bluuebunny/crossref_metadata_2025_split huggingface dataset:
Back-EMF Sensing of Linear Resonant Actuators for Detection of Tap-Induced Vibration
Authors: Schmidt Ryan , Guzman Melissa Hernandez , Schlagenhauf Franziska , Singhose William 
Published: November 2023

Abstract
This paper examines the dynamics, detection, and interpretation of back electromotive force (EMF) in linear resonant actuators (LRAs). LRAs are small motors that are commonly used to generate haptic signals in a wide variety of devices including phones, smartwatches, and video game controllers. LRAs use a coil attached to the motor chassis to generate a magnetic field. This magnetic field causes displacement of a magnetic mass that is attached to the LRA chassis using a spring. The spring acts to return the mass to its equilibrium position, causing it to vibrate. The physical design of an LRA produces dynamics that are similar to a mass-spring-damper system. Haptic signals are generated by moving the internal mass at frequencies that can be felt by the user. A possible application of sensing back-EMF in LRAs is detecting user taps on consumer electronic devices such as smartphones and smart watches. Active sensing, which requires driving the LRA with an alternating current, can be used for pressure and environment sensing but requires careful consideration of the frequency of the driving signal and sampling rate. Passive sensing such as tap, swipe, and motion sensing can be realized with limited current draw, but are difficult to utilize when the LRA is actively being used for generating haptic effects. This paper applies passive back-EMF sensing to detect taps and explores the classification of different tap intensities.
The Impact of COVID-19 on Mass Personalization Supply Chain Networks – A Qualitative Inquiry
Authors: Schuebert Bryce , Shah Devanshi , Mullis Jesse , Mozaffar Fatemeh , Morkos Beshoy 
Published: November 2023

Abstract
Mass personalization (MPP) is a novel production method that integrates the consumer into the design process, efficiently producing distinct, scalable products that satisfy latent consumer needs. Previous MPP research has focused on the Industry 4.0 manufacturing processes and technologies required to make personalization a feasible method. Inherently, MPP necessitates a configurable supply chain that accommodates fluctuating product requirements. However, there has been little effort to examine the resilience and robustness of MPP supply chain networks in instances of external disruptions such as the ongoing COVID-19 supply chain crisis. This research takes a formal qualitative approach to investigate three MPP focal firms and the pandemic’s impact on their supply chain network through interviews with industry leaders. In doing so, we address research questions centered on MPP robust and resilience against external disruptions. The study finds that faced COVID-19 disruptions, MPP firms with centralized, specialty suppliers were vulnerable, while firms with increased supplier redundancy, network transitivity, and amplified visibility were robust and resilient. Evidence indicates that MPP capabilities provided robustness advantages over other production methods. Further, This work discovered that MPP FFs were particularly vulnerable to COVID-19 disruptions when using non-redundant, centralized suppliers. However, FFs taking advantage of MPP technologies to increase visibility and supplier redundancy were robust to disruptions and quick to recover from interruptions.
Inverse Determination of Detailed Internal Flow and Temperature Fields From Wall Measurements
Authors: Aryal Kapil , Nair Vivek , Dennis Brian H. 
Published: November 2023

Abstract
A data driven reduced order model (ROM) formulation is presented that is both quick and computationally efficient in estimating field variables for multi-physics inverse estimation applications. The approach is based on training data obtained by performing high fidelity simulations for a design of experiments generated in parameter space. Proper Orthogonal Decomposition (POD) in the parameter space is used to extract the most efficient modes and its coefficients. The trajectories of the modal coefficients are first analyzed and based on this information, a feed-forward neural network is trained with parameters as input and the modal coefficients as output. The resulting ROM is applied to the prediction of steady full temperature and velocity field inside a cylindrical channel with a spherical heat source at the center of the channel. The input parameters are the temperature measurements at three points on the wall surface, or at locations very close to the heated sphere. This approach is valuable for applications where non-invasive measurements are available yet internal detailed information is desired. As a proof-of-principle, the method is applied to a steady flow problem in a 2-D axisymmetric geometry at various flow rates and heat loads. The black-box approach makes use of full order solutions obtained by the finite element package COMSOL. The predicted nodal temperatures and the predicted nodal velocities show very accurate agreements with FOM solutions. The POD-ANN ROM framework clearly captures the coupling relationship between temperature and velocity because the velocity field was predicted very accurately based only on temperature data from the sensors. The high recall speed enabled by the ANN allows for real-time prediction of FOM fields as a function of the input parameters. This framework proved to be extremely reliable even in the presence of high Gaussian noise in the measured data.
Machine Learning Based Deflection Prediction and Inverse Design for Discrete Variable Stiffness Units
Authors: Fu Jiaming , Guo Qianyu , Gan Dongming 
Published: November 2023

