bluuebunny/crossref_metadata_2025 huggingface dataset:
A Weighted Network Modeling Approach for Analyzing Product Competition
Authors: Cui Yaxin , Ahmed Faez , Sha Zhenghui , Wang Lijun , Fu Yan , Chen Wei
Published: November 2020

Statistical network models allow us to study the co-evolution between the products and the social aspects of a market system, by modeling these components and their interactions as graphs. In this paper, we study competition between different car models using network theory, with a focus on how product attributes (like fuel economy and price) affect which cars are considered together and which cars are finally bought by customers. Unlike past work, where most systems have been studied with the assumption that relationships between competitors are binary (i.e., whether a relationship exists or not), we allow relationships to take strengths (i.e., how strong a relationship is). Specifically, we use valued Exponential Random Graph Models and show that our approach provides a significant improvement over the baselines in predicting product co-considerations as well as in the validation of market share. This is also the first attempt to study aggregated purchase preference and car competition using valued directed networks.
Environmental and Economic Impacts of Nitrogen Trifluoride at an Idaho Semiconductor Facility
Authors: Thompson Matthew A. , Mohajeri Amir , Mirkouei Amin
Published: November 2020

Nitrogen Trifluoride (NF3) is an inorganic compound widely used in the electronics industry for manufacturing various products, such as semiconductors, solar panels, and touch screens. However, NF3 emissions that accumulate in the atmosphere have 17,200 times the global warming potentials of CO2 over a 100-year time horizon. The abatement efficiency for NF3 is high, although some amount of NOx is generated. This study aims to provide economic and environmental impact assessments on the use of NF3. Life cycle assessment method is applied for evaluating environmental aspects. Additionally, a real case study for the Idaho semiconductor facility is used to assess the method and demonstrate the application of this study. The results show that slight reductions in abatement efficiency have dramatic impacts on mitigating greenhouse gas (GHG) emissions. Even small unplanned releases of NF3, either through mechanical failure or human error, have significant environmental impacts, and every reasonable effort should be taken to avoid such incidents. The results also indicate that the cost of abatement is the primary driver of economic impact. It is found that the considerable distance from the chemical plant in Arizona to the point of use in Idaho contributed a minor portion of GHGs associated with the use of NF3. It is also found that contaminants (e.g., SF6 and CF4) within the cylinder potentially have more substantial GHG impacts than the actual NF3, owing in part to the relative ease with which NF3 is destroyed through abatement.
Organic Piezoresistive Pressure Sensitive Robotic Skin for Physical Human-Robot Interaction
Authors: Wei Danming , Zhang Ruoshi , Saadatzi Mohammad N. , Olowo Olalekan O. , Popa Dan O.
Published: November 2020

Pressure sensitive robotic skins have long been investigated for applications to physical human-robot interaction (pHRI). Numerous challenges related to fabrication, sensitivity, density, and reliability remain to be addressed under various environmental and use conditions. In our previous studies, we designed novel strain gauge sensor structures for robotic skin arrays. We coated these star-shaped designs with an organic polymer piezoresistive material, Poly (3, 4-ethylenedioxythiophene)-ploy(styrenesulfonate) or PEDOT: PSS and integrated sensor arrays into elastomer robotic skins. In this paper, we describe a dry etching photolithographic method to create a stable uniform sensor layer of PEDOT:PSS onto star-shaped sensors and a lamination process for creating double-sided robotic skins that can be used with temperature compensation. An integrated circuit and load testing apparatus was designed for testing the resulting robotic skin pressure performance. Experiments were conducted to measure the loading performance of the resulting sensor prototypes and results indicate that over 80% sensor yields are possible with this fabrication process.
Scalable Objective-Driven Batch Sampling in Simulation-Based Design for Models With Heteroscedastic Noise
Authors: van Beek Anton , Farooq Ghumman Umar , Munshi Joydeep , Tao Siyu , Chien TeYu , Balasubramanian Ganesh , Plumlee Matthew , Apley Daniel , Chen Wei
Published: November 2020

Objective-driven adaptive sampling is a widely used tool for the optimization of deterministic black-box functions. However, the optimization of stochastic simulation models as found in the engineering, biological, and social sciences is still an elusive task. In this work, we propose a scalable adaptive batch sampling scheme for the optimization of stochastic simulation models with input-dependent noise. The developed algorithm has two primary advantages: (i) by recommending sampling batches, the designer can benefit from parallel computing capabilities, and (ii) by replicating of previously observed sampling locations the method can be scaled to higher-dimensional and more noisy functions. Replication improves numerical tractability as the computational cost of Bayesian optimization methods is known to grow cubicly with the number of unique sampling locations. Deciding when to replicate and when to explore depends on what alternative minimizes the posterior prediction accuracy at and around the spatial locations expected to contain the global optimum. The algorithm explores a new sampling location to reduce the interpolation uncertainty and replicates to improve the accuracy of the mean prediction at a single sampling location. Through the application of the proposed sampling scheme to two numerical test functions and one real engineering problem, we show that we can reliably and efficiently find the global optimum of stochastic simulation models with input-dependent noise.
A Formal Representation of Conjugate Verbs in Function Modeling
Authors: Chowdhury Ahmed , Venkatanarasimhan Lakshmi N. A. , Sen Chiradeep
Published: November 2020

