bluuebunny/crossref_metadata_2025 huggingface dataset:
Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion
Authors: Pierce Justin , Williams Glen , Simpson Timothy W. , Meisel Nicholas A. , McComb Christopher
Published: November 2021

Modern digital manufacturing processes, such as additive manufacturing, are cyber-physical in nature and utilize complex, process-specific simulations for both design and manufacturing. Although computational simulations can be used to optimize these complex processes, they can take hours or days — an unreasonable cost for engineering teams leveraging iterative design processes. Hence, more rapid computational methods are necessary in areas where computation time presents a limiting factor. When existing data from historical examples is plentiful and reliable, supervised machine learning can be used to create surrogate models that can be evaluated orders of magnitude more rapidly than comparable finite element approaches. However, for applications that necessitate computationally-intensive simulations, even generating the training data necessary to train a supervised machine learning model can pose a significant barrier. Unsupervised methods, such as physics-informed neural networks, offer a shortcut in cases where training data is scarce or prohibitive. These novel neural networks are trained without the use of potentially expensive labels. Instead, physical principles are encoded directly into the loss function. This method substantially reduces the time required to develop a training dataset, while still achieving the evaluation speed that is typical of supervised machine learning surrogate models. We propose a new method for stochastically training and testing a convolutional physics-informed neural network using the transient 3D heat equation- to model temperature throughout a solid object over time. We demonstrate this approach by applying it to a transient thermal analysis model of the powder bed fusion manufacturing process.
A Model for the Digital Method of Measuring LED Incident Photocurrent
Authors: Campbell Jake , Pretty Christopher G. , Knopp Jennifer , Bones Phil , Chase J. Geoffery
Published: November 2021

Pulse oximeters and other light based sensor types are used to monitor arterial blood oxygen levels, heart rate, and much more that rely on LEDs and photodiodes. The conventional method of using photodiodes to detect light signals is accurate, but requires relatively expensive hardware processing to extract the signal. Digital sensing of light using an LED provides a low-cost alternative by using a voltage threshold timing method. However, the accuracy of this method is dependant on the microcontroller clock speed and suffers from variable sample rate (100 us to 10 ms). This paper develops a model for a digital light sensing method using only a microcontroller’s ADC and timer, and an LED. Using the voltage discharge curve of a reverse biased LED, the sensor is capable of accurately detecting light intensities ranging from 0–3885 mcd at a sample period of 500 us. A linear relationship was found through the incident light intensity ranges of 0 to 3880 mcd. The model fit the expected experimental values, with an estimated photocurrent ranging from 10 pA to 55 nA. With an R2 of 0.9997, the model demonstrates the digital sensing method linearly responds to incident light intensity and can simplify the design of pulse oximeters and similar light based sensor types.
Multibody Analysis of a Tensegral Servo-Actuated Structure for Civil Applications
Authors: Scoccia Cecilia , Palmieri Giacomo , Callegari Massimo , Rossi Marco , Carbonari Luca , Munafò Placido , Marchione Francesco , Chiappini Gianluca
Published: November 2021

The use of glass elements in civil engineering is spreading in the last years beyond merely aesthetic functions for their ease of installation and production. Nonetheless, the structural performance of such materials in any condition of use is object of investigation. In this scenario, the paper analyses the performance of an innovative concept of tensegrity floor (Patent no 0001426973) characterized by a particular steel-glass adhesive junction that permits a profitable structural cooperation between such basically different materials. As known, at the base of the effectiveness of tensegral structures lies the correct tensioning of metal strands which are devoted at keeping the rigid elements compressed. The tensioning level is then responsible of the actual deformation of the structure, which is of course of uttermost importance while speaking of civil applications. To address this issue with the adequate level of confidence required by construction practice, a mechatronic servo-system is proposed, aimed at maintaining, and modifying when needed, the stress state of the metal cables to adjust the deformation of the upper plane in response to varying loads. Three different actuation schemes, with different levels of realization complexity, are analysed and compared in simulated environment by means of a hybrid multibody-finished elements mode.
Can Gratitude Promote More Creative Engineering Design?
Authors: Sisson Natalie M. , Impett Emily A. , Shu L. H.
Published: November 2021

Urgent societal problems, including climate change, require innovation, and can benefit from interdisciplinary solutions. A small body of research has demonstrated the potential of positive emotions (e.g., gratitude, awe) to promote creativity and prosocial behavior, which may help address these problems.

