bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Optimization for Simulation-Based Design of Multi-Model Systems
Authors: Tao Siyu , van Beek Anton , Apley Daniel W. , Chen Wei 
Published: November 2020

Abstract
We address the problem of simulation-based design using multiple interconnected expensive simulation models, each modeling a different subsystem. Our goal is to find the globally optimal design with minimal model evaluation costs. To our knowledge, the best existing approach is to treat the whole system as a single expensive model and apply an existing Bayesian optimization (BO) algorithm. This approach is likely inefficient due to the need to evaluate all the component models in each iteration. We propose a multi-model BO approach that dynamically and selectively evaluates one component model per iteration based on linked emulators for uncertainty quantification and the system knowledge gradient (KG) as acquisition function. Building on this, we resolve problems with constraints and feedback couplings that often occur in real complex engineering design by penalizing the objective emulator and reformulating the original problem into a decoupled one. The superior efficiency of our approach is demonstrated through solving an analytical problem and a multidisciplinary design problem of electronic packaging optimization.
METASET: An Automated Data Selection Method for Scalable Data-Driven Design of Metamaterials
Authors: Chan Yu-Chin , Ahmed Faez , Wang Liwei , Chen Wei 
Published: November 2020

Abstract
Data-driven design of mechanical metamaterials is an increasingly popular method to combat costly physical simulations and immense, often intractable, geometrical design spaces. Using a precomputed dataset of unit cells, a multiscale structure can be quickly filled via combinatorial search algorithms, and machine learning models can be trained to accelerate the process. However, the dependence on data induces a unique challenge: An imbalanced dataset containing more of certain shapes or physical properties than others can be detrimental to the efficacy of the approaches and any models built on those sets. In answer, we posit that a smaller yet diverse set of unit cells leads to scalable search and unbiased learning. To select such subsets, we propose METASET, a methodology that 1) uses similarity metrics and positive semi-definite kernels to jointly measure the closeness of unit cells in both shape and property space, and 2) incorporates Determinantal Point Processes for efficient subset selection. Moreover, METASET allows the trade-off between shape and property diversity so that subsets can be tuned for various applications. Through the design of 2D metamaterials with target displacement profiles, we demonstrate that smaller, diverse subsets can indeed improve the search process as well as structural performance. We also apply METASET to eliminate inherent overlaps in a dataset of 3D unit cells created with symmetry rules, distilling it down to the most unique families. Our diverse subsets are provided publicly for use by any designer.
Advisory and Adaptive Communication Improves Trust in Autonomous Vehicle and Pedestrian Interaction
Authors: She Jinjuan 
Published: November 2020

Abstract
Autonomous vehicle (AV) is considered to be a significant part of the future of the automotive industry, with advantages such as higher transportation safety, less greenhouse gas emission, and wider transportation accessibility. However, the fruit of this technology cannot meet with much success in the market without an appropriate level of human trust, which might lead to refusing to adopt it, or using it in a wrong way. Therefore, except for improving safety of the technology itself, interactions between AV and human around it, such as pedestrians, are also paramount, especially effective communication. It is expected that certain communication could improve trust, and enable people to respond and act towards it accurately. This paper conducted a preliminary online study for a proof of concept that communication style (informative, advisory, and commanding) and communication strategy (single communication, adaptive communication) could affect pedestrian crossing decision process. The results demonstrate that advisory style improves trust in AVs when a Cross decision is expected by AVs, while both commanding and advisory styles improve trust in AVs when a Not Cross decision is expected by AVs. In addition, adaptive communication strategy improves trust significantly when AVs expect pedestrians to cross. This study helps understanding the communication between AV and pedestrians and is instrumental in developing more advanced AV communication mechanisms.
Memory and Idea Generation Applied to Product Repurposing
Authors: Arabian K. , Addis D. R. , Shu L. H. 
Published: November 2020

