukish Michael A. , Stump Gary M. , Bennett Lorri A. , Schlake Bryan W. , Anstrom Joel R. , Rahn Christopher D.
Published: November 2023

Adding battery locomotives to traditional diesel locomotives to form a hybrid consist has the potential to reduce fuel consumption and emissions in freight rail operations. This paper provides round trip, route-based estimates of diesel (hpd/ton) and battery (hpb/ton) power requirements and diesel (gal/ton) and battery (hpbhr/ton) energy requirements for hybrid consist. Given the route-specific power profile, the power split between the battery pack and the diesel engine is optimized to minimize fuel consumption by running the diesel engine at maximum efficiency during the entire trip. The results from 100-mile out/back routes between Chicago and Harrisburg indicate that the required diesel power for hybrid consist is maximum in low-gradient regions at 1.17 (hpd/ton) and the required battery power is maximum in hilly regions at 2.04 (hpb/ton) for discharge and 9.43 (hpb/ton) for charge. Maximum fuel efficiency gains of approximately 60% are seen in hilly routes, where 2.09 (hpbhr/ton) of battery energy is needed. Minimum fuel economy gains are observed in flat regions, with a 20% fuel consumption reduction. This ideal case analysis of hybrid consist can serve as an easy-to-use tool for the US freight rail sector to estimate fuel savings and sort routes based on the potential results for electrification, without requiring substantial computation.
Improving Change Management by Quantifying the Relationships Between Margins and Design Variable Flexibility
Authors: Jacobson Lindsey , Ferguson Scott
Published: November 2023

Managing system changes is one of the most challenging and important tasks facing today’s engineering designers. Beyond the numerous design revisions that occur during the design process, accelerating rates of technological and societal growth strain existing systems, and those that will produce the greatest value are the systems that can be adapted and evolved. The complexity of modern engineered systems requires that significant resources be invested so that changes can be managed throughout the design and redesign processes. Implementing even relatively small modifications can require extensive design effort in systems with many coupled and entangled relationships. There is significant evidence that design margins can effectively limit change propagation, yet the relationship between margins and change propagation has not been fully studied. In this paper, we take a step toward quantifying how margins create flexibility at a component level in an engineered system. We define a decision variable’s (DV) Complex Flexibility Range (CFR) as the extent by which a variable can change while maintaining feasibility with respect to all requirements and constraints. A high-powered rocket’s recovery system is modeled, and the CFRs are calculated for multiple DVs. We use the quantified CFRs to demonstrate how margins create flexibility at the level of DVs and how changing a decision variable impacts margins and DV flexibility. Several applications for CFRs are identified, including 1) predicting change propagation, 2) identifying change absorbers, 3) communicating changes in margin/flexibility, and 4) negotiating DV selection and requirements definition. This work provides a foundation for further study of how margins can be allocated and for studying how systems can be efficiently, and effectively, adapted and evolved.
A Novel Mass Sensor Incoporating Multiple Internal Resonances in Coupled Resonators Under Electrostatic Actuation
Authors: Sun Rongjian , Zhao Jian , Kacem Najib , Dong Zeyuan , Lyu Ming
Published: November 2023

Nonlinearly coupled vibrations in microelectromechanical sensors have received much attention for their great potential in improving sensor performance. In this paper, a novel mass sensor based on multiple internal resonances of three electrostatically coupled resonators is proposed. The mathematical model of the sensor is established by using Euler-Bernoulli theory, and the dynamic response before and after mass perturbation is solved by using the method of multiple scales, and verified by the harmonic balance method combined with the asymptotic numerical method. The relative shift of the amplitude sum induced by the mass perturbation at the saddle-node bifurcation point is used as the output sensitivity, and the sensitivity is enhanced by three orders of magnitude compared with the relative shift of frequency. Finally, the effect of driving voltage on the sensitivity of the mass sensor is analyzed.
Performance Assessment of Fractional-Order Control of Non-Minimum Phase Power Converter Systems
Authors: Nwoke Justus , Viola Jairo , Chen YangQuan
Published: November 2023