Many modern and innovative design problems require multi-modal, reconfigurable solutions. Function modeling is a common tool used to explore solutions in early stages of mechanical engineering design. Currently, function structure representations do not support the modeling of formally-defined reconfigurable function models. There is a well-established need in function modeling to dynamically capture the effects of state change of a flow property on the operating mode of the system. This paper presents a formal representation to capture the duality of specific functions, and illustrates it through three verbs that shift from one mode of operation to its logical and topological opposite, based on the existence of, or the value of a signal from, an input flow. Additionally, an approach to extend these functions to function features, in order to support physics-based reasoning on the interactions between flows is also presented. Through the example of a system-level model of a geothermal heat pump operating in its heating mode, the representation demonstrates the ability to support causal reasoning on functional modes of systems, provides quantitative reasoning on the efficiency of those modes, and illustrates the modeling efficacy of the extended representation.
Investigating the Coupled Effects Between Rotor-Blade Aeroelasticity and Tip Vortex Stability
Authors: Rodriguez Steven N. , Iliopoulos Athanasios P. , Michopoulos John G. , Jaworski Justin W.
Published: November 2020

The relationship between rotor-blade aeroelasticity and tip-vortex stability is investigated numerically. An aeroelastic framework based on the free-vortex wake and finite element methods is employed to model a subscaled helicopter rotor in hover and forward-tilted conditions. A linear eigenvalue stability analysis is performed on tip vortices to associate the coupled impact of aeroelastic effects and vortex evolution. Prior numerical investigations have shown that highly flexible wind turbine rotor-blades have the potential to decrease levels of the instability of tip vortices. The present work focuses on testing these findings against a subscaled rotor within the range of helicopter operational rotation frequencies. The presented work aims to develop further insight into rotor-wake interactions and blade-vortex interaction to explore the mitigation of adverse rotorcraft operational conditions, such as their effect on aerodynamic-induced airframe vibrations and the associated life-cycle fatigue performance.
Incorporating Contextual Factors Into a Design Process: An Analysis of Engineering for Global Development Literature
Authors: Burleson Grace , Sienko Kathleen H. , Toyama Kentaro
Published: November 2020

It is frequently suggested that designing artifacts requires a deep understanding of context. We analyzed 186 papers from three specific literature searches involving a design process for global development applications. Each paper was reviewed and coded for (1) whether or not the study teams performed some level of contextual investigation, (2) the methods and/or approaches for understanding the artifact’s context, and (3) use of open-ended analysis or framework-based analysis for qualitative contextual investigation. In total, 159 papers (85%) described some level of contextual investigation with 46 of these describing performance-focused field tests in the artifact’s context of use and 113 papers using qualitative methods for contextual investigation. 18 papers used a framework, such as a cited questionnaire, for analyzing their contextual data, overwhelmingly during needs assessment and validation stages of design. We find that study teams of every paper motivated their design with contextual information, but there was great diversity in how context was investigated, analyzed, and described. Few linked their design decisions to specific contextual factors. We recommend that researchers include detailed description of methods and contextual factors considered during their design process to improve the transferability and repeatability of design approaches.
Using Network Partitioning to Design a Green Supply Chain
Authors: Williams Jack , Alizadeh Reza , Allen Janet K. , Mistree Farrokh
Published: November 2020

In supply chain network design, a retailer may determine the number and locations of facilities based on the cost of opening the facility, a customer driving to the facility, and a replenishment truck driving to the facility from a warehouse. However, this does not include the system’s greenhouse gas (GHG) emissions. Given the existential threat posed by global warming, it is pertinent to consider how the design of the system affects its GHG emissions. We model the supply chain as a network of customers and store locations, with customers driving in cars to and from stores and the retailer resupplying the stores from a central warehouse. The number and location of stores is determined while minimizing the GHG emission. Our contributions are (1) to remove the assumption of uniform demand, and instead build a model of a GSC based on population data; (2) to model the GSC as a two-echelon k-median problem. We conduct a sensitivity analysis to study the effect of a carbon tax in encouraging a greener system considering various scenarios under which emissions might increase or decrease. Specific scenarios lead to a lower overall GHG emission. For example, doubling the fuel efficiency of cars decreases emissions by 46% compared to the baseline scenario. The proposed design approach is not limited to GSC design and can be extended to many design problems, including manufacturing, material design, and healthcare.
Design and Modeling of a Variable Stiffness Barrel Mechanism for Ankle Exoskeleton
Authors: Soliman Ali M. , Hussain Irfan , Awad Mohammad I. , Gan Dongming
Published: November 2020