Abstract
Many engineering problems still require novel solutions, e.g., the repurposing of retired wind-turbine blades. Increasing evidence suggests that the recall of episodic memories enhances idea generation, but its application to engineering problems has been limited. The current work investigates the effectiveness of a memory induction on generating ideas. Engineering undergraduate students in a fourth-year design course (N = 38) completed a study under both of two conditions, a memory induction and a control (non-episodic-memory) induction. Participants underwent the induction before generating ideas on the Alternate Uses Task (AUT), a standard test of divergent thinking, and a wind-turbine-blade repurposing task (WRT).
AUT responses following the memory induction were deemed significantly more flexible (p = .045) and elaborate (p = .041) than responses following the control induction. No difference in response fluency (p = 0.205) followed the two inductions, possibly due to limited time allotted for the AUT. In line with this explanation, fluency was inversely related to elaboration. In the WRT, more appropriate (p = 0.009) and more feasible (p = 0.015) ideas for repurposing wind-turbine blades were generated following the memory than the control induction.
These results suggest that strategies increasing access to episodic memory may improve generation of alternative-use ideas for both common objects and wind-turbine blades.
Period-1 to Period-2 Motions in a Discontinuous Oscillator
Authors: Guo Siyu , Luo Albert C. J. 
Published: November 2020

Abstract
In this paper, grazing bifurcations on bifurcation trees in a discontinuous dynamical oscillator are discussed. Once the grazing bifurcation occurs, periodic motions switches from the old motion to a new one. Thus, grazing bifurcations on a bifurcation tree of period-1 to period-2 motions varying spring stiffness are presented in a discontinuous oscillator with three domains divided by circular boundaries. The stability and bifurcations of period-1 and period-2 motions are discussed. From analytical predictions, periodic motions are simulated numerically. Stiffness effects on the periodic motions are discussed. Such studies will help one understand parameter effects in discontinuous dynamical systems, which can be applied for system design and control.
Unified Motion Synthesis of Spatial Seven-Bar Platform Mechanisms and Planar-Four Bar Mechanisms
Authors: Sharma Shashank , Purwar Anurag 
Published: November 2020

Abstract
A unified motion generation algorithm that combines Spatial and Planar mechanism synthesis has been a hard problem in kinematics. In this paper, we present a new method to generate planar RRRR mechanisms and spatial 5-SS mechanisms using a unified algorithm. For a generalized spatial pose problem where all the poses fall on a plane, we show that there exist 1-∞ plane constraint solutions and 3-∞ planar-spherical solution dyads. We also show that for a spatial five pose problem where all poses lie on a plane, there exists a 2-∞ solution space of spherical and planar constraints. This multiplicity of solutions are intelligently constrained to find up to four circle constraints representing planar four-bar mechanism. Finally, examples are presented testing the proposed algorithm and verified using results from past publications.
Propulsion Dynamic Requirements Analysis for Multi-Axle Skid-Steer Wheeled Vehicles
Authors: Yacoub Mostafa , Ali Ahmed 
Published: November 2020

Abstract
Multi-axle skid-steer wheeled vehicles have the advantages of simplicity and enhanced traction. That’s why they are used in off-road environments and also in mobile robots. In the present work, a dynamic analysis of the propulsion system requirements for multi-axle wheeled vehicles is investigated. As the multi-axle wheeled vehicle differentially steers at a smaller turning radius, the driving torque requirements approach their peak. The adhesion at each tire of the multi-axle vehicle and its relation to the contact patches are analyzed. The analysis presented starts with four wheel drive, six wheel drive and eight wheel drive vehicles, then it is widened to n-wheel drive vehicles. A generic formula for obtaining the propulsion torque requirements for multi-axle skid-steer wheeled vehicles is presented. The analysis is extended to include experimental validation of the obtained analytical results. The experimental work includes three small electrically driven skid-steer vehicles; four wheel drive vehicle, six wheel drive vehicle and eight wheel drive vehicle. The selection of the drive motors for each of those vehicles was based on the proposed formula. Each of the three vehicles was tested in the worst case adhesion torque requirement. The experimental results showed that the proposed formula is capable, to a great extent, to predict the torque requirements for the multi-axle skid-steer wheeled vehicles in the design phase.
Path Synthesis of Defect-Free Spatial 5-SS Mechanisms Using Machine Learning
Authors: Sharma Shashank , Purwar Anurag 
Published: November 2020