Non-minimum phase (NMP) systems present unique controller design challenges like the reduced stability region or an elevated noise and disturbance sensitivity due to its limited bandwidth caused by the presence of one or more right half plane zeros. In power electronics, architectures like the flyback converter exhibit this behavior, increasing the complexity in designing closed-loop controls for regulation tasks. This work present the assessment of several fractional-order controllers as an alternative for the control of NMP systems in the presence of external disturbances and random noise. In this case, a non-ideal flyback converter in regulation tasks is used as the benchmark system to compare the performance of several fractional-order control methods against its integer-order version in the presence of external disturbances and random noise. The obtained results shows that using fractional-order controllers can improve the power converters transient response and its response against external events.
Model Architecture Exploration Using ChatGPT for Specific Manufacturing Applications
Authors: Villena Toro Javier , Tarkian Mehdi
Published: November 2023

Selecting an appropriate machine learning model architecture for manufacturing tasks requires expertise in both computer science and manufacturing. However, integrating state-of-the-art machine learning models and manufacturing processes is often challenging due to the distance between these fields. OpenAI’s popular language model, ChatGPT, has the potential to bridge this gap.

This paper proposes guidelines and questions to explore model architecture options and extract valuable information from ChatGPT’s natural language processing capabilities. While ChatGPT is a powerful tool, it is important to verify any answers obtained against reliable sources before making any decisions. The guidelines compose a flowchart with four queries to give ChatGPT enough context and exisiting input data information. ChatGPT suggestions will be directed towards input processing, output, and architecture proposals. The last query produces keywords based on the chat for a background study on the topic.

A manufacturing case study was conducted to demonstrate the effectiveness of these guidelines. The study involved creating a model to forecast fixturing locations for welding processes in the automotive sector. After conducting four separate interviews with ChatGPT, the authors discuss the selection of architecture based on ChatGPT suggestions and contrast it with previous literature.

The proposed guidelines are expected to be useful in a variety of manufacturing contexts, as they offer a structured approach to exploring model architecture options using ChatGPT’s capabilities, ultimately leading to new and innovative applications of machine learning in this field.
Adding a Novel Olfactory Dimension to Multisensory Experience in Virtual Reality Training
Authors: Ferrise Francesco , Dozio Nicolò , Spadoni Elena , Rossoni Marco , Carulli Marina , Bordegoni Monica
Published: November 2023

Nowadays, industrial training is gaining popularity, and in particular, Virtual Reality (VR) technologies are often adopted to recreate training experiences that can transform the learning process by exploiting the concept of learning by doing. Moreover, VR allows us to recreate realistic and immersive environments that provide trainees with hands-on experience in a safe and controlled setting. One of the advantages of using VR technologies to perform training simulations lies in the ability that these tools offer to mix different senses as if they were independent variables and to manipulate them one at a time. In this way, the effects of using one sense on the specific task under analysis can be discovered in a controlled scenario in which the others are controlled. One of the least used senses in VR is undoubtedly that of smell. In this paper, we intend to use a new olfactory device specifically designed to be adopted with VR technologies, integrate it with an immersive VR training application, and propose a series of uses allowed by this combination. In the paper, we report the details of the multisensory approach that integrates the different senses. Additionally, the paper presents the findings of a pilot experiment conducted to validate the adopted approach and assess the results. The study demonstrates that the developed Olfactory Display had no adverse impact on users’ interaction with VR content.
Preliminary Concepts for Magnetic Actuation and Stabilization of Origami-Based Arrays
Authors: Pruett Hunter , Coleman Nathan , Magleby Spencer
Published: November 2023

Five genres of magnetic hinge concepts are presented; a simple bistable magnetic hinge, a monostable magnetic hinge from the simple bistable magnetic hinge, a hinge based on diametrically magnetized gears, a hinge composed of pairs of magnets, and a hinge based on the strategic placement of a single pair of cuboid magnets. Particular focus is given to the hinge composed of a single pair of cuboid magnets, as this genre of hinge can be low-profile and used in thin panels, which can yield a greater deployed area given a stowed volume. A framework for the generalization of such a hinge is presented and various design variables are defined. Two novel self-actuating and self-stabilizing hinges (the MaLO and MaLDO hinges) based on this framework are presented. The characterization of these hinges is defined and two key additional offset design variables are presented. The effect on bistability of varying one offset is explored in the MaLDO hinge and a hypothesized relationship for estimating when the hinge will be bistable is presented and discussed. Both hinges are shown in selected applications; the MaLDO hinge is shown implemented in a deployable truss and the MaLO hinge is shown implemented in a Miura-ori-based reflectarray antenna design.
Curvature Analysis of Linear and Circular Tractrices for the Planar Motion of Vehicles
Authors: Lanni Chiara , Figliolini Giorgio , Angeles Jorge
Published: November 2023

