bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Flow Curves for Ultra-Thin Steel Sheets With the In-Plane Torsion Test
Authors: Stiebert Fabian , Traphöner Heinrich , Meya Rickmer , Tekkaya A. Erman 
Published: August 2021

Abstract
The in-plane torsion test is a shear test that has already been successfully used to determine flow curves up to high strains for thin sheets with thicknesses between 0.5 mm and 3.0 mm. In the same way as with other shear tests, the formation of wrinkles is a major challenge in determining flow curves with the in-plane torsion test, especially when testing ultra-thin sheets with a thickness between 0.1 mm and 0.5 mm. A new method for suppressing wrinkling is introduced, in which the formation of wrinkles is avoided by arranging and gluing single sheets to multi-layered specimens. The influence of the used adhesive on the determination of flow curves is negligible. The proposed method is used to identify flow curves for two materials, the high strength steel TH620 and the soft steel TS230, used in the packaging industry. The Materials are tested in sheet thicknesses between 0.17 mm and 0.6 mm. The determined equivalent plastic strains for the TH620 with a sheet thickness of 0.20 mm, could be increased from 0.38 (bulge-test) to over 0.8 with the new method by using four-layered specimens.
Trajectory-Dependent Compensation Scheme to Reduce Manipulator Execution Errors for Manufacturing Applications
Authors: Bhatt Prahar M. , Malhan Rishi K. , Rajendran Pradeep , Shembekar Aniruddha V. , Gupta Satyandra K. 
Published: August 2021

Abstract
Robotic manipulators are increasingly being used for performing a wide variety of manufacturing processes. Some of the manufacturing processes performed using robotic manipulators require high trajectory execution accuracy. Automatically generated trajectories often exhibit significant execution errors due to robot model inaccuracies and controller behaviors. This suggests that a trajectory compensation scheme can be used to modify trajectory to reduce execution error. Unfortunately, the nature of the trajectory and the end-effector loading affect the trajectory tracking errors. So, the error reduction using a trajectory-independent automated compensation scheme does not always work. Our paper presents a method to sample the input trajectory, generate the training data by measuring the sampled trajectory execution, and learning the compensation scheme based on the physical run. The learned trajectory-dependent compensation scheme is capable of reducing the execution error. To demonstrate the compensation scheme’s effectiveness, we perform experiments on manipulators. After the trajectory compensation, the manipulator has considerably low trajectory execution errors, with the average path error close to the robot’s repeatability.
Deformation Analysis of 3D Printed Metacarpophalangeal and Interphalangeal Joints via Transfer Learning
Authors: Toscano Juan Diego , Hajifar Sahand , Segura Christian Oswaldo , Segura Luis Javier , Sun Hongyue 
Published: August 2021

Abstract
A cast/brace is a tight garment that restricts the movement and provides support to an injured zone. Traditional casts/braces suffer from material wastage, discomfort, patient dissatisfaction, odor, unnecessary weight, and dangerous extraction procedures. These issues can be solved partially by constructing the casts/braces via 3D printing. Toward this end, we print the personalized metacarpal casts/braces (MCB) via fused deposition modeling (FDM), and investigate their mechanical properties to ensure the desired functionality. However, printing the full-size MCB is time-consuming (takes more than 11 hours in our design), making it hard to collect a sufficient data set for the mechanical properties investigation. Here, we explore the utilization of reduced-size MCB to facilitate the analysis of full-size MCB via transfer learning. In particular, three critical process variables (i.e., raster width, layer height, and extrusion temperature) were varied, and a universal testing machine was used to measure the total deformation of the MCB. We then perform the prediction of the deformation in full-size MCB with transfer learning of data from reduced-size MCB and limited data from full-size MCB. From the case study, the transfer learning approach can reduce the needs of data collection in the time-consuming full-size MCB by leveraging the information from reduced-size MCB.
A FPGA-Based Cloud-Edge Collaboration Platform in Cloud Manufacturing
Authors: Xiao Chuan , Zhao Chun , Liu Yue , Zhang Lin 
Published: August 2021