Abstract
The synthesis of spatial mechanisms for defect-free path generation has not received a lot of attention. In this paper, we focus on the synthesis of 5-SS mechanisms and use a machine learning based approach. First, we create a coupler path database using a solver based on the iterative Newton-Raphson optimization algorithm. Subsequently, a data cleanup, normalization, balancing, and augmentation pipeline is established based on intrinsic properties of space curves namely curvature and torsion. Finally, we use an unsupervised learning algorithm based on Variational Autoencoder combined with K-means clustering to find a multiplicity of defect-free 5-SS mechanisms and examples are presented.
Analysis of Virtual Communication Within Engineering Design Teams and its Impact on Team Effectiveness
Authors: Adolphe Lauren , Van de Zande Georgia D. , Wallace David , Olechowski Alison 
Published: November 2020

Abstract
Online communication and collaboration tools are changing the way teams design products. The tools also generate a rich data source from which to study trends in communication. This paper focuses on how engineering teams utilize Slack, a popular team messaging software platform. We aim to better understand communication and coordination in product design teams via analysis of team social network dynamics, unique patterns of chat-like messaging (emoji usage), and the evolution of communication topics over time.
Our study analyzes the online interactions of 32 teams, sent during a 3-month senior undergraduate product design course. These 400,000+ messages represent the team communications from 4 years of teams, with 17–20 students per team.
We find that 1) Slack communications resulted in high density network maps, 2) network analysis of teams reveals that leaders have more central positions in the network, 3) strong teams have lower average centrality among members, equivalent to less public channel membership per person, 4) stronger teams use emojis at a higher rate, and 5) emojis are used most by leaders and highly connected members.
These findings represent preliminary foundations for best practices in online messaging, which may lead to more effective collaboration in product design.
Design of a Large Workspace Passive Spherical Joint via Contact Edge Design
Authors: Bajaj Neil M. , Dollar Aaron M. 
Published: November 2020

Abstract
This paper presents the design of a compact ball and socket type spherical joint that makes use of passive elements to increase the range of motion to greater than a hemisphere with infinite roll capacity. We discuss the limitations of typical spherical joints due to simple geometric considerations, and how the addition of redundancy, passive elements, and multiple contacting surfaces of differing geometry can increase the workspace of these joints. We discuss the relationship between kinematics, mechanical conditions (e.g. friction and contact forces) under quasistatic motion, and geometry required to achieve the increased range of motion. Furthermore, we provide a metric for assessing the viability or benefit of a potential design. Finally, we validate one of our designs with a physical prototype and demonstrate its achievable range of motion.
Cabozantinib-based combination therapy for the treatment of hepatocellular carcinoma
Authors: Shang Runze , Song Xinhua , Wang Pan , Zhou Yi , Lu Xinjun , Wang Jingxiao , Xu Meng , Chen Xinyan , Utpatel Kirsten , Che Li , Liang Binyong , Cigliano Antonio , Evert Matthias , Calvisi Diego F , Chen Xin 
Published: November 2020

ObjectiveHepatocellular carcinoma (HCC) is the most common type of primary liver cancer with limited treatment options. Cabozantinib, an orally bioavailable multikinase inhibitor is now approved by Food and Drug Administration (FDA) for HCC patients. We evaluated the therapeutic efficacy of cabozantinib, either alone or in combination, in vitro and in vivo.DesignHuman HCC cell lines and HCC mouse models were used to assess the therapeutic efficacy and targeted molecular pathways of cabozantinib, either alone or in combination with the pan-mTOR inhibitor MLN0128 or the checkpoint inhibitor anti-PD-L1 antibody.ResultsCabozantinib treatment led to stable disease in c-Met/β-catenin and Akt/c-Met mouse HCC while possessing limited efficacy on Akt/Ras and c-Myc liver tumours. Importantly, cabozantinib effectively inhibited c-MET and ERK activity, leading to decreased PKM2 and increased p21 expression in HCC cells and in c-Met/β-catenin and Akt/c-Met HCC. However, cabozantinib was ineffective in inhibiting the Akt/mTOR cascade. Intriguingly, a strong inhibition of angiogenesis by cabozantinib occurred regardless of the oncogenic drivers. However, cabozantinib had limited impact on other tumour microenvironment parameters, including tumour infiltrating T cells, and did not induce programmed death-ligand 1 (PD-L1) expression. Combining cabozantinib with MLN0128 led to tumour regression in c-Met/β-catenin mice. In contrast, combined treatment with cabozantinib and the checkpoint inhibitor anti-PD-L1 antibody did not provide any additional therapeutic benefit in the four mouse HCC models tested.Conclusionc-MET/ERK/p21/PKM2 cascade and VEGFR2-induced angiogenesis are the primary targets of cabozantinib in HCC treatment. Combination therapies with cabozantinib and mTOR inhibitors may be effective against human HCC.
An optimized HNO3 and HBF4 digestion method for multielemental soil and sediment analysis using inductively coupled plasma quadrupole mass spectrometry
Authors: Javed Muhammad Babar , Grant-Weaver Iain , Shotyk William 
Published: November 2020

A robust and reliable analytical procedure for the determination of trace (mg∙kg−1) and ultra-trace elements (μg∙kg−1) in soil and sediments by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) was optimized. Aliquots of ∼200 mg of two certified reference materials (IAEA Soil-7, soil and IAEA SL-1, lake sediments) were digested in nitric acid (HNO3) purified twice by sub-boiling distillation using a microwave-heated high-pressure autoclave. Incremental addition of tetrafluoroboric acid (HBF4, 0.1–2 mL) to HNO3 was evaluated for yield. The selection of appropriate proportions of digestion acids was crucial to obtain accurate results. Digested samples were analyzed for a range of trace elements including those that are potentially toxic (Ag, Cd, Pb, Sb, and Tl), plant micronutrients (Cu, Fe, Mn, and Zn), those enriched in bitumen (Mo, Ni, and V), and lithophile elements (Al, Ba, Co, Cr, Rb, Sr, Th, Ti, Y, and Zr). Nitric acid alone proved to be sufficient to completely liberate Cd, Co, Cr, Fe, Mn, Ni, Pb, V, and Zn in both soil and sediments (87%–120% recovery). For almost all the other elements, addition of HBF4 was needed for improved recovery. A combination of 3 mL of HNO3 and 1.5 mL of HBF4 was optimal to fully liberate an extended list of elements including Ba, Sb, and Sr from both the reference materials. Conservative lithophile elements (Th, Ti, Y, and Zr) could not be completely recovered with the proposed method, requiring hydrofluoric acid for complete dissolution of recalcitrant minerals.
Observational signatures of strongly naked singularities: image of the thin accretion disk
Authors: Gyulchev Galin , Kunz Jutta , Nedkova Petya , Vetsov Tsvetan , Yazadjiev Stoytcho 
Published: November 2020

AbstractWe study the optical appearance of a thin accretion disk around the strongly naked static Janis–Newman–Winicour singularity. The solution does not possess a photon sphere, which results in the formation of a complex structure of bright rings in the central region of the disk image. Such structure is absent in the case of the Schwarzschild black hole with a thin accretion disk, where instead of the image we observe the black hole shadow. Some of the rings emit with the maximal observable radiation flux from the accretion disk, and should be experimentally detectable. Thus, this qualitatively new feature can be used to distinguish observationally black holes from naked singularities. We elucidate the appearance of the ring structure by revealing the physical mechanism of its formation, and explaining the nature of each of the ring images. We make the conjecture that a similar structure would also appear for other solutions without a photon sphere and it can serve as a general observational signature for distinguishing compact objects possessing no photon sphere from black holes.
Physics-Based Modeling and Parameter Identification for Lithium Ion Batteries Under High Current Discharge Conditions
Authors: Kostetzer Lucas , Nebl Christoph , Stich Michael , Bund Andreas , Schweiger Hans-Georg 
Published: November 2020