The curvature analysis of the linear and circular tractrix curves for the planar motion of vehicles is formulated as based on the application of the classical differential geometry, along with the Bresse and return circles. In particular, a two-wheel (bicycle) model of four wheels vehicles was assumed and the evolutes of the corresponding fixed centrodes, being the related moving centrodes represented by straight lines, are determined, along with the evolutes of the linear and circular tractrix curves.

The proposed formulation has been implemented in Matlab, in order to simulate and analyze the vehicle behavior in terms of curvature, when the front wheel center follows a straight line or a circle. Significant numerical and graphical results allowed the validation of the proposed formulation in different conditions.
Document Understanding-Based Design Support: Language Model Based Design Knowledge Extraction
Authors: Qiu Yunjian , Jin Yan
Published: November 2023

Design knowledge in the vast amount of design reports and documents can be a great resource for designers in their practice. However, capturing such domain-specific information embedded in long-length unstructured texts is always time-consuming and sometimes difficult. Therefore, it is highly desirable for a computer system to automatically extract the main knowledge points and their corresponding inner structures from given documents. In this study of document understanding for design support (DocUDS), a design-perspective knowledge extraction approach is proposed that uses phrase-level domain-specific labeled datasets to finetune a Bidirectional Encoder Representation from Transformers (BERT) model so that it can extract design knowledge from documents. The BERT model finetuning attempts to blend in the domain-specific knowledge of well-recognized domain concepts and is based on the datasets generated from design reports. The model is utilized to map the captured sentences to the main design entities , , and . In addition, this approach uncovers inner relationships among the sentences and constructs overall structures of documents to enhance understanding. The definitions of design perspectives, inter-perspective relations, and intra-perspective relations are introduced, which together capture the main design knowledge points and their relations and constitute an understanding of the design domain knowledge of a text. The case study results have demonstrated the proposed approach’s effectiveness in understanding and extracting relevant design knowledge points.
Control of a Bipedal Walking Using Partial Feedback Linearization and Gaussian Process Regression-Based of the Step-to-Step Map
Authors: Torres Daniel , Hernandez Hinojosa Ernesto , Bhounsule Pranav A.
Published: November 2023

Bipedal robots with small and point feet find it difficult to balance instantaneously due to underactuation, but can be relatively easy to control over the time scale of a step. Thus, models of step-to-step dynamics provide an effective means for the development of step-to-step controllers. Such models are analytically intractable because they are obtained from integrating nonlinear equations of motion. Our hypothesis is that obtaining approximations of such models can be effective for real-time computations of control inputs. We use partial feedback linearization to reduce the system dimensions for the step-to-step map. We formulate and solve an optimal control problem with the approximations to compute control for tracking a reference velocity and walking on stepping stones. These solutions demonstrate the need for bipedal robots to achieve specific control objectives, such as walking speed and foot placement, in order to navigate through restricted environments such as the stepping stones. We provide simulations on a 5-link biped to show the efficacy of the approach. A video link is provided: https://www.youtube.com/watch?v=p2TLU3Jzul8.
Towards High Dynamic Operations With Parallel-Serial Hybrid Robots
Authors: Sagar Keerthi , Ramadoss Vishal , Zoppi Matteo
Published: November 2023

Hybrid manipulators are a combination of parallel and serial linkage connection robots which can exhibit high articulation and achieve modularity in design. This paper presents the results on the kinematic modeling and motion generation of a parallel-serial hybrid robot architecture. Parallel mechanisms are increasingly being employed as a reconfigurable subsystem alongside serial kinematic chains for high speed machining and manufacturing operations. These kinematic structures have known to have superior stiffness and dynamic properties at the expense of increased complexity in modeling and control. For a specific application of placing fixture heads along sheet metal, a hybrid parallel-serial manipulator is developed. It consists of a spherical revolute (SR) 4-degree-of-freedom (DOF) serial arm mounted on a (3-DOF) parallel manipulator with two UPR (4-DOF) legs constrained to move in a common rotating plane, and an SPR (5-DOF) leg. The kinematic architecture utilizes parallel linkage as a positioning manipulator, whereas the serial arm provides the necessary dexterity and increased workspace required for the task. An approach to model such complex kinematic structures with the evaluation of workspace and motion generation is discussed. The presented approach is finally validated both in simulation and with experiments performed on the real platform.
Chat Generative Pretrained Transformer: Extinction of the Designer or Rise of an Augmented Designer
Authors: Gill Amaninder Singh
Published: November 2023

