bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliability-Informed Life Cycle Warranty Cost and Life Cycle Analysis of Newly Manufactured and Remanufactured Units
Authors: Li Meng , Nemani Venkat P. , Liu Jinqiang , Lee Michael A. , Ahmed Navaid , Kremer Gül E. , Hu Chao 
Published: April 2021

Abstract
Standard life cycle techniques such as life cycle warranty cost (LCWC) analysis and life cycle analysis (LCA) are used to respectively quantify the relative economical and environmental advantages of remanufactured goods while simultaneously identifying avenues for improvement. In this paper, we contribute to the literature on life cycle studies by incorporating reliability into LCWC analysis and LCA with the goal of improving long-term/multiple life cycle decision making. We develop a branched power-law model to incorporate the physical degradation mechanisms leading to reduced reuse rates of system parts over multiple life cycles. We then follow a standard LCA protocol to quantify the difference between a new unit and its remanufactured version in terms of environmental impact items such as abiotic depletion potential, global warming potential, and energy consumption. We then devise four practical warranty policies that vary in the choice of replacement and/or provision for extended warranty. All possible replacement scenarios for multiple life cycles are explored for each policy and a mathematically rigorous framework is provided, where the reliability information is used to calculate probabilistic LCWC and life cycle impact items. This reliability-informed LCWC analysis and LCA framework enables design engineers to compare design options and warranty policies by quantifying both economical and environmental impacts to aid in decision making. Although the framework is presented in a general form applicable to any engineered system, we demonstrate the utility of this framework by using a case study of an infinitely variable transmission used in agricultural equipment.
Evolutionary Gaussian Processes
Authors: Planas Robert , Oune Nick , Bostanabad Ramin 
Published: April 2021

AbstractEmulation plays an important role in engineering design. However, most emulators such as Gaussian processes (GPs) are exclusively developed for interpolation/regression and their performance significantly deteriorates in extrapolation. To address this shortcoming, we introduce evolutionary Gaussian processes (EGPs) that aim to increase the extrapolation capabilities of GPs. An EGP differs from a GP in that its training involves automatic discovery of some free-form symbolic bases that explain the data reasonably well. In our approach, this automatic discovery is achieved via evolutionary programming (EP) which is integrated with GP modeling via maximum likelihood estimation, bootstrap sampling, and singular value decomposition. As we demonstrate via examples that include a host of analytical functions as well as an engineering problem on materials modeling, EGP can improve the performance of ordinary GPs in terms of not only extrapolation, but also interpolation/regression and numerical stability.
Designing an Optimal Modular-Based Product Family Under Intellectual Property and Sustainability Considerations
Authors: Kim Jinju , Saidani Michael , Kim Harrison M. 
Published: April 2021

Abstract
With the rapid development of new technology and the growing global competition in industry, it is essential for companies to protect their sensitive product designs and technologies. To ensure that their systems are not exploited by potential patent infringers, original equipment manufacturers often apply physical attributes and/or reduce commonality within a product family to prevent easy reusing and recovering. Yet, these design strategies are key barriers to the sustainable recovery and recycling of products. To address these trade-offs, this paper proposes a stepwise methodology to identify the sustainable optimal product family architecture design while protecting intellectual property on sensitive parts or modules. The developed approach notably allows the selection of suitable and sustainable candidates to share among products, taking into account the cost-benefit of commonality within the product family. To demonstrate and test the proposed methodology, a case study is performed with a printer-product family. Environmental savings resulting from the new modular-based architecture obtained for this product family are quantified and discussed.
The Influence of Process Management: Uncovering the Impact of Real-Time Managerial Interventions via a Topic Modeling Approach
Authors: Gyory Joshua T. , Kotovsky Kenneth , Cagan Jonathan 
Published: April 2021