Extreme scenarios of high discharge current must be understood for better battery management system design. Physics-based modeling can give a better insight into the battery response but can be challenging due to the large number of parameters. In this work, an electrochemical pseudo-2D model is developed and used in the parameter identification and validated under high current discharge conditions. Commercial 18 650 cells with maximum rated current of 20 A (13.3 C) are characterized with discharge rates up to 40 C under controlled thermal conditions. The proposed three-step parameter identification procedure starts with the open circuit voltage being used to estimate the equilibrium potentials. In a second step, kinetic parameters are identified under high current aided by a parameter sensitivity analysis and parameter optimization with an evolutionary algorithm. The third step is the verification by comparing simulation results with measurements resulting in root main square error under 89 mV for currents until 26.6 C. Limits of the model are explored in the 33.3 C case, where a parameter re-fit shows that polarization effects change for very high current.
KCNQ1
and Long QT Syndrome in 1/45 Amish
Authors: Streeten Elizabeth A. , See Vincent Y. , Jeng Linda B.J. , Maloney Kristin A. , Lynch Megan , Glazer Andrew M. , Yang Tao , Roden Dan , Pollin Toni I. , Daue Melanie , Ryan Kathleen A. , Van Hout Cristopher , Gosalia Nehal , Gonzaga-Jauregui Claudia , Economides Aris , Perry James A. , O’Connell Jeffrey , Beitelshees Amber , Palmer Kathleen , Mitchell Braxton D. , Shuldiner Alan R ,   Regeneron Genetics Center*
Published: November 2020

Background:
In population-based research exome sequencing, the path from variant discovery to return of results is not well established. Variants discovered by research exome sequencing have the potential to improve population health.

Methods:

Population-based exome sequencing and agnostic ExWAS were performed 5521 Amish individuals. Additional phenotyping and in vitro studies enabled reclassification of a
KCNQ1
variant from variant of unknown significance to pathogenic. Results were returned to participants in a community setting.

Results:

A missense variant was identified in
KCNQ1
(c.671C>T, p.T224M), a gene associated with long QT syndrome type 1, which can cause syncope and sudden cardiac death. The p.T224M variant, present in 1/45 Amish individuals is rare in the general population (1/248 566 in gnomAD) and was highly associated with QTc on electro-cardiogram (
P
=5.53E-24, β=20.2 ms/allele). Because of the potential importance of this variant to the health of the population, additional phenotyping was performed in 88 p.T224M carriers and 54 noncarriers. There was stronger clinical evidence of long QT syndrome in carriers (38.6% versus 5.5%,
P
=0.0006), greater history of syncope (32% versus 17%,
P
=0.020), and higher rate of sudden cardiac death in first degree relatives<age 30 (4.5% versus 0%,
P
=0.026). Expression of p.T224M KCNQ1 in Chinese hamster ovary cells showed near complete loss of protein function. Our clinical and functional data enabled reclassification of p.T224M from a variant of unknown significance to pathogenic. Of the 88 carriers, 93% met criteria for beta-blocker treatment and 5/88 (5.7%) were on medications that may further prolong QTc. Carriers were provided a Clinical Laboratory Improvement Amendments confirmed report, genetic counseling, and treatment recommendations. Follow-up care was coordinated with local physicians.

Conclusions:
This work provides a framework by which research exome sequencing can be rapidly translated in a culturally appropriate manner to directly benefit research participants and enable population precision health.