In this paper, we present a novel variable-stiffness joint for a walking assistance ankle exoskeleton. This design is adaptive to user needs in the sense that it can aid in different types of motion, i.e. walking, jogging and running, through different stiffness levels. We created a concept that utilizes multiple springs that could contort into different orientations in order to create a fully compliant ankle exoskeleton. The design provides a wide range of assistive torques without constant replacement of parts or springs for each type of activity. This design can be utilized by a wide range of people engaging in different types of activities. Those could be individuals with an active lifestyle or the elderly suffering from muscular atrophy.
Analytical Mechatronic Modeling and Analysis for Anti-Walkout of PTU Actuator With ADAMS-Simulink Co-Simulation
Authors: Liao Cong , Zhang Haiyan H. , Berry Fred , Chung Jerry , Dessai Ravi
Published: November 2020

A spline clutch maneuvered by an actuator provides a Power Transfer Unit (PTU), the functions of power disconnection, or speed selection. In the driveline system, the PTU actuator is the core mechatronic component to realize the essential functionality. This paper focuses on increasing the performance and stability of the PTU using analytical mechatronic modeling and analysis with ADAMS-Simulink co-simulation. By utilizing the Adams, the PTU was modeled, and the characteristics of the sleeve walk-out were revealed. The motor and partial mechanical components were modeled in the Simulink and combined with the Adams model for co-simulation. The fuzzy logic with PID position control is developed to suppress the on-set of the walk-out. The effectiveness of the control strategy was validated by the co-simulation. This method can be extended to other actuators with spline clutch applications to minimize the risk of walk-out.
Design of Trustworthy Cyber-Physical-Social Systems With Discrete Bayesian Optimization
Authors: Wang Yan
Published: November 2020

Cyber-physical-social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently a trust quantification method was proposed to measure trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. In this paper, the applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. A Bayesian optimization method is developed to perform trust based CPSS network design, where the most trustworthy network with respect to a reference node can be selected to collaborate and share information with.
Machine Learning Augmentation in Micro-Sensor Assemblies
Authors: Hasan Mohammad H. , Alsaleem Fadi , Abbasalipour Amin , Pourkamali Anaraki Siavash , Emad-Un-Din Muhammad , Jafari Roozbeh
Published: November 2020

The size and power limitations in small electronic systems such as wearable devices limit their potential. Significant energy is lost utilizing current computational schemes in processes such as analog-to-digital conversion and wireless communication for cloud computing. Edge computing, where information is processed near the data sources, was shown to significantly enhance the performance of computational systems and reduce their power consumption. In this work, we push computation directly into the sensory node by presenting the use of an array of electrostatic Microelectromechanical systems (MEMS) sensors to perform colocalized sensing-and-computing. The MEMS network is operated around the pull-in regime to access the instability jump and the hysteresis available in this regime. Within this regime, the MEMS network is capable of emulating the response of the continuous-time recurrent neural network (CTRNN) computational scheme. The network is shown to be successful at classifying a quasi-static input acceleration waveform into square or triangle signals in the absence of digital processors. Our results show that the MEMS may be a viable solution for edge computing implementation without the need for digital electronics or micro-processors. Moreover, our results can be used as a basis for the development of new types of specialized MEMS sensors (ex: gesture recognition sensors).
Dichotomy of Design Experience: A Case Study of One Student’s Experience With Problem Typology and His Perceptions of Design
Authors: Olewnik Andrew , Yerrick Randy , Simmons Amanda , Lee Yonghee
Published: November 2020

This paper presents a case study of Jeff, a mechanical engineering senior, and his experience with design in two different contexts — one in the classroom and one extracurricular. After a year-long study of undergraduate engineers, Jeff revealed marked differences in his uptake of design principles and reflexivity toward his thinking within the discipline. We explored with Jeff the critical differences and experiences that led to his changes once we had completed data collection with his peer cohort of undergraduates. We explored Jeff’s interpretation of the differences he considered as positive changes, the attributes of applying principles of problem typology, and the requisite context required to achieve these changes as a student. Through qualitative analysis four assertions are examined — improved approach to design problem solving, broadened view of design, engineering as multiple types of problems, and relevance to the profession — and validated through a member check. Potential implications for engineering education, especially as it pertains to design education are briefly described.
Expected Uncertainty Reduction for Sequential Kriging-Based Reliability Analysis
Authors: Li Meng , Shen Sheng , Barzegar Vahid , Sadoughi Mohammadkazem , Laflamme Simon , Hu Chao
Published: November 2020