Abstract
Large deflection modeling is a crucial field of study in the analysis and design of compliant mechanisms (CM). This paper proposes a machine learning (ML) approach for predicting the deflection of discrete variable stiffness units (DSUs) that cover a range from small to large deflections. The primary structure of a DSU consists of a parallel guide beam with a hollow cavity that can change stiffness discretely by inserting or extracting a solid block. The principle is based on changing the cross-sectional area properties of the hollow section. Prior to model training, a large volume of data was collected using finite element analysis (FEA) under different loads and various dimensional parameters. Additionally, we present three widely used machine learning-based models for predicting beam deflection, taking into account prediction accuracy and speed. Several experiments are conducted to evaluate the performance of the ML models that were compared with the FEA and analytical model results. The optimal ML model, multilayer perceptron (MLP), can achieve a 7.9% maximum error compared to FEA. Furthermore, the model was employed in a practical application for inverse design, with various cases presented depending on the number of solved variables. This method provides a innovative perspective for studying the modeling of compliant mechanisms and may be extended to other mechanical mechanisms.
Three-Dimensional Symmetric Tossing Motion Prediction – A Pilot Study
Authors: Lee Seunghun , Yang James 
Published: November 2023

Abstract
Weight tossing is a complex motion that combines multiple manual material handling tasks. The combined motion reduces labor time but comes at the cost of increased physical strain. After the pandemic, workplace injuries have been emerging as a hot potato. The industry spent an astronomical budget on improving workplace safety. It is critical to investigate different strategies for tossing motion to prevent injury risks. Tossing motion prediction provides insights into the status of the human biodynamic system during tossing. This paper reported an optimization-based 3D symmetric tossing motion prediction with a forty-one degree of freedom digital human model. The general equation of motion is generated using forward recursive kinematics and backward recursive dynamics. The dynamic effort is the objective function to be minimized. Design variables are the control points of the B-spline for the joint angles. Both time-dependent and independent non-linear constraints were applied to the problem. Lab experimental data collection for tossing a sandbag to a target point was collected and used to evaluate the predicted motion. The validation result showed that the predicted motion had a good agreement with experimental data in major joint angles, but the ground reaction forces showed some discrepancies. Future work was discussed to improve this prediction technique.
Efficient and Accurate Real-Time Simulations of Coupled Mechanical Systems Using the Universal Hydraulic Surrogate
Authors: Khadim Qasim , Kurvinen Emil , Mikkola Aki , Orzechowski Grzegorz 
Published: November 2023

Abstract
The real-time simulation of coupled multibody and hydraulics systems can be challenging due to the complexity, accuracy, and non-linear behavior of the modeling methods and the computational requirements. To this end, this study introduces the universal hydraulic surrogate approach instead of the conventional lumped fluid theory to solve the dynamics of hydraulically driven systems. The universal hydraulic surrogate is prepared with an approximated force model and trained with the behaviors of lumped fluid theory using the Covariance Matrix Adaption Evolutionary Strategy (CMA-ES). The universal hydraulic surrogate is used to solve the dynamics of the hydraulically actuated four-bar mechanism. The performance of the universal hydraulic surrogate is compared with the lumped fluid theory in terms of numerical accuracy and computational efficiency. The maximum percent normalized root mean square error (PN-RMSE) in the states of the four-bar mechanism using a simple force model compared to the lumped fluid theory is 2.06 %. The simulation with the universal hydraulic surrogate approach is up to 45 times faster than the lumped fluid theory in the studied case. The proposed study will enhance the computational efficiency of the coupled multibody systems and enhances their use in artificial intelligence, neural networks, and machine learning applications for complicated industrial systems.
An Investigation Into an Approach for Automated Supply Chain Onboarding
Authors: Jelisic Elena , Ivezic Nenad , Kulvatunyou Boonserm , Charoenwut Perawit , Nikolov Ana 
Published: November 2023

Abstract
The COVID-19 pandemic has brought the cold chain for biopharmaceutical products to the spotlight. To preserve their structure and function, biopharmaceuticals such as cells, proteins and enzymes, RNA molecules, and RNA-based drugs (e.g., mRNA-based COVID-19 vaccines) require low temperatures for proper handling, storage, and transport. Due to the sensitivity of these products transported through cold chains and the lack of traceability, risks associated with the stability, efficacy, safety, tardiness, quality, and waste are significant. For this reason, the ability to quickly find, connect, and do business with a new supply chain partner, such as in cold chain partnering is essential. Many researchers suggested various approaches to improve the effectiveness of cold chains. However, standardization and interoperability remain open challenges. Motivated by the biopharma risks and the need for interoperability, this paper presents a preliminary investigation into a novel approach for automating the onboarding of new supply chain partners. Based on the analysis of previous efforts in the cold chain domain, the notion of external context is recognized. In addition, the paper introduces the notion of business context which is proposed as a basis for a novel approach to achieve agile supply chain via automatic supply chain partner onboarding. Cold chain networking is used as a specific case study. The investigation results show that, with identified improvements, the approach has a potential to increase the automation in supply chain integration.
Effect of Tool Profile Modification on the Loaded Contact Performance for Face-Hobbed Hypoid Gear
Authors: Wei Xinqi , Wang Yawen , Lim Teik 
Published: November 2023

Abstract
Tool profile modification of face-hobbed hypoid gears is widely used to reduce the meshing shock associated with edge contact during heavy load meshing of gears. It is necessary to study the effect of different modification amounts and modification types on gear meshing performance to determine the optimal modification settings. This paper presents a mathematical model for tool profile modification of face-hobbed hypoid gears. Then, a set of modification parameters is designed, and the tooth surface deviation distribution is analyzed based on the proposed model. Finally, the effect of different modification parameters and types on the meshing performance is investigated based on a semi-finite element contact analysis model. The results show that the appropriate tool profile modification types and amounts can eliminate the edge contact of gear under heavy load. The curved blade has a drum correction effect on the tooth surface, and the edge contact of the tooth surface can be effectively removed with the increase of the radius curvature, but the transmission error also increases. The Toprem can change the position of the contact pattern in the tooth height direction, but it cannot eliminate the stress concentration phenomenon, and the transmission error increases sharply with the increase of the length of the Toprem.
Boosting student performance with inclusive writing-to-learn assignments through graphic organizers in large enrollment undergraduate biology courses
Authors: Wallace Alison , Barosh Theresa , Brisch Ellen , Laybourn Paul , Balgopal Meena M. 
Published: November 2023

ABSTRACT
Logistical challenges in large enrollment classes are often mentioned as obstacles to active learning. Writing is an integral part of being a scientist and is often one of the first tools considered by STEM instructors to increase student engagement, but iterative writing assignments in large classes require creativity on the part of the instructor. We found an association between writing-to-learn assignments designed to be consistent with inclusive learning pedagogies and student performance measures in a large enrollment undergraduate biology course. They provide ample opportunity for deliberate practice and inclusive engagement, components of the “heads and hearts” hypothesis posed to explain the variation in active learning impacts on the performance of minoritized students.
Three-Component Synthesis of New C3-Substituted 5,6-Dihydropyrrolo[2,1-a]isoquinolines
Authors: Miftyakhova A. R. , Sidakov M. B. , Borisova T. N. , Fakhrutdinov A. N. , Titov A. A. , Sorokina E. A. , Varlamov A. V. 
Published: November 2023

Abstract
New C3-substituted 5,6-dihydropyrrolo[2,1-a]isoquinolines have been synthesized via three-com­ponent domino reaction of 1-aroyl-3,4-dihydroisoquinolines, dimethyl acetylenedicarboxylate, and CH acids in anhydrous acetonitrile under microwave irradiation at 130°C.
Role of pharmacists in the context of rare diseases: a scoping review protocol
Authors: Cunico Cássia , Leite Silvana Nair 
Published: November 2023

IntroductionRare diseases are chronic conditions, generally incurable, progressive and disabling, which may result in early death. Access to therapeutic products, both medicines and appropriate medical devices, is essential to prevent the progression of the disease and maintain the patients’ quality of life. Pharmacists can be part of health teams, in charge of guiding patients’ journey, monitoring pharmacotherapy and identifying risks. This scoping review aims to identify and summarise evidence on the role of pharmacists and its impact in the field of rare diseases.Methods and analysisThe searches will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline for protocols. Three electronic databases will be consulted. Studies reporting on qualitative and/or quantitative data from any world region will be considered. There will be no language or initial time limit for studies inclusion, until December 2022. To be eligible for inclusion, studies must focus on the role pharmacists in clinical services aimed at promote the access to medicines, prevention and resolution of problems related to pharmacotherapy. No assessments of items’ quality will be made, as the purpose of this scoping review is to synthesise and describe the coverage of the evidence. Clinical, humanistic or economic outcomes from studies that meet the inclusion criteria will be included in the review. The analysis will synthesise the available evidence and may be able to push pharmaceutical practice forward, aiding professionals, educators and managers in the implementation of new approaches to better meet the needs of rare diseases and providing opportunities for future research.Ethics and disseminationPrimary data will not be collected in this study and formal ethical approval is not required. The findings of this study will be disseminated through peer-reviewed publications and conference presentations.
Communication between consultants providing advice and referring physicians: a scoping review
Authors: Muftah Amira , Stempien James , Goodridge Donna , Watson Erin , Oyedokun Taofiq 
Published: November 2023

ObjectiveCommunication during consultations between referring and consultant physicians is often cited as a source of adverse events, medical error and professional incivility. While existing literature focuses on the role of referring physicians, few studies acknowledge the role of consultant physicians in enhancing communication during consultations. This scoping review aims to identify and synthesise available recommendations to enhance the communication practices of consultants during real-time consultations.DesignA scoping review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews.Data sourcesMedline, EMBASE and PsycINFO databases were searched from inception to August 2022.Eligibility criteria for selecting studiesEnglish-language publications which describe recommendations, strategies or frameworks to improve the communication practices of consultant physicians during real-time consultations with referring physicians.Data extraction and synthesisThe search strategy included the following concepts: consultation, physician, communication, interprofessional relations and best practice. Two authors independently performed each phase of title and abstract screening, full-text review and data extraction. Discrepancies were resolved by a third author. Extracted data were iteratively analysed and summarised thematically.ResultsSixteen publications met the inclusion criteria. Synthesis of available recommendations identified organisation, expertise and interpersonal skills as three overarching and interconnected dimensions of communication demonstrated by consultants during effective consultations. Twelve studies identified interpersonal skills as being critical in alleviating the widespread professional incivility that is reported during consultations. Existing recommendations to improve the communication practices of consultants are limited as they lack standardised interventions and fail to comprehensively address all three elements identified in this review.ConclusionThis scoping review synthesises available recommendations to improve the communication practices of consultant physicians during real-time consultations. An opportunity exists to develop communication tools or educational interventions based on the findings of this review to enhance interphysician consultation encounters.
Maternal serum levels of prokineticin-1 related to pregnancy complications and metformin use in women with polycystic ovary syndrome: a post hoc analysis of two prospective, randomised, placebo-controlled trials
Authors: Ujvari Dorina , Trouva Anastasia , Hirschberg Angelica Lindén , Vanky Eszter 
Published: November 2023

ObjectiveSerum prokineticin-1 (s-PROK1) in the second and third trimester of pregnancy is positively correlated to preeclampsia, intrauterine growth restriction (IUGR) and preterm delivery. Women with polycystic ovary syndrome (PCOS) are prone to these adverse pregnancy outcomes. However, the contribution of PROK1 to the development of pregnancy complications and the effect of metformin and hyperandrogenism on s-PROK1 in PCOS have not been studied previously.DesignThis work is a post hoc analysis of two prospective, randomised, placebo-controlled trials.SettingPregnant women with PCOS were included from 11 study centres in Norway.ParticipantsFrom 313 women, 264 participated in the present study after exclusions due to dropouts or insufficient serum samples.InterventionWomen with PCOS were randomly administered with metformin or placebo, from first trimester to delivery.Primary and secondary outcome measuress-PROK1 was analysed using ELISA at gestational week 19 and related to pregnancy complications, fasting insulin levels, homoeostatic model assessment for insulin resistance (HOMA-IR), testosterone, or androstenedione levels, metformin use, PCOS phenotype and hyperandrogenism.ResultsMaternal s-PROK1 in the second trimester did not predict pregnancy-induced hypertension, pre-eclampsia or late miscarriage/preterm delivery in women with PCOS. However, s-PROK1 was lower in women who used metformin before inclusion, both in those randomised to metformin and to placebo, compared with those who did not. s-PROK1 was also lower in those who used metformin both at conception and during pregnancy compared with those who used metformin from inclusion or did not use metformin at all. s-PROK1 was lower in hyperandrogenic compared with normo-androgenic women with PCOS.ConclusionsMaternal s-PROK1 in the second trimester did not predict pregnancy complications in PCOS. Those who used metformin at conception and/or during pregnancy had lower s-PROK1. PCOS women with hyperandrogenism exhibited lower s-PROK1 compared with normo-adrogenic phenotypes.Trial registration numberNCT03259919andNCT00159536.