AbstractComputationally studying team discourse can provide valuable, real-time insights into the state of design teams and design cognition during problem-solving. The particular experimental design, adopted from previous work by the authors, places one of the design team conditions under the guidance of a human process manager. In that work, teams under this process management outperformed the unmanaged teams in terms of their design performance. This opens the opportunity to not only model design discourse during problem-solving, but more critically, to explore process manager interventions and their impact on design cognition. Utilizing this experimental framework, a topic model is trained on the discourse of human designers of both managed and unmanaged teams collaboratively solving a conceptual engineering design task. Results show that the two team conditions significantly differ in a number of the extracted topics and, in particular, those topics that most pertain to the manager interventions. A dynamic look during the design process reveals that the largest differences between the managed and unmanaged teams occur during the latter half of problem-solving. Furthermore, a before and after analysis of the topic-motivated interventions reveals that the process manager interventions significantly shift the topic mixture of the team members’ discourse immediately after intervening. Taken together, these results from this work not only corroborate the effect of the process manager interventions on design team discourse and cognition but provide promise for the computational detection and facilitation of design interventions based on real-time, discourse data.
Multi-Objective Optimization for High-Dimensional Expensively Constrained Black-Box Problems
Authors: Cheng George H. , Gary Wang G. , Hwang Yeong-Maw 
Published: April 2021

Abstract
Multi-objective optimization (MOO) problems with computationally expensive constraints are commonly seen in real-world engineering design. However, metamodel-based design optimization (MBDO) approaches for MOO are often not suitable for high-dimensional problems and often do not support expensive constraints. In this work, the situational adaptive Kreisselmeier and Steinhauser (SAKS) method was combined with a new multi-objective trust region optimizer (MTRO) strategy to form the SAKS-MTRO method for MOO problems with expensive black-box constraint functions. The SAKS method is an approach that hybridizes the modeling and aggregation of expensive constraints and adds an adaptive strategy to control the level of hybridization. The MTRO strategy uses a combination of objective decomposition and K-means clustering to handle MOO problems. SAKS-MTRO was benchmarked against four popular multi-objective optimizers and demonstrated superior performance on average. SAKS-MTRO was also applied to optimize the design of a semiconductor substrate and the design of an industrial recessed impeller.
Acoustic Field-Assisted Two-Photon Polymerization Process
Authors: Lichade Ketki M. , Pan Yayue 
Published: April 2021

Abstract
This study successfully integrates acoustic patterning with the Two-Photon Polymerization (TPP) process for printing nanoparticle–polymer composite microstructures with spatially varied nanoparticle compositions. Currently, the TPP process is gaining increasing attention within the engineering community for the direct manufacturing of complex three-dimensional (3D) microstructures. Yet the full potential of TPP manufactured microstructures is limited by the materials used. This study aims to create and demonstrate a novel acoustic field-assisted TPP (A-TPP) process, which can instantaneously pattern and assemble nanoparticles in a liquid droplet, and fabricate anisotropic nanoparticle–polymer composites with spatially controlled particle–polymer material compositions. It was found that the biggest challenge in integrating acoustic particle patterning with the TPP process is that nanoparticles move upon laser irradiation due to the photothermal effect, and hence, the acoustic assembly is distorted during the photopolymerization process. To cure acoustic assembly of nanoparticles in the resin through TPP with the desired nanoparticle patterns, the laser power needs to be carefully tuned so that it is adequate for curing while low enough to prevent the photothermal effect. To address this challenge, this study investigated the threshold laser power for polymerization of TPP resin (Pthr) and photothermal instability of the nanoparticle (Pthp). Patterned nanoparticle–polymer composite microstructures were fabricated using the novel A-TPP process. Experimental results validated the feasibility of the developed acoustic field-assisted TPP process on printing anisotropic composites with spatially controlled material compositions.
Government management capacities and the containment of COVID-19: a repeated cross-sectional study across Chinese cities
Authors: Li Wenchao , Li Jing , Yi Junjian 
Published: April 2021

ObjectivesBetter understanding of the dynamics of the COVID-19 (2019 novel coronavirus disease) pandemic to curb its spread is now a global imperative. While travel restrictions and control measures have been shown to limit the spread of the disease, the effectiveness of the enforcement of those measures should depend on the strength of the government. Whether, and how, the government plays a role in fighting the disease, however, has not been investigated. Here, we show that government management capacities are critical to the containment of the disease.SettingWe conducted a statistical analysis based on cross-city comparisons within China. China has undergone almost the entire cycle of the anticoronavirus campaign, which allows us to trace the full dynamics of the outbreak, with homogeneity in standards for statistics recording.Primary and secondary outcome measuresOutcome measures include city-specific COVID-19 case incidence and recoveries in China.ResultsThe containment of COVID-19 depends on the effectiveness of the enforcement of control measures, which in turn depends on the local government’s management capacities. Specifically, government efficiency, capacity for law enforcement, and the transparency of laws and policies significantly reduce COVID-19 prevalence and increase the likelihood of recoveries. The organisation size of the government, which is not closely related to its capacity for management, has a limited role.
Cross-sectional online survey to determine the prevalence, knowledge, attitude and practice of tobacco cessation among governmental healthcare workers in Qatar
Authors: AlMulla Ahmad , Kouyoumjian Silva , ElNakib Nour 
Published: April 2021

ObjectivesOne effective approach of tobacco control is to encourage the role and the participation of healthcare workers in the prevention efforts against tobacco use. This study aimed to determine the prevalence of tobacco use among governmental healthcare workers in Qatar, to assess healthcare workers’ knowledge, attitude and practice of tobacco cessation and to predict factors associated with above average tobacco cessation practice scores.DesignA cross-sectional survey study was conducted among healthcare workers working in Hamad Medical Corporation and Primary Healthcare Centres in Qatar using a self-administered online questionnaire in 2019.SettingHamad Medical Corporation and Primary Healthcare Centres in Qatar.ParticipantsGovernmental healthcare workers aged 18 years and above (n=7214).ResultsThe response rate of our online survey was 20.6% (7214/35 000). Of the 7214 healthcare workers, 16.3% (n=1178) were current tobacco users. In particular, the prevalence of tobacco use among physicians was 11.0%. Fifty-two per cent of healthcare workers (n=2338) attained an average knowledge score (12–17), 71.8% (n=3094) attained positive attitude scores (8–12) and 57.1% (n=3052) attained above average practice scores (12–26). Among the different professions, physicians were having the highest mean knowledge (15.3±4.7), attitude (9.4±1.9) and practice (13.7±6.1) scores. Multivariate analysis showed that having good knowledge (adjusted OR (AOR)=2.8; p<0.0001) and training (AOR=2.4; p<0.0001) were the strongest factors associated positively with above average tobacco cessation practice scores.ConclusionsHealthcare workers in Qatar have a relatively similar prevalence of tobacco use than earlier studies with no significant increase. Investing more in training programmes for healthcare workers are needed to root out this negative behaviour and to increase their skills to assist users to quit.
Diet quality indices, genetic risk and risk of cardiovascular disease and mortality: a longitudinal analysis of 77 004 UK Biobank participants
Authors: Livingstone Katherine M , Abbott Gavin , Bowe Steven J , Ward Joey , Milte Catherine , McNaughton Sarah A 
Published: April 2021

ObjectivesTo examine associations of three diet quality indices and a polygenic risk score with incidence of all-cause mortality, cardiovascular disease (CVD) mortality, myocardial infarction (MI) and stroke.DesignProspective cohort study.SettingUK Biobank, UK.Participants77 004 men and women (40–70 years) recruited between 2006 and 2010.Main outcome measuresA polygenic risk score was created from 300 single nucleotide polymorphisms associated with CVD. Cox proportional HRs were used to estimate independent effects of diet quality and genetic risk on all-cause mortality, CVD mortality, MI and stroke risk. Dietary intake (Oxford WebQ) was used to calculate Recommended Food Score (RFS), Healthy Diet Indicator (HDI) and Mediterranean Diet Score (MDS).ResultsNew all-cause (n=2409) and CVD (n=364) deaths and MI (n=1141) and stroke (n=748) events were identified during mean follow-ups of 7.9 and 7.8 years, respectively. The adjusted HR associated with one-point higher RFS for all-cause mortality was 0.96 (95% CI: 0.94 to 0.98), CVD mortality was 0.94 (95% CI: 0.90 to 0.98), MI was 0.97 (95% CI: 0.95 to 1.00) and stroke was 0.94 (95% CI: 0.91 to 0.98). The adjusted HR for all-cause mortality associated with one-point higher HDI and MDS was 0.97 (95% CI: 0.93 to 0.99) and 0.95 (95% CI: 0.91 to 0.98), respectively. The adjusted HR associated with one-point higher MDS for stroke was 0.93 (95% CI: 0.87 to 1.00). There was little evidence of associations between HDI and risk of CVD mortality, MI or stroke. There was evidence of an interaction between diet quality and genetic risk score for MI.ConclusionHigher diet quality predicted lower risk of all-cause mortality, independent of genetic risk. Higher RFS was also associated with lower risk of CVD mortality and MI. These findings demonstrate the benefit of following a healthy diet, regardless of genetic risk.
Prediction of treatment dosage and duration from free-text prescriptions: an application to ADHD medications in the Swedish prescribed drug register
Authors: Zhang Le , Lagerberg Tyra , Chen Qi , Ghirardi Laura , D'Onofrio Brian M , Larsson Henrik , Viktorin Alexander , Chang Zheng 
Published: April 2021

BackgroundAccurate estimation of daily dosage and duration of medication use is essential to pharmacoepidemiological studies using electronic healthcare databases. However, such information is not directly available in many prescription databases, including the Swedish Prescribed Drug Register.ObjectiveTo develop and validate an algorithm for predicting prescribed daily dosage and treatment duration from free-text prescriptions, and apply the algorithm to ADHD medication prescriptions.MethodsWe developed an algorithm to predict daily dosage from free-text prescriptions using 8000 ADHD medication prescriptions as the training sample, and estimated treatment periods while taking into account several features including titration, stockpiling and non-perfect adherence. The algorithm was implemented to all ADHD medication prescriptions from the Swedish Prescribed Drug Register in 2013. A validation sample of 1000 ADHD medication prescriptions, independent of the training sample, was used to assess the accuracy for predicted daily dosage.FindingsIn the validation sample, the overall accuracy for predicting daily dosage was 96.8%. Specifically, the natural language processing model (NLP1 and NLP2) have an accuracy of 99.2% and 96.3%, respectively. In an application to ADHD medication prescriptions in 2013, young adult ADHD medication users had the highest probability of discontinuing treatments as compared with other age groups. The daily dose of methylphenidate use increased with age substantially.ConclusionsThe algorithm provides a flexible approach to estimate prescribed daily dosage and treatment duration from free-text prescriptions using register data. The algorithm showed a good performance for predicting daily dosage in external validation.Clinical implicationsThe structured output of the algorithm could serve as basis for future pharmacoepidemiological studies evaluating utilization, effectiveness, and safety of medication use, which would facilitate evidence-based treatment decision-making.
Racial, ethnic and socioeconomic disparities in patients undergoing left atrial appendage closure
Authors: Sparrow Robbie , Sanjoy Shubrandu , Choi Yun-Hee , Elgendy Islam Y , Jneid Hani , Villablanca Pedro A , Holmes David R , Pershad Ashish , Alraies Chadi , Sposato Luciano A , Mamas Mamas A , Bagur Rodrigo 
Published: April 2021

ObjectiveThis manuscript aims to explore the impact of race/ethnicity and socioeconomic status on in-hospital complication rates after left atrial appendage closure (LAAC).MethodsThe US National Inpatient Sample was used to identify hospitalisations for LAAC between 1 October 2015 to 31 December 2018. These patients were stratified by race/ethnicity and quartiles of median neighbourhood income. The primary outcome was the occurrence of in-hospital major adverse events, defined as a composite of postprocedural bleeding, cardiac and vascular complications, acute kidney injury and ischaemic stroke.ResultsOf 6478 unweighted hospitalisations for LAAC, 58% were male and patients of black, Hispanic and ‘other’ race/ethnicity each comprised approximately 5% of the cohort. Adjusted by the older Americans population, the estimated number of LAAC procedures was 69.2/100 000 for white individuals, as compared with 29.5/100 000 for blacks, 47.2/100 000 for Hispanics and 40.7/100 000 for individuals of ‘other’ race/ethnicity. Black patients were ~5 years younger but had a higher comorbidity burden. The primary outcome occurred in 5% of patients and differed significantly between racial/ethnic groups (p<0.001) but not across neighbourhood income quartiles (p=0.88). After multilevel modelling, the overall rate of in-hospital major adverse events was higher in black patients as compared with whites (OR: 1.60, 95% CI 1.22 to 2.10, p<0.001); however, the incidence of acute kidney injury was higher in Hispanics (OR: 2.19, 95% CI 1.52 to 3.17, p<0.001). No significant differences were found in adjusted overall in-hospital complication rates between income quartiles.ConclusionIn this study assessing racial/ethnic disparities in patients undergoing LAAC, minorities are under-represented, specifically patients of black race/ethnicity. Compared with whites, black patients had higher comorbidity burden and higher rates of in-hospital complications. Lower socioeconomic status was not associated with complication rates.
New generation of DNA-based immunotherapy induces a potent immune response and increases the survival in different tumor models
Authors: Lopes Alessandra , Bastiancich Chiara , Bausart Mathilde , Ligot Sophie , Lambricht Laure , Vanvarenberg Kevin , Ucakar Bernard , Gallez Bernard , Préat Véronique , Vandermeulen Gaëlle 
Published: April 2021

BackgroundStrategies to increase nucleic acid vaccine immunogenicity are needed to move towards clinical applications in oncology. In this study, we designed a new generation of DNA vaccines, encoding an engineered vesicular stomatitis virus glycoprotein as a carrier of foreign T cell tumor epitopes (plasmid to deliver T cell epitopes, pTOP). We hypothesized that pTOP could activate a more potent response compared with the traditional DNA-based immunotherapies, due to both the innate immune properties of the viral protein and the specific induction of CD4 and CD8 T cells targeting tumor antigens. This could improve the outcome in different tumor models, especially when the DNA-based immunotherapy is combined with a rational therapeutic strategy.MethodsThe ability of pTOP DNA vaccine to activate a specific CD4 and CD8 response and the antitumor efficacy were tested in a B16F10-OVA melanoma (subcutaneous model) and GL261 glioblastoma (subcutaneous and orthotopic models).ResultsIn B16F10-OVA melanoma, pTOP promoted immune recognition by adequate processing of both MHC-I and MHC-II epitopes and had a higher antigen-specific cytotoxic T cell (CTL) killing activity. In a GL261 orthotopic glioblastoma, pTOP immunization prior to tumor debulking resulted in 78% durable remission and long-term survival and induced a decrease of the number of immunosuppressive cells and an increase of immunologically active CTLs in the brain. The combination of pTOP with immune checkpoint blockade or with tumor resection improved the survival of mice bearing, a subcutaneous melanoma or an orthotopic glioblastoma, respectively.ConclusionsIn this work, we showed that pTOP plasmids encoding an engineered vesicular stomatitis virus glycoprotein, and containing various foreign T cell tumor epitopes, successfully triggered innate immunity and effectively promoted immune recognition by adequate processing of both MHC-I and MHC-II epitopes. These results highlight the potential of DNA-based immunotherapies coding for viral proteins to induce potent and specific antitumor responses.