Several acquisition functions have been proposed to identify an optimal sequence of samples in sequential kriging-based reliability analysis. However, no single acquisition function provides better performance over the others in all cases. To address this problem, this paper proposes a new acquisition function, namely expected uncertainty reduction (EUR), that serves as a meta-criterion to select the best sample from a set of optimal samples, each identified from a large number of candidate samples according to the criterion of an acquisition function. EUR directly quantifies the expected reduction of the uncertainty in the prediction of limit-state function by adding an optimal sample. The uncertainty reduction is quantified by sampling over the kriging posterior. In the proposed EUR-based sequential sampling framework, a portfolio that consists of four acquisition functions is first employed to suggest four optimal samples at each iteration of sequential sampling. Then, EUR is employed as the meta-criterion to identify the best sample among those optimal samples. The results from two mathematical case studies show that (1) EUR-based sequential sampling can perform as well as or outperform the single use of any acquisition function in the portfolio, and (2) the best-performing acquisition function may change from one problem to another or even from one iteration to the next within a problem.
Evaluating Supply Chain Resource Limits From News Articles and Earnings Call Transcripts: An Application of Integrated Factor Analysis and Analytical Network Process
Authors: Chu Chih-Yuan , Gunay Elif E. , Al-Araidah Omar , Kremer Gül E.
Published: November 2020

Due to the impact of globalization, companies have extended their borders across nations to launch products more competitively. However, globalization affects various uncertainties and risks that may limit the performance of supply chains. Research indicates that models that incorporate uncertainties and risks will help to improve the resilience of global supply chains. In the era of technology, we experience the abundance of textual data from various web-media resources related to companies, which can be deployed to understand the impact of risks on the chain. Accordingly, this study aims to utilize textual data collected from news articles and earnings call transcripts to assess the vulnerability of the suppliers and the chain. Among many, we considered supply chain resource limits as a subcomponent of vulnerability and collected textual data associated with its sub-factors. Then, we proposed an integrated factor analysis and Analytical Network Process (ANP) method to model the company’s supply chain resource limits index. Specifically, factor analysis was used to determine the latent constructs of the variables that are grouped under resource limits and their correlations. This latent construct and correlations were then applied as the interdependencies among variables in the ANP to discover the final importance weights of the variables in terms of supply chain resource limits. The results of the study showed that the shortages of capacity, components, and energy supply are the most critical sub-factors. The company’s supply chain resource limits index (SCRLI) can be further calculated to assist decision-makers of an enterprise in supply chain configuration design, and improve the supply chain resilience.
The Impact of Prototyping Strategies on Crowdfunding Success
Authors: Srinivasan Sriram , Li Zhuoxuan Fanny , Han Yu Lee , Camburn Bradley A.
Published: November 2020

Innovative design and technology startups often struggle to gain market success when launching a new product. Research in business management highlights the impact of strategic marketing to foster launch success. Prototyping plays a critical role in demonstrating the potential of the said new technologies and innovations into the market. Prototypes can engage users or highlight the potential of an opportunity to investors. The design performance impact of prototyping strategies has been evaluated in recent studies. This work explores the impact that strategic prototyping (defined here as the use of techniques such as: subsystem isolation, or scale modeling), has on market outcome. Pilot analysis of two hundred launch campaigns on the marketing and sales platform - Kickstarter.com, is conducted. This database provides clear documentation of the information that is provided to said investors or ‘backers’, and resulting funds received. The relative usage frequency of various strategies is reported from a subset of product launch efforts after which the correlations between the demonstration of the strategies and funding received is calculated. These preliminary observations may support designers in managing project resources while developing prototypes to launch new products.
Reliability-Informed Life-Cycle Warranty Cost Analysis: A Case Study on a Transmission in Agricultural Equipment
Authors: Li Meng , Liu Jinqiang , Nemani Venkat Pavan , Ahmed Navaid , Kremer Gül E. , Hu Chao
Published: November 2020

In agricultural and industrial equipment, both new and remanufactured systems are often available for warranty coverage. In such cases, it may be challenging for equipment manufacturers to properly trade-off between the system reliability and the cost associated with a replacement option (e.g., replace with a new or remanufactured system). To address this problem, we present a reliability-informed life-cycle warranty cost (LCWC) analysis framework that enables equipment manufacturers to evaluate different warranty policies. These warranty policies differ in whether a new or remanufactured system is used for replacement in the case of product failure. The novelty of this LCWC analysis framework lies in its ability to incorporate real-world field reliability data into warranty policy assessment using probabilistic warranty cost models that consider multiple life cycles. First, the reliability functions for the new and remanufactured systems are built as the time-to-failure distributions that provide the best-fit to the field reliability data. Then, these reliability functions and their corresponding warranty policies are used to build the LCWC models according to the specific warranty terms. Finally, Monte Carlo simulation is used to propagate the time-to-failure uncertainty of each system, modeled by its reliability function, through each LCWC model to produce a probability distribution of the LCWC. The effectiveness of the proposed reliability-informed LCWC analysis framework is demonstrated with a real-world case study on a transmission used in some agricultural equipment.
Architecting the Cooperative 3D Printing System
Authors: Poudel Laxmi , Marques Lucas Galvan , Williams Robert Austin , Hyden Zachary , Guerra Pablo , Fowler Oliver Luke , Moquin Stephen Joe , Sha Zhenghui , Zhou Wenchao
Published: November 2020

Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple mobile 3D printing robots work together cooperatively to print the desired part. At the core of C3DP lies the chunk-based printing strategy. This strategy splits the desired part into smaller chunks, and then the chunks are assigned and scheduled to be printed by individual printing robots. In our previous work, we presented various hardware and software components of C3DP, such as mobile 3D printers, chunk-based slicing, scheduling, and simulation. In this study, we present a fully integrated and functional C3DP platform with all necessary components, including chunker, slicer, scheduler, printing robots, build floor, and outline how they work in unison from a system-level perspective. To realize C3DP, new developments of both hardware and software are presented, including new chunking approaches, scalable scheduler for multiple robots, SCARA-based printing robots, a mobile platform for transporting printing robots, modular floor tiles, and a charging station for the mobile platform. Finally, we demonstrate the capability of the system using two case studies. In these demonstrations, a CAD model of a part is fed to the chunker, divided into smaller chunks, passed to the scheduler, and assigned and scheduled to be printed by the scheduler with a given number of robots. The slicer generates G-code for each of the chunks and combines G-code into one file for each robot. The simulator then uses the G-code generated by the slicer to generate animations for visualization purposes.
Vibration Suppression of a Harmonically Forced Oscillator Using a Passive Nonlinear Vibration Absorber
Authors: Yu Bo
Published: November 2020

In this paper, the performance of a nonlinear vibration absorber with different nonlinearity is studied. The analytical solutions of periodic motions are obtained using the general harmonic balance method. As the nonlinear strength is weak, the effectiveness of the absorber is discussed. For strong nonlinearities, unstable parodic motions can be obtained and stabilities of the periodic motions are determined through the eigenvalue analysis. The Hopf and saddle bifurcations are observed. Numerical simulations are illustrated for both masses at the resonance peaks. The harmonic amplitude spectrums show the harmonic effects on periodic motions, and the corresponding accuracy of approximate analytical solutions.
Uncertainty Quantification With Maximum Entropy Method for Fatigue Life Estimation
Authors: Nielsen S. M. , Hougaard H. A. , Balling O.
Published: November 2020

Use of high-fidelity fatigue models that incorporate not only material uncertainty but also part variability and operational uncertainties can improve the accuracy of predictive maintenance and thus decrease operational cost. However, due to the large number of computationally expensive cost function evaluations necessary, little work has been done to explore this field. In this research, the expected life probability distributions with low computational cost is estimated through a general statistical framework that applies Maximum Entropy Method (MEM), fractional statistical moments and Multiplicative Dimensional Reduction (M-DRM). The framework is tested on advanced models of a 6204 SKF ball bearing. The influence of critical part tolerances and load conditions on fatigue life with a probability density function with only 80 function evaluations is quantified in both a finite element analysis and a non-linear analytical model. The number of function evaluations is one order of magnitude lower than necessary for a comparable accuracy achieved by Monte Carlo simulation.
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs
Authors: Chen Wei , Ahmed Faez
Published: November 2020

Deep generative models are proven to be a useful tool for automatic design synthesis and design space exploration. When applied in engineering design, existing generative models face three challenges: 1) generated designs lack diversity and do not cover all areas of the design space, 2) it is difficult to explicitly improve the overall performance or quality of generated designs, and 3) existing models generate do not generate novel designs, outside the domain of the training data. In this paper, we simultaneously address these challenges by proposing a new Determinantal Point Processes based loss function for probabilistic modeling of diversity and quality. With this new loss function, we develop a variant of the Generative Adversarial Network, named “Performance Augmented Diverse Generative Adversarial Network” or PaDGAN, which can generate novel high-quality designs with good coverage of the design space. Using three synthetic examples and one real-world airfoil design example, we demonstrate that PaDGAN can generate diverse and high-quality designs. In comparison to a vanilla Generative Adversarial Network, on average, it generates samples with 28% higher mean quality score with larger diversity and without the mode collapse issue. Unlike typical generative models that usually generate new designs by interpolating within the boundary of training data, we show that PaDGAN expands the design space boundary outside the training data towards high-quality regions. The proposed method is broadly applicable to many tasks including design space exploration, design optimization, and creative solution recommendation.
A Methodological Framework for Making the Transition From Traditional Innovation Teaching Towards Serious Games
Authors: Ma Yiming , Vallet Flore , Cluzel François , Yannou Bernard
Published: November 2020