Systematic design process is used in engineering systems design to develop solutions to problems of varying complexity. There have been efforts within the community to develop tools to perform automated generative design at varying stages of the systematic design process. However, a Large Language Model (LLM) has never been used. To this end, this paper presents an initial investigation into the use of OpenAI’s ChatGPT to automatically generate solutions to an engineering problem. It is demonstrated that for the most part ChatGPT is quite capable of generating conceptual design for an engineering problem. In light of this technology, this paper floats questions on the future direction of research and education for the engineering systems design community.
Multi-Task Multi-Fidelity Machine Learning for Reliability-Based Design With Partially Observed Information
Authors: Xu Yanwen , Wu Hao , Liu Zheng , Wang Pingfeng
Published: November 2023

In complex engineering systems, assessing system performance and underlying failure mechanisms with respect to uncertain variables requires repeated testing, which is often limited by test capacity and computational budget and fails to accurately capture the complex system’s high-dimensional nature. A method that can efficiently use information that is partially available from various sources is thus urgently needed for complex system design. This paper presents a multi-fidelity surrogate modeling strategy that efficiently utilizes partially observed information (POI) from various sources, including data with different fidelity and dimensionality. Additionally, in reliability analysis and design optimization tasks, multiple constraints must be evaluated concurrently for each design point. However, as the complexity of systems increases, the number of constraints grows, resulting in a rapid increase in computational effort. Therefore, a multi-fidelity multi-task surrogate modeling framework with POI was proposed to aid in the development of surrogate models, which increases the effectiveness of reliability analysis. The proposed multi-fidelity multi-task machine learning (MFMT-ML) model utilizes a Bayesian framework, which significantly improves the predictive model’s performance and provides uncertainty quantification of the prediction. It also offers premium features such as using multi-fidelity sources of data points and POI, allowing simultaneous evaluation of multiple constraints through a single test, and offering a highly accurate and efficient reliability-based design optimization framework through knowledge sharing. By incorporating partially observed information from various sources, our approach offers a promising avenue for improving system performance prediction accuracy and efficiency while reducing the cost and complexity of complex system design.
Unraveling shared risk factors for diabetic foot ulcer: a comprehensive Mendelian randomization analysis
Authors: Yin Kangli , Qiao Tianci , Zhang Yongkang , Liu Jiarui , Wang Yuzhen , Qi Fei , Deng Junlin , Zhao Cheng , Xu Yongcheng , Cao Yemin
Published: November 2023

Introduction

Diabetic foot ulcer (DFU) stands as a severe diabetic lower extremity complication, characterized by high amputation rates, mortality, and economic burden. We propose using Mendelian randomization studies to explore shared and distinct risk factors for diabetic lower extremity complications.

Research design and methods

We selected uncorrelated genetic variants associated with 85 phenotypes in five categories at the genome-wide significance level as instrumental variables. Genetic associations with DFU, diabetic polyneuropathy (DPN), and diabetic peripheral artery disease (DPAD) were obtained from the FinnGen and UK Biobank studies.

Results

Body mass index (BMI) emerged as the only significant risk factor for DPAD, DPN, and DFU, independent of type 2 diabetes, fasting glucose, fasting insulin, and HbA1c. Educational attainment stood out as the sole significant protective factor against DPAD, DPN, and DFU. Glycemic traits below the type 2 diabetes diagnosis threshold showed associations with DPAD and DPN. While smoking history exhibited suggestive associations with DFU, indicators of poor nutrition, particularly total protein, mean corpuscular hemoglobin, and mean corpuscular volume, may also signal potential DFU occurrence.

Conclusions

Enhanced glycemic control and foot care are essential for the diabetic population with high BMI, limited education, smoking history, and indicators of poor nutrition. By focusing on these specific risk factors, healthcare interventions can be better tailored to prevent and manage DFU effectively.