Abstract
To address the issue that many devices are connected to the cloud during the manufacturing process, which causes severe delays in analyzing massive manufacturing data in the cloud, an FPGA-based architecture of cloud edge collaboration is proposed. In this architecture, manufacturing equipment is connected to the cloud through an FPGA-based embedded edge node. The device data obtained by the edge node is processed by the FPGA module and the embedded system module according to the time-sensitivity. Considering the limited computing power of a single edge node, to realize cloud-edge collaborative computing, a communication-oriented task model and a computing model for edge nodes are designed. The task model learns cloud to edge and edge-edge communication, and the task model realizes the function of migrating computing tasks to other nodes. The edge node system’s design is realized based on the communication-oriented task model and the computing model for edge nodes. The cloud edge collaboration method is researched and explored based on this system. A series of comparative experiments, comparing the time delay of the FPGA module and embedded system module processing the same data, the framework’s usability and data processing ability can be verified.
Conduction Heat Assisted Friction Element Welding
Authors: Grimm Tyler J. , Parvathy Gowtham V. , Mears Laine 
Published: August 2021

Abstract
Increasing awareness of global warming and strict government regulations have required the automotive industry to pursue lightweighting as an avenue towards increased vehicle efficiency. Lightweight designs typically rely heavily on multi-material use, which enables selective strengthening of critical areas without additional, unnecessary mass. Joining these materials during manufacturing has proven to be a challenging endeavor.
Friction element welding (FEW) is one process that is capable of joining aluminum to steel. This two-sided joining technique utilizes a fastener to secure the aluminum sheet by creating a friction weld with the steel sheet. While this process is extremely robust for most materials, the FEW process can result in the extrusion of material from underneath the head of the fastener, termed chipping, which leads to corrosion and aesthetic issues. This behavior is typically seen in high strength aluminum alloys, such as 7075. A solution to chipping is implemented herein, which utilizes a modified downholder to conductively heat the aluminum sheet prior to the FEW process. This heating method was explored experimentally and through various numerical analyses. This method was found to be a viable option for relieving chipping. While the process time was only increased by a maximum of 2.5 seconds, faster, more localized heating should be targeted for future work.
Experimental Study on the Effect of Surface Integrity on Fatigue Performance of Aero-Engine Blades
Authors: Huang Yun , Li Shaochuan , Xiao Guijian , Chen Benqiang , He Yi , Wang Wenxi , Zhou Kun 
Published: August 2021

Abstract
As the core component of aero-engine, the service performance of aero-engine blade has an important influence on the engine’s reliability and safety performance. Existing studies have shown that machined surface characteristics affect the fatigue strength of components. However, current studies are all based on regular fatigue samples. The structure of blades different from fatigue samples, and the influence mechanism of structural differences on the service performance of blades is still unclear. In addition, the conventional fatigue test conditions are not representative for the blades’ actual service conditions, so it is difficult to realize the processing process for the service performance optimization. In this study, the aero-engine blades processed by abrasive belt grinding and the vibration fatigue test bench were used to explore the influence of surface roughness, surface texture, and surface residual stress on the fatigue performance of aero-engine blades under actual working conditions. The aero-engine blades were ground with different process parameters to obtain different single-factor surface characteristics. By comparing the vibration fatigue life of blades with different surface features, the influence degree of each surface feature on the fatigue life was explored. Results showed that surface roughness has the greatest influence on fatigue strength, followed by residual stress, and surface texture has the least influence on fatigue strength.
Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing
Authors: Di Lei , Shah Gaurav Manish , Yang Yiran , Wei Cuicui 
Published: August 2021

Abstract
The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.
An OSGi-Based Adaptation Access of Machine Tools in the Cloud Manufacturing Environment
Authors: Li Xiaobin , Yin Chao 
Published: August 2021

Abstract
Machine tools (MTs) are the core manufacturing resources for discrete manufacturing enterprises. In the cloud manufacturing environment, MTs are massive, heterogeneous, widely dispersed and highly autonomous, which makes it difficult for cloud manufacturing mode to be deeply applied to support the networked collaboration operation among manufacturing enterprises. Realizing universal access and cloud application of various MTs is an essential prerequisite to solve the above problem. In this paper, an OSGi-based adaptation access method of MTs is proposed. First, the MTs information description model in the cloud manufacturing environment is built. Then, an OSGi-based adaptation access framework of MTs is constructed, and key enabling technologies, including machine tool information acquisition and processing, Bundle and Subsystem construction, are studied. Finally, an application case is conducted to verify the effectiveness and feasibility of the proposed method.
A Rheological Study of Bio-Ink: Shear Stress and Cell Viability
Authors: Habib Md Ahasan , Khoda Bashir 
Published: August 2021