Serious games (SGs) are motivational and practical pedagogical tools that have been widely used in design education. SGs seem to be an efficient way to give instructions on innovation processes (IPs), offering unique and attractive environments to support situated learning. While there has been much interest in SGs of the IPs type, there is very little research about the design framework to reduce the complexity and time consumption of their design process. This paper presents the preliminary results of our ongoing study: a design framework adapted to innovation SGs. The framework integrates eight general design frameworks/models/methodologies for SGs. Besides, it introduces a new stage “analysis of traditional teaching experience,” which conducive to the early phases of the design. We use a case study to prove the value of this stage. First, it aids designers in defining the teaching objectives of innovation SGs, that is, choosing required competencies from innovation competency frameworks. More importantly, it helps identify game mechanics that may contribute to the realization of teaching objectives. This stage should support designers successfully making the transition from traditional innovation teaching towards SGs.
A Primal Treatise of Constant-Force, Compliant Segments and Mechanisms
Authors: Midha Ashok , Lodagala Vamsi , Bagivalu Prasanna Pratheek , Komatireddy Jyothi
Published: November 2020

The evolution of constant-force mechanisms is propelled by a growing interest in being able to exert constant or near-constant force in various applications. Compliant mechanisms have recently received much attention in the design of constant-force mechanisms because of their several advantages, e.g. fewer parts, compact construct, natural energy storage, no backlash, among many others. There have been many research efforts in developing various techniques to design these mechanisms for applications in diverse fields. Several of these techniques require design optimization to generate a constant force over a desired range of motion. There is generally a lack of understanding of the mechanics of the generation of constant force. This paper presents the hypothesis that simple arrangements, such as a rigid link with a torsional spring, or compliant segments, under axial loading are capable of producing constant force. Three compliant segment types are considered herein: fixed-free, pinned-pinned, and fixed-guided beams under axial loading, to demonstrate that they can exert near-constant force, without the need for a design optimization. This paper further exemplifies that the proposed theory is the kernel to generating constant force by different mechanism configurations.
Validation of a High-Fidelity Finite Element Tire Model on Pavement
Authors: Wasfy Tamer , Wasfy Hatem , Jayakumar Paramsothy , Sanikommu Srinivas
Published: November 2020

The objective of this study is to validate a high-fidelity finite element tire model on hard pavement. In this model, the tire rubber matrix is modeled using locking-free brick elements with embedded thin beam elements along the tire’s circumference, meridian, and diagonals for modeling the tire’s reinforcements (belt, ply and bead). The internal air pressure is applied as a distributed force on the inner surface of the brick elements. Frictional contact between the outer surface of the brick elements and the pavement is modeled using the penalty method along with an asperity based Coulomb friction model. In order to validate the tire model, a medium duty truck tire is modeled and the following response quantities are compared to experimental results: (1) normal load versus deflection at different tire pressures; (2) rolling resistance versus speed; (3) longitudinal force versus slip; (4) lateral force versus slip angle for different normal loads; and (5) self-aligning torque versus slip angle for different normal loads.
Investigation of Printing Parameters of Additive Manufacturing Process for Sustainability Using Design of Experiments
Authors: Khalid Marwan , Peng Qingjin
Published: November 2020

Additive Manufacturing (AM) offers many advantages to make objects compared to traditional subtractive manufacturing, for example, complex geometries can be easily fabricated, and light weight parts can be formed while maintaining the parts strength for the low carbon footprint, low material consumption and waste. But there are areas for AM to improve in sustainability, reliability, productivity, robustness, material diversity and part quality. Life cycle assessment (LCA) studies have identified that the AM printing stage has a big impact on the life cycle sustainability (LCS) of 3D printed products. AM building parameters can be properly selected to control the LCS. This research explores the optimal AM process parameters to reduce the process energy and material consumption. Investigated parameters include the printing layer height, number of shells, material infilling percentage, infilling type and building orientation. Design of experiments (DOE) approach and statistical analysis tools are used to find optimal parameter settings for sustainable AM. Models formulated in this research can be easily extended to other additive manufacturing processes.
An Approach for Representing and Evaluating User Tactics in Early Stage Product Development
Authors: Owens Trent , Mattson Christopher A. , Sorensen Carl D. , Stapleton Tyler , Anderson Michael L.
Published: November 2020