This study integrates, for the first time, psychology research on a positive and prosocial emotion (i.e., gratitude) with engineering-design creativity research. In a pre-registered study design, engineering students and working engineers (pilot N = 49; full study N = 329) completed gratitude, positive-emotion control, or neutral-control inductions. Design creativity was assessed through rater scores of responses to an Alternate Uses Task (AUT) and a Wind-Turbine-Blade Repurposing Task (WRT).

No significant differences among AUT scores emerged across conditions in either sample. While only the pilot-study manipulation of gratitude was successful, WRT results warrant further studies on the effect of gratitude on engineering-design creativity. The reported work may also inform other strategies to incorporate prosocial emotion to help engineers arrive at more original and effective concepts to tackle environmental sustainability, and in the future, other problems facing society.
Design of a Human-Robot Collaborative System: Methodology and Case Study
Authors: Scoccia Cecilia , Ciccarelli Marianna , Palmieri Giacomo , Callegari Massimo
Published: November 2021

Human-machine collaboration is one of the key drivers of the Industry 4.0 paradigm. The recent advances in collaborative robotics led to the effective implementation of various control strategies able to improve interactions between robots and humans in unstructured environments. This represents an important socio-economic aspect: the robot does not replace the human being, but supports them in carrying out repetitive or dangerous tasks. In this scenario it is necessary to take into account different contrasting issues that derive from the necessity to grant the high performance typical of a robotic installation together with the safety levels required by a manual operation. In this paper we analyse the use case of a famous kitchen industry that decided to test the introduction of collaborative robotics to increase the flexibility and productivity of their production lines. A method, to define the design criteria of the Human-Robot Collaboration system (HRC), is proposed taking into account aspects related to both the safety and the ergonomics of the human operator, using a real-time mapping of the work area and the management of operations. The collaboration between robot and operator can be facilitated thanks to the use of an assistive device which, through the recognition of gestures, allows easy communication. Therefore, this paper aims to combine: operator safety and ergonomics, study of the workstation, sensor technologies, identification and tracing of gestures. Several simulations have been performed to evaluate the proposed collaborative workstation.
A Modified Incremental Harmonic Balance Method for Periodic Forced Oscillations of a Dielectric Elastomer Membrane Undergoing In-Plane Deformation
Authors: Zhang Jian , Zhao Jian , Wang Xuefeng , Wang Hongyu
Published: November 2021

Dielectric elastomers (DEs) are widely used in soft transducers with mechanical or electrical loads. DE devices are mainly used for applications under dynamic loads, such as, ocean wave generators, loudspeakers, oscillators, and artificial muscles. It is still a challenge to analytically solve the vibration equation of a DE transducer. For example, for a DE membrane undergoing stretching deformation that is studied in this paper, its vibration equation is highly nonlinear with high-order and fractional-order polynomials. Numerical integration (NI) methods or traditional harmonic balance (HB) methods were used in previous works, but the two methods have low efficiency for strong and complex nonlinearities, and it is difficult to improve the accuracy of the solution. In this work, a free-energy model is used to study the dynamic characteristics of a DE membrane undergoing in-plane deformation, which undergoes a combined load excited by mechanical compression and electric fields. To improve the calculation efficiency and accuracy, we employ a modified incremental harmonic balance (IHB) method based on the fast Fourier transform to solve the periodically-excited nonlinear dynamic equation of the DE membrane. Finally, results of the example verify that the modified IHB method is fast and accurate, and has a very good performance in solving a problem with high nonlinearities.
Potential Energy Surfaces for Conceptual Design and Analysis of Mechanical Systems
Authors: Manion Charles A. , Fuge Mark
Published: November 2021