Abstract
3D bio-printing is an emerging technology to fabricate tissue scaffold in-vitro through the controlled allocation of biomaterial and cell, which can mimic the in-vivo counterpart of living tissue. Live cells are often encapsulated into the biomaterials (i.e., bio-ink) and extruded by controlling the printing parameters. The functionality of the bioink depends upon three factors: (a) printability, (b) shape fidelity, and (c) bio-compatibility. Increasing viscosity will improve the printability and the shape fidelity; but will require higher applied extrusion pressure, which is detrimental to the living cell dwelling in the bio-ink, which is often ignored in bio-ink optimization process. In this paper, we demonstrate a roadmap to develop and characterize bio-inks ensuring the printability, shape fidelity, and cell survivability, simultaneously. The pressure exerted on the bio-ink during extrusion processes is measured analytically and the information is incorporated in the rheology design of the bio-ink. Cell-laden filament is fabricated with Human Embryonic Kidney (HEK 293) cell and analyzed the cell viability. The overall cell viability of the filament fabricated with 8 psi and 12 psi is 90% and 74% respectively. Additionally, a crossectional live-dead assay of the printed filament with HEK 293 cell is performed which demonstrates the spatial pattern that matches our findings as well.
Experimental Investigation of the Material Removal Rate in Grinding of Calcified Plaque by Rotational Atherectomy
Authors: Li Xinxiao , Chernjavsky Patrick , Angjeli Katerina , Hoffman Sola , Frunzi Sara , Zheng Yihao 
Published: August 2021

Abstract
Rotational atherectomy (RA) utilizes a high-speed, metal-bonded diamond-abrasive grinding wheel to remove the calcified atherosclerotic plaque inside arteries, restore blood flow, and treat cardiovascular diseases. RA operational guidelines have been clinically investigated to improve clinical outcomes and reduce complication rates, but are still in lack of consensus. Particularly, the effect of the grinding wheel rotational speed on plaque material removal rate (MRR) is unclear. This study experimentally investigates the RA MRR over a range of wheel rotational speeds based on a vascular simulator with a calcified plaque surrogate. The MRR, presented as the luminal area gain, with the increase of the number of grinding passes, was measured at the rotational speed of 120,000, 150,000, and 180,000 rpm. The luminal area was characterized via microscopy and image processing. The ground surface morphology and surface roughness at different rotational speeds were investigated. The results showed that a higher rotational speed led to a higher MRR and a smoother ground surface. This observation is significant for RA clinical guideline improvement.
Selective Laser Melting of Stainless Steel 316L for Mechanical Property-Gradation
Authors: Parikh Yash , Kuttolamadom Mathew 
Published: August 2021

Abstract
With an end goal of creating single-alloy functionally-graded additively manufactured (FGAM) parts, this paper investigates the manufacture and properties of stainless steel 316L samples via a pulsed selective laser melting (SLM) process. The focus is on elucidating the underlying causes of property variations (within a functionally-acceptable range) through material characterization and testing. Five samples (made via different volumetric energy density-based process parameter sets) were down-selected from preliminary experimental results and analyzed for their microstructure, mechanical and physical properties (hardness, density/porosity, Young’s modulus). It was observed that property variations resulted from combinations of porosity types/amounts, martensitic phase fractions, and grain sizes. Based on these, various functionally-graded specimens of different sizes were built as per ASTM standards, each having intended property changes along its gauge volumes. The presented findings establish that a methodical control of microstructure and mechanical properties could be obtained in a repeatable and reproducible manner by changing the process parameters. This work lays the foundation for understanding and tuning the global mechanical performance of FGAM bulk structures as well as the role of interfacial zones.
Predicting hospital admissions from individual patient data (IPD): an applied example to explore key elements driving external validity
Authors: Meid Andreas Daniel , Gonzalez-Gonzalez Ana Isabel , Dinh Truc Sophia , Blom Jeanet , van den Akker Marjan , Elders Petra , Thiem Ulrich , Küllenberg de Gaudry Daniela , Swart Karin M A , Rudolf Henrik , Bosch-Lenders Donna , Trampisch Hans J , Meerpohl Joerg J , Gerlach Ferdinand M , Flaig Benno , Kom Ghainsom , Snell Kym I E , Perera Rafael , Haefeli Walter Emil , Glasziou Paul , Muth Christiane 
Published: August 2021

ObjectiveTo explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.Study design and settingUsing individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).ResultsPrior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.ConclusionsPredictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.Trial registration numberPROSPERO id: CRD42018088129.
Root causes and preventability of emergency department presentations of older patients: a prospective observational study
Authors: Driesen Babiche , Merten Hanneke , Barendregt Rosalie , Bonjer H Jaap , Wagner Cordula , Nanayakkara Prabath W B 
Published: August 2021

ObjectiveMore older patients are presenting to the emergency department (ED). It is important to know why these patients present and if the ED is the best place for them to receive the care they need. The primary aim of this study was to identify organisational-related, technical-related, healthcare worker-related and patient-related factors leading to ED presentations of older patients. The secondary aim was to determine patients’ and caregivers’ perspectives on what kinds of ED presentations are potentially preventable.DesignThis is a prospective observational study. A root cause analysis was performed by the Prevention and Recovery Information System for Monitoring and Analysis method. It used basic administrative data collected from patient records and interviews of patients, general practitioners (GPs) and physicians at the ED.SettingThe ED of an academic hospital in the Netherlands.Participants100 older patients (aged ≥70 years) who attended the ED between November 2017 and March 2018.ResultsIn 100 patients presenting to the ED, 159 factors that contributed to presentation were identified; most of these factors were related to underlying diseases (59%) and patient-related factors (18%). These presentations were considered potentially preventable by 23% of the physicians at the ED and 21% of the GPs, but only 10% of the patients. In only four cases was there overall agreement between the patients and the healthcare workers.ConclusionThe most frequent underlying factors contributing to an ED presentation in older patients are disease-related and patient-related. The low percentage of ED presentations considered potentially preventable shows that a ‘preventable ED presentation’ is difficult to define and therefore interventions to reduce them are unlikely to be simple. Novel solutions within the acute care pathway are required in order to deliver care of optimal quality and safety to older patients.
Plasma NfL levels and longitudinal change rates in C9orf72 and GRN-associated diseases: from tailored references to clinical applications
Authors: Saracino Dario , Dorgham Karim , Camuzat Agnès , Rinaldi Daisy , Rametti-Lacroux Armelle , Houot Marion , Clot Fabienne , Martin-Hardy Philippe , Jornea Ludmila , Azuar Carole , Migliaccio Raffaella , Pasquier Florence , Couratier Philippe , Auriacombe Sophie , Sauvée Mathilde , Boutoleau-Bretonnière Claire , Pariente Jérémie , Didic Mira , Hannequin Didier , Wallon David ,   the French Research Network on FTD/FTD-ALS,   the PREV-DEMALS and Predict-PGRN study groups, Colliot Olivier , Dubois Bruno , Brice Alexis , Levy Richard , Forlani Sylvie , Le Ber Isabelle 
Published: August 2021

ObjectiveNeurofilament light chain (NfL) is a promising biomarker in genetic frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). We evaluated plasma neurofilament light chain (pNfL) levels in controls, and their longitudinal trajectories in C9orf72 and GRN cohorts from presymptomatic to clinical stages.MethodsWe analysed pNfL using Single Molecule Array (SiMoA) in 668 samples (352 baseline and 316 follow-up) of C9orf72 and GRN patients, presymptomatic carriers (PS) and controls aged between 21 and 83. They were longitudinally evaluated over a period of >2 years, during which four PS became prodromal/symptomatic. Associations between pNfL and clinical–genetic variables, and longitudinal NfL changes, were investigated using generalised and linear mixed-effects models. Optimal cut-offs were determined using the Youden Index.ResultspNfL levels increased with age in controls, from ~5 to~18 pg/mL (p<0.0001), progressing over time (mean annualised rate of change (ARC): +3.9%/year, p<0.0001). Patients displayed higher levels and greater longitudinal progression (ARC: +26.7%, p<0.0001), with gene-specific trajectories. GRN patients had higher levels than C9orf72 (86.21 vs 39.49 pg/mL, p=0.014), and greater progression rates (ARC:+29.3% vs +24.7%; p=0.016). In C9orf72 patients, levels were associated with the phenotype (ALS: 71.76 pg/mL, FTD: 37.16, psychiatric: 15.3; p=0.003) and remarkably lower in slowly progressive patients (24.11, ARC: +2.5%; p=0.05). Mean ARC was +3.2% in PS and +7.3% in prodromal carriers. We proposed gene-specific cut-offs differentiating patients from controls by decades.ConclusionsThis study highlights the importance of gene-specific and age-specific references for clinical and therapeutic trials in genetic FTD/ALS. It supports the usefulness of repeating pNfL measurements and considering ARC as a prognostic marker of disease progression.Trial registration numbersNCT02590276 and NCT04014673.