Frequent and effective design evaluation is foundational to the success of any product development effort. Products that will be used, installed, or otherwise handled by humans would benefit from both an evaluation of the product itself (the physical embodiment of the technology, termed technology), and the steps a user should take to use that technology (termed tactics). Current methods for the evaluation of tactics are scattered across multiple research areas, and are often inaccessible to engineers who have no prior experience with them. Furthermore, the existing tactics evaluation methods often focus mostly on the use of a product and do not simultaneously consider technological performance. In this paper we present a method for the simultaneous evaluation of tactics and technology during the conceptual design stage. To achieve this, we propose three contributions; an approach for representing tactics concepts, a set of criteria for tactics evaluations, and a means for presenting the results of the technology/tactics evaluation to facilitate team ideation.
The nucleus measures shape changes for cellular proprioception to control dynamic cell behavior
Authors: Venturini Valeria , Pezzano Fabio , Català Castro Frederic , Häkkinen Hanna-Maria , Jiménez-Delgado Senda , Colomer-Rosell Mariona , Marro Monica , Tolosa-Ramon Queralt , Paz-López Sonia , Valverde Miguel A. , Weghuber Julian , Loza-Alvarez Pablo , Krieg Michael , Wieser Stefan , Ruprecht Verena
Published: November 2020

The nucleus makes the rules

Single cells continuously experience and react to mechanical challenges in three-dimensional tissues. Spatial constraints in dense tissues, physical activity, and injury all impose changes in cell shape. How cells can measure shape deformations to ensure correct tissue development and homeostasis remains largely unknown (see the Perspective by Shen and Niethammer). Working independently, Venturini
et al.
and Lomakin
et al.
now show that the nucleus can act as an intracellular ruler to measure cellular shape variations. The nuclear envelope provides a gauge of cell deformation and activates a mechanotransduction pathway that controls actomyosin contractility and migration plasticity. The cell nucleus thereby allows cells to adapt their behavior to the local tissue microenvironment.

Science
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295
Patterning and growth control in vivo by an engineered GFP gradient
Authors: Stapornwongkul Kristina S. , de Gennes Marc , Cocconi Luca , Salbreux Guillaume , Vincent Jean-Paul
Published: November 2020

Engineering synthetic morphogens

Morphogens provide positional information during tissue development. For this behavior to occur, morphogens must spread out and form a concentration gradient; however, their mechanism of transport remains a matter of debate. Stapornwongkul
et al.
now show that in the presence of extracellular binding elements (binders), the inert green fluorescent protein (GFP) can form a detectable concentration gradient by diffusion in the developing fly wing (see the Perspective by Barkai and Shilo). When combining the expression of nonsignaling binders and receptors engineered to respond to GFP, a synthetic GFP gradient can substitute for a natural morphogen to organize growth and patterning. In related work, Toda
et al.
also show that GFP can be converted into a morphogen by providing anchoring interactions that tether the molecule, forming a gradient that can be recognized by synthetic receptors that activate gene expression. These synthetic morphogens can be used to program de novo multidomain tissue patterns. These results highlight core mechanisms of morphogen signaling and patterning and provide ways to program spatial tissue organization independently from endogenous morphogen pathways.

Science
, this issue p.
321
, p.
327
; see also p.
292
Tales from times long past
The Sediments of Time: My Lifelong Search for the Past
Meave Leakey with Samira Leakey
Houghton Mifflin Harcourt, 2020. 400 pp.
Authors: King Barbara J.
Published: November 2020

Field adventures and human origin stories combine in a paleoanthropologist's compelling new memoir
New Perspectives on Antimicrobial Agents: Remdesivir Treatment for COVID-19
Authors: Aleissa Muneerah M. , Silverman Emily A. , Paredes Acosta Luisa M. , Nutt Cameron T. , Richterman Aaron , Marty Francisco M.
Published: November 2020

Remdesivir was recently approved by the Food and Drug Administration for the treatment of hospitalized patients with coronavirus disease 2019 (COVID-19). Remdesivir is the prodrug of an adenosine analogue that inhibits viral replication of several RNA virus families, including
Coronaviridae
. Preclinical data in animal models of coronavirus diseases, including COVID-19, have demonstrated that early treatment with remdesivir leads to improved survival, decreased lung injury, and decreased levels of viral RNA.
Targeting Neuropilin-1 Suppresses the Stability of CD4
+
CD25
+
Regulatory T Cells via the NF-κB Signaling Pathway in Sepsis
Authors: Gao Yu-lei , Wang Chun-xue , Wang Zi-yi , Li Wen-jie , Liu Yan-cun , Shou Song-tao , Chai Yan-fen
Published: November 2020

Neuropilin-1 (Nrp-1) contributes to maintaining the stability of CD4
+
CD25
+
regulatory T cells (T
regs
). We investigated the impact of Nrp-1 on the stability of CD4
+
CD25
+
T
regs
, and the underlying signaling pathways, in a model of sepsis. Splenic CD4
+
CD25
+
T
regs
were either treated with anti-Nrp-1, transfected to silence Nrp-1 and inhibitor of NF-κB kinase subunit beta (IKKβ), or administered ammonium pyrrolidine dithiocarbamate (PDTC), followed by recombinant semaphorin 3A (rSema3A), in a simulation of sepsis.
Novel Effective Bacillus cereus Group Species “
Bacillus clarus
” Is Represented by Antibiotic-Producing Strain ATCC 21929 Isolated from Soil
Authors: Méndez Acevedo Marysabel , Carroll Laura M. , Mukherjee Manjari , Mills Emma , Xiaoli Lingzi , Dudley Edward G. , Kovac Jasna
Published: November 2020