Current computational Design Synthesis approaches have had trouble generating components with higher kinematic pairs and have instead relied on libraries of predefined components. However, higher kinematic pairs are ubiquitous in many mechanical devices such as ratchets, latches, locks, trigger mechanisms, clock escapements, and materials handling systems. In many cases there is a need to synthesize new higher kinematic pair devices. To address this problem, we develop a new representation for mechanical systems that extends the capabilities of configuration spaces to consider arbitrary energy storing mechanical devices. The key idea underlying this representation is the use of potential energy surfaces as a generalization of configuration spaces. This generalization enables modelling of mechanical systems in a physics independent manner and captures behaviors such as dynamics. By modeling a device through the lens of a potential energy surface, we demonstrate that differentiable simulation is possible. Differentiable simulation enables efficient calculation of gradients of potential energy surface parameters with respect to an objective function that depends on trajectories taken on the potential energy surface. This allows synthesis of mechanical devices with desired kinematic and dynamic behavior through gradient descent. We demonstrate this through several synthesis examples including positioning devices (e.g., a funnel) and timing devices (e.g., an oscillator).
Evoked Electromyographic Fatigue Indices During Intermittent Stimulation Towards Dynamic Wrist Contractions
Authors: McKenzie Lachlan R. , Fortune Benjamin C. , Chatfield Logan T. , Pretty Christopher G.
Published: November 2021

Functional electrical stimulation (FES) in stroke rehabilitation is hindered by early patient fatigue. Therefore the study of FES-elicited fatigue is needed to optimise its therapeutic impact. In this study, the reliability of evoked electromyography (EMG) median frequency (MDF) and peak-to-peak (PTP) fatigue indices were investigated during stimulation of the forearm. During isometric constant stimulation the MDF-time and PTP-time waveforms exhibited negative gradients in the ranges (−1.3 to −3.6) Hz · s−1 and (−0.013 to −0.016) V · s−1 respectively, most with coefficients of determination (R2) greater than 0.83. During vEMG-controlled stimulation the MDF-contraction waveforms exhibited negative gradients in the range (−2.4 to −9.0) Hz · Cont−1 while the PTP gradients ranged from (0.0070 to −0.019) V · Cont−1. For these datasets the MDF waveforms’ R2 > 0.62 and most PTP waveforms’ R2 < 0.35. These findings suggest that the MDF and PTP amplitude are suitable fatigue indices during isometric constant stimulation but the PTP-based index becomes unreliable during vEMG-controlled stimulation.
Uncertainty Quantification and Reduction Using Sensitivity Analysis and Hessian Derivatives
Authors: Sánchez Josefina , Otto Kevin
Published: November 2021

We study the use of Hessian interaction terms to quickly identify design variables that reduce variability of system performance. To start we quantify the uncertainty and compute the variance decomposition to determine noise variables that contribute most, all at an initial design. Minimizing the uncertainty is next sought, though probabilistic optimization becomes computationally difficult, whether by including distribution parameters as an objective function or through robust design of experiments. Instead, we consider determining the more easily computed Hessian interaction matrix terms of the variance-contributing noise variables and the variables of any proposed design change. We also relate the Hessian term coefficients to subtractions in Sobol indices and reduction in response variance. Design variable changes that can reduce variability are thereby identified quickly as those with large Hessian terms against noise variables. Furthermore, the Jacobian terms of these design changes can indicate which design variables can shift the mean response, to maintain a desired nominal performance target. Using a combination of easily computed Hessian and Jacobian terms, design changes can be proposed to reduce variability while maintaining a targeted nominal. Lastly, we then recompute the uncertainty and variance decomposition at the more robust design configuration to verify the reduction in variability. This workflow therefore makes use of UQ/SA methods and computes design changes that reduce uncertainty with a minimal 4 runs per design change. An example is shown on a Stirling engine design where the top four variance-contributing tolerances are matched with two design changes identified through Hessian terms, and a new design found with 20% less variance.
Kinematic Modeling of a Novel RR-RP Hybrid Serial-Parallel Mechanism With Variable Topology
Authors: Slaboch Brian J. , Holtzen Peter , Rodriguez Luis A.
Published: November 2021

This paper introduces a new mechanism that will be classified as an RR-RP hybrid serial-parallel mechanism with variable topology. A mechanism with variable topology is a mechanism that can change its topology due to a change it its joints constraint geometric profile. The RR-RP is unique in that it combines the functionality of both an RR and RP serial manipulator without the need for an additional actuator, leading to a lower weight, lower cost, and more efficient mechanism. The new mechanism and its topology are presented, followed by a workspace analysis, derivation of the forward and inverse kinematics, and velocity analysis of the new mechanism.
Visualizing Model-Based Product Definitions in Augmented Reality
Authors: Vernica Teodor , Lipman Robert , Bernstein William Z.
Published: November 2021

Augmented reality (AR) technologies present immense potential for the design and manufacturing communities. However, coordinating traditional engineering data representations into AR systems without loss of context and information remains a challenge. A major barrier is the lack of interoperability between manufacturing-specific data models and AR-capable data representations. In response, we present a pipeline for porting standards-based Product Manufacturing Information (PMI) with three-dimensional (3D) model data into an AR scene. We demonstrate our pipeline by interacting with annotated parts while continuously tracking their pose and orientation. Our work provides insight on how to address fundamental issues related to interoperability between domain-specific models and AR systems.
Optimized Torque Assistance During Walking With an Idealized Hip Exoskeleton
Authors: Ratnakumar Neethan , Zhou Xianlian
Published: November 2021

The hip muscles account for a great percentage of the total human energy expenditure during walking and many wearable devices have been developed in assisting the hip joint to reduce the metabolic Cost Of Transport (COT) for walking. However, the effectiveness of assisting the hip in only one direction (either flexion or extension) or both directions has not been systematically studied and the underlying muscle mechanics and energetics affected by the assistance are not well understood. In this study, human-exoskeleton simulation based optimizations were performed to find optimized hip assistance torque profiles for (1) unidirectional flexion assistance, (2) unidirectional extension assistance, and (3) bidirectional flexion and extension assistance. Our results show that the bidirectional assistance is the most effective in reducing the COT of walking (22.7% reduction) followed by flexion (19.2%) and extension (11.7%). The flexion assistance resulted in more COT saving than the output of its net work by 35.9%, which indicates that the negative work done (42.2% of its positive counterpart) also played an important role in reducing the COT. The bidirectional assistance also reduced the activations of the hip extensors to a great extent and shifted the activation pattern of the hip flexor (ilipsoas). These results can provide valuable information for optimal hip actuation (timing and profiles) and help exoskeleton designers make informed decisions.
A Mixed-Method Analysis of Schedule and Cost Growth in Defense Acquisition Programs
Authors: Hans Atharva , Chaudhari Ashish M. , Bilionis Ilias , Panchal Jitesh H.
Published: November 2021

Cost and schedule overruns are common in the procurement of large-scale defense acquisition programs. Current work focuses on identifying the root causes of cost growth and schedule delays in the defense acquisition programs. There is need for a mix of quantitative and qualitative analysis of cost and schedule overruns which takes into account program factor such as, technology maturity, design maturity, initial acquisition time, and program complexity. Such analysis requires an easy to access database for program-specific data about how an acquisition programs’ technical and financial characteristics vary over the time. To fulfill this need, the objective of this paper is twofold: (i) to develop a database of major US defense weapons programs which includes details of the technical and financial characteristics and how they vary over time, and (ii) to test various hypotheses about the interdependence of such characteristics using the collected data. To achieve the objective, we use a mixed-method analysis on schedule and cost growth data available in the U.S. Government Accountability Office’s (GAO’s) defense acquisitions annual assessments during the period 2003–2017. We extracted both analytical and textual data from original reports into Excel files and further created an easy to access database accessible from a Python environment. The analysis reveals that technology immaturity is the major driver of cost and schedule growth during the early stages of the acquisition programs while technical inefficiencies drive cost overruns and schedule delays during the later stages. Further, we find that the acquisition programs with longer initial length do not necessarily have higher greater cost growth. The dataset and the results provide a useful starting point for the research community for modeling cost and schedule overruns, and for practitioners to inform their systems acquisition processes.
Teleoperation Interface for sAFAM, a Solid Articulated Four Axes Microrobot
Authors: Alqatamin Moath , Ritz Brooke , Sherehiy Andriy , Jackson Douglas , Zhang Ruoshi , Chowdhury Sri S. , Wei Danming , Popa Dan O.
Published: November 2021

The sAFAM is a novel mm-size microrobot built using MicroElectroMechanical Systems (MEMS) technology. It consists of a monolithically fabricated microrobotic arm assembled onto four in-plane actuators, capable of moving along four degrees of freedom, including translational movement in X and Y axes as well as pitch and yaw. In this paper, several design modifications were proposed to increase movement precision, stability, and controllability to the sAFAM tip. An interface is developed to assist a human operator accurately position the microrobot tip during nano-object handling. A Python-based graphical user interface (GUI) was programmed to make it intuitive for an operator to use and obtain required tip precision under a microscope. Experimental results demonstrate the functionality of the proposed control solution, and the tip motion resolution using microscope images of the microrobot tip under 20x magnification during operation. The hardware and software requirements for the proposed experimental setup and control platform are discussed in detail.
Robot Motion Planner for Under-Constrained Trajectories With Part-Specific Geometric Variances
Authors: Oridate Ademola , Pryor Mitchell , Seepersad Carolyn
Published: November 2021

Industrial manipulators often interact with large and complex objects for a variety of automation tasks. Finding a feasible path for the robot end-effector that ensures task success is often non-trivial due to considerations such as reachability, singularity avoidance, and collision avoidance. This paper proposes an approach to expand the search space for feasible robot trajectories (and search for an optimal solution) by taking advantage of task redundancy for certain tasks while ensuring task completion. The effort builds on previous work enabling virtual fixture generation for complex shapes given CAD or scan data. The proposed method has been developed into a trajectory planning library on the ROS (Robot Operating System) framework and tested by simulating an interaction of a six-axis industrial robot with an aircraft fuselage. Results show increased coverage of task area with minimal robot base placements.
Calibration of Parallel Kinematic Machine Based on Stewart Platform – A Literature Review
Authors: Karmakar Sourabh , Patel Apurva , Turner Cameron J.
Published: November 2021

Stewart platform-based Parallel Kinematic Machines (PKM) have been extensively studied by researchers due to their inherent finer control characteristics. This has opened its potential deployment opportunities in versatile critical applications like the medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturing, etc. All these precise, complicated, and repeatable motion applications require micro and nano-scale movement control in 3D space; a 6-DOF PKM can take this challenge smartly. For this, the PKM must be more accurate than the desired application accuracy level and thus proper calibration for a PKM robot is essential. Forward kinematics-based calibration for such hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To analyze different techniques, an external instrument-based, constraint-based, and auto or self-calibration-based approaches have been used for calibration. This survey has been done by reviewing these key methodologies, their outcome, and important points related to inverse kinematic-based PKM calibrations in general. It is observed in this study that the researchers focused on improving the accuracy of the platform position and orientation considering the errors contributed by a single source or multiple sources. The error sources considered are mainly structural, in some cases, environmental factors are also considered, however, these calibrations are done under no-load conditions. This study aims to understand the current state of the art in this field and to expand the scope for other researchers in further exploration in a specific area.
Informed Latent Space Exploration for Image-Based Path Synthesis of Linkages
Authors: Deshpande Shrinath , Lyu Zhijie , Purwar Anurag
Published: November 2021

This paper brings together rigid body kinematics and machine learning to create a novel approach to path synthesis of linkage mechanisms under practical constraints, such as location of pivots. We model the coupler curve and constraints as probability distributions of image pixels and employ a Convolutional Neural Network (CNN) based Variational AutoEncoder (VAE) architecture to capture and predict the features of the mechanism. Plausible solutions are found by performing informed latent space exploration so as to minimize the changes to the input coupler curve while seeking to find user-defined pivot locations. Traditionally, kinematic synthesis problems are solved using precision point approach, wherein the input path is represented as a set of points and a set of equations in terms of design parameters are formulated. Generally, this problem is solved via optimization, wherein a measure of error between the given path and the coupler curve is minimized. A limitation of this approach is that the existing formulations depend on the type of mechanism, do not admit practical constraints in a unified way, and provide a limited number of solutions. However, in the machine design pipeline, kinematic synthesis problems are concept generation problems, where designers care more about a large number of plausible and practical solutions rather than the precision of input or the solutions. The image-based approach proposed in this paper alleviates the difficulty associated with inherently uncertain inputs and constraints.
Automated Quantum Entanglement and Cryptography for Networks of Robotic Systems
Authors: Khoshnoud Farbod , Ghazinejad Maziar
Published: November 2021

In this paper the procedure for automating the photon quantum experiments for mobile robotic applications is presented. Due to the rapid advances of quantum technologies and quantum engineering, the integration of quantum capabilities in robotic and autonomous systems will be inevitable, and therefore the study and investigation of compatibility and adaptability of quantum systems and classical autonomous systems is of great importance. In a quantum-classical hybrid setup, the source of single photon generation is placed on a leader robot which can send correlated single photons to robot followers. In the case of quantum entanglement, spontaneous parametric down-conversion process using nonlinear paired BBO crystals is implemented which sends entangled photons to the single photon counting modules installed on mobile robots. In the case of quantum cryptography, single photons are sent from Alice robot to Bob robot, where Alice has the course of single photon and Bob has a polarizing beamsplitter and two detectors and that can detect the polarization of photons as vertical and horizontal. Bob then can convert the polarizations to a digital signals as zeros and ones and use them as communication information for control purposes through a classical channel. Motorized optics equipment can automatically align the source of photons to detectors on the mobile robots. The automated alignment procedure is one of the key enabling technologies in integrating quantum capabilities with control of mobile robotic systems. In this paper, in particular, the automated alignment is studied while considering the uncertainties in the dynamic of the system which can potentially cause the alignment task very challenging. The uncertainty analysis in the automated alignment is implemented by Optimal Uncertainty Quantification technique to ensure achieving the quantum control of the robotic systems and presented here for the first time.
Multi-Modeshape Reservoir Computing Using a Continuous MEMS Microbeam
Authors: Hasan Mohammad H. , Alsaleem Fadi
Published: November 2021

Delay-based Reservoir computing (RC) offers great potential in time-series problems, especially when applied in hardware due to its low computational power and its compact nature. However, this approach suffers from a large computational delay because of the serial probing of virtual nodes. To address this disadvantage, this paper presents the use of a continuous MEMS arch for Delay-based RC. This novel approach reduces the computational delay by using fewer virtual nodes through maintaining sufficient virtual node coupling and nonlinear complexity. As a demonstration, we show that a single MEMS arch is capable of performing a binary waveform classification task of a multi-frequency square-and-triangle waveform problem with a success rate > 96% using only 10 virtual nodes compared to 40 virtual nodes in a typical implementation. The reduction in the number of virtual neurons is achieved by biasing the MEMS device using an AC source around its second modeshape.
Home Energy Management System (HEMS): Coupled Flexible Load Management in Homes
Authors: Jiang Yilin , Song Li , Allen Janet K. , Mistree Farrokh
Published: November 2021

Electricity suppliers have introduced time-of-use (TOU) metering and pricing in residential buildings in recent years. By increasing the price of electricity during on-peak hours (e.g., 2 pm to 7 pm in summer months), suppliers expect to regulate the energy usage from homeowners when the grid is near capacity. Therefore, homeowners are motivated to shift the load by moving their home electricity use from on-peak hours to off-peak hours for utility cost savings. However, peak load management is another factor that needs to be considered, since a higher peak load might cause other penalties, such as making suppliers change their current tariff policy in the next paying period since the grid needs to fulfill a higher demand.

In this paper we explore the Home Energy Management System (HEMS) Strategy for homeowners who are considering saving money by reducing/avoiding the on-peak hour electricity usage while reducing peak load. A multi-goal scheduling problem is solved by constructing a coupled compromise decision support problem in which a water heater is coupled with flexible, non-thermal appliances such as a washing machine. To address these multiple goals, we use Decision Support Problem (DSP) construct. A use case simulation shows that our scheduler can make a reasonable tradeoff between two conflicting goals, helping the homeowner save money while maintaining low peak demand.
Fast, Accurate, and Automated 3D Reconstruction Using a Depth Camera Mounted on an Industrial Robot
Authors: Malhan Rishi , Joseph Rex Jomy , Bhatt Prahar M. , Shah Brual , Gupta Satyandra K.
Published: November 2021

3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture point-clouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.
Fractional-Order Impedance Control Design for Robot Manipulator
Authors: Liu Xiaolian , Wang Shaohua , Luo Ying
Published: November 2021

In order to make robot manipulators work more compliantly when contacting with the environment, it is necessary to reduce the contact force caused by positioning errors. One effective way to solve this problem is impedance control, which makes the robot manipulator a second-order mass-spring-damping system in principle. In this paper, a position-based fractional-order impedance control design method is proposed for the robot manipulator force control. The end-effector/environment contact model is established, and the closed-loop system is analyzed with the reference force as input. A fractional-order impedance parameters design method is proposed for better force-control performance, which calculates and optimizes parameters through frequency-domain specifications (i.e., phase margin and gain crossover frequency) and time-domain specification (i.e., the minimum JITSE). With the Robotics ToolBox for MATLAB (RTB), the performance comparison between integer-order and fractional-order impedance controls is illustrated in simulation. The fractional-order impedance control system has a faster response, smaller overshoot, and better resistance to external disturbances from the environment.
Dynamics of Dual-Cell Series Miura-Ori Structures With Different Types of Inter-Cell Connections
Authors: Zhou Hai , Wu Haiping , Xu Jian , Fang Hongbin
Published: November 2021

Origami-inspired structures and materials have shown remarkable properties and performances originating from the intricate geometries of folding. Origami folding could be a dynamic process and origami structures could possess rich dynamic characteristics under external excitations. However, the current state of dynamics of origami has mostly focused on the dynamics of a single cell. This research has performed numerical simulations on multi-stable dual-cell series Miura-Ori structures with different types of inter-cell connections based on a dynamic model that does not neglect in-plane mass. We introduce a concept of equivalent constraint stiffness k* to distinguish different types of inter-cell connections. Results of numerical simulations reveal the multi-stable dual-cell structure will exhibit a variety of complex nonlinear dynamic responses with the increasing of connection stiffness because of the deeper energy well it has. The connection stiffness has a strong effect on the steady-state dynamic responses under different excitation amplitudes and a variety of initial conditions. This effect makes us able to adjust the dynamic behaviors of dual-cell series Miura-Ori structure to our needs in a complex environment. Furthermore, the results of this research could provide us a theoretical basis for the dynamics of origami folding and serve as guidelines for designing dynamic applications of origami metastructures and metamaterials.
Precise and Effective Robotic Tool Change Strategy Using Visual Servoing With RGB-D Camera
Authors: Wei Danming , Trombley Christopher M. , Sherehiy Andriy , Popa Dan O.
Published: November 2021

In modern industrial manufacturing processes, robotic manipulators are routinely used in the assembly, packaging, and material handling operations. During production, changing end-of-arm tooling is frequently necessary for process flexibility and reuse of robotic resources. In conventional operation, a tool changer is sometimes employed to load and unload end-effectors, however, the robot must be manually taught to locate the tool changers by operators via a teach pendant. During tool change teaching, the operator takes considerable effort and time to align the master and tool side of the coupler by adjusting the motion speed of the robotic arm and observing the alignment from different viewpoints. In this paper, a custom robotic system, the NeXus, was programmed to locate and change tools automatically via an RGB-D camera. The NeXus was configured as a multi-robot system for multiple tasks including assembly, bonding, and 3D printing of sensor arrays, solar cells, and microrobot prototypes. Thus, different tools are employed by an industrial robotic arm to position grippers, printers, and other types of end-effectors in the workspace. To improve the precision and cycle-time of the robotic tool change, we mounted an eye-in-hand RGB-D camera and employed visual servoing to automate the tool change process. We then compared the teaching time of the tool location using this system and compared the cycle time with those of 6 human operators in the manual mode. We concluded that the tool location time in automated mode, on average, more than two times lower than the expert human operators.
A Content Analysis of Mental Health Literacy Education for Sport Coaches
Authors: Hebard Stephen P. , Bissett James E. , Kroshus Emily , Beamon Emily R. , Reich Aviry
Published: November 2021

Sport coaches can play an influential role in athletes’ mental health help seeking through purposeful communication, destigmatization of mental health concerns, and supportive relationships. To positively engage in these behaviors, coaches require mental health knowledge (or literacy), positive attitudes about that knowledge, and self-efficacy to use that knowledge. Guided by a multidimensional health literacy framework, we conducted a content analysis of web content and scholarly literature to identify health education programming for coaches that addressed athlete mental health. A purposive sample of Olympic National Governing Bodies, collegiate athletic associations, high school sport associations, youth sport governing bodies, and the scholarly literature were analyzed. We found inconsistent programming regarding a range of mental health disorders, behaviors critical to mental health promotion, and critical components of mental health literacy. Implications and next steps for mental health literacy support for coaches are discussed.
Effect of Aerobic Walking Exercise on Stress Urinary Incontinence in Postmenopausal Women
Authors: Elbandrawy Asmaa M. , Mahmoud Sara G. , AboElinin Mohamed F. , Yousef Amel M.
Published: November 2021

The purpose of this study was to explore the impact of aerobic walking exercise on stress urinary incontinence (SUI) among postmenopausal women. Thirty females diagnosed with SUI participated in the research. Participants were assigned randomly into two groups: The usual care group (UC) and the UC plus aerobic walking exercise (TMT) group. The UC group performed pelvic floor muscle (PFM) training only, while the TMT group performed PFM training in addition to aerobic exercise. Myomed biofeedback was used to assess the PFM strength both before and after a 12-week period. The Revised Urinary Incontinence Scale was utilized to assess changes in incontinence severity symptoms after intervention. Findings revealed a significant increase in PFM strength in both UC and TMT groups (p = .011 and p = .010, respectively) and a significant reduction in their Revised Urinary Incontinence Scale (p = .011 and p = .001, respectively) after the end of the 12 weeks of the training program. In addition, there was a more significant increase in PFM strength in the TMT group than in the UC group (p = .010) and a more significant decrease in Revised Urinary Incontinence Scale (p = .011) after 12 weeks of the training program. This study concluded that aerobic walking exercise with PFM training is more effective than PFM training only in increasing PFM strength and improving symptoms of SUI in postmenopausal women with SUI.
Quantitative cross-species translators of cardiac myocyte electrophysiology: Model training, experimental validation, and applications
Authors: Morotti Stefano , Liu Caroline , Hegyi Bence , Ni Haibo , Fogli Iseppe Alex , Wang Lianguo , Pritoni Marco , Ripplinger Crystal M. , Bers Donald M. , Edwards Andrew G. , Grandi Eleonora
Published: November 2021

Found in translation: We present quantitative tools that map cardiac myocyte physiology and pharmacology across species.
Qubit readout error mitigation with bit-flip averaging
Authors: Smith Alistair W. R. , Khosla Kiran E. , Self Chris N. , Kim M. S.
Published: November 2021

We present a scheme to characterize and mitigate readout errors on multi-qubit devices more efficiently using random bit-flips.
Long-lived spin-polarized intermolecular exciplex states in thermally activated delayed fluorescence-based organic light-emitting diodes
Authors: Weissenseel Sebastian , Gottscholl Andreas , Bönnighausen Rebecca , Dyakonov Vladimir , Sperlich Andreas
Published: November 2021

Disentangling spin-spin interactions reveals highly spin-polarized efficiency-limiting exciplexes in next-generation TADF OLEDs.
Characterization of Highly Ferulate-Tolerant Acinetobacter baylyi ADP1 Isolates by a Rapid Reverse Engineering Method
Authors: Luo Jin , McIntyre Emily A. , Bedore Stacy R. , Santala Ville , Neidle Ellen L. , Santala Suvi
Published: November 2021

Microbial conversion of lignin-enriched streams is a promising approach for lignin valorization. However, the lignin-derived aromatic compounds are toxic to cells at relevant concentrations.
Pathogenesis of Respiratory Viral and Fungal Coinfections
Authors: Salazar Fabián , Bignell Elaine , Brown Gordon D. , Cook Peter C. , Warris Adilia
Published: November 2021

Individuals suffering from severe viral respiratory tract infections have recently emerged as “at risk” groups for developing invasive fungal infections. Influenza virus is one of the most common causes of acute lower respiratory tract infections worldwide.
Development of a Multiplex PCR Short Tandem Repeat Typing Scheme for Candida krusei
Authors: van Haren Merlijn H. I. , de Groot Theun , Spruijtenburg Bram , Jain Kusum , Chowdhary Anuradha , Meis Jacques F.
Published: November 2021

Candida krusei
is a human-pathogenic yeast that can cause candidemia with the lowest 90-day survival rate in comparison to other
Candida
species. Infections occur frequently in immunocompromised patients, and