The
B. cereus
group comprises numerous closely related lineages with various degrees of pathogenic potential and industrial relevance. Species-level taxonomic classification of
B. cereus
group strains is important for risk evaluation and communication but remains challenging. Biochemical and phenotypic assays are often used to assign
B. cereus
group strains to species but are insufficient for accurate taxonomic classification on a genomic scale. Here, we show that antibiotic-producing ATCC 21929 represents a novel lineage within the
B. cereus
group that, by all metrics used to delineate prokaryotic species, exemplifies a novel effective species. Furthermore, we show that ATCC 21929 is incapable of producing enterotoxins Hbl and Nhe or exhibiting cytotoxic effects on HeLa cells at human body temperature
in vitro
. These results provide greater insight into the genomic and phenotypic diversity of the
B. cereus
group and may be leveraged to inform future public health and food safety efforts.
Discovering the Molecular Determinants of Phaeobacter inhibens Susceptibility to Phaeobacter Phage MD18
Authors: Urtecho Guillaume , Campbell Danielle E. , Hershey David M. , Hussain Fatima A. , Whitaker Rachel J. , O’Toole George A.
Published: November 2020

Bacteriophages are useful nonantibiotic therapeutics for bacterial infections as well as threats to industries utilizing bacterial agents. This study identified
Phaeobacter virus MD18
, a phage antagonist of
Phaeobacter inhibens
, a bacterium with promising use as a probiotic for aquatic farming industries. Genomic analysis suggested that Phaeobacter phage MD18 has evolved to enhance its replication in
P. inhibens
by adopting favorable tRNA genes as well as through genomic sequence adaptation to resemble host codon usage. Lastly, a high-throughput analysis of
P. inhibens
transposon insertion mutants identified genes that modulate host susceptibility to phage MD18 and implicated the type IV pilus as the likely receptor recognized for adsorption. This study marks the first characterization of the relationship between
P. inhibens
and an environmentally sampled phage, which informs our understanding of natural threats to the bacterium and may promote the development of novel phage technologies for genetic manipulation of this host.
Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity
Authors: Youngblut Nicholas D. , de la Cuesta-Zuluaga Jacobo , Reischer Georg H. , Dauser Silke , Schuster Nathalie , Walzer Chris , Stalder Gabrielle , Farnleitner Andreas H. , Ley Ruth E.
Published: November 2020

Microbiome studies on a select few mammalian species (e.g., humans, mice, and cattle) have revealed a great deal of novel genomic diversity in the gut microbiome. However, little is known of the microbial diversity in the gut of other vertebrates. We studied the gut microbiomes of a large set of mostly wild animal species consisting of mammals, birds, reptiles, amphibians, and fish. Unfortunately, we found that existing reference databases commonly used for metagenomic analyses failed to capture the microbiome diversity among vertebrates. To increase database representation, we applied advanced metagenome assembly methods to our animal gut data and to many public gut metagenome data sets that had not been used to obtain microbial genomes. Our resulting genome and gene cluster collections comprised a great deal of novel taxonomic and genomic diversity, which we extensively characterized. Our findings substantially expand what is known of microbial genomic diversity in the vertebrate gut.
Supplemental Material: Cyclophosphates, a new class of native phosphorus compounds, and some insights into prebiotic phosphorylation on early Earth
Authors: Britvin Sergey , al. et
Published: November 2020

Topographic coordinates of collected samples, details of analytical procedures, and characterization of minerals.
Supplemental Material: Early Devonian tectonic conversion from contraction to extension in the Chinese Western Tianshan: A response to slab rollback
Authors: Wang Xin-Shui , Gao Jun , al. et
Published: November 2020

Figures S1, S2, and Tables S1, S2, and S3.
Extended storage of SARS-CoV-2 nasopharyngeal swabs does not negatively impact results of molecular-based testing across three clinical platforms
Authors: Skalina Karin A , Goldstein D Y , Sulail Jaffar , Hahm Eunkyu , Narlieva Momka , Szymczak Wendy , Fox Amy S
Published: November 2020

With the global outbreak of COVID-19, the demand for testing rapidly increased and quickly exceeded the testing capacities of many laboratories. Clinical tests which receive CE (Conformité Européenne) and Food and Drug Administration (FDA) authorisations cannot always be tested thoroughly in a real-world environment. Here we demonstrate the long-term stability of nasopharyngeal swab specimens for SARS-CoV-2 molecular testing across three assays recently approved by the US FDA under Emergency Use Authorization. This study demonstrates that nasopharyngeal swab specimens can be stored under refrigeration or even ambient conditions for 21 days without clinically impacting the results of the real-time reverse transcriptase-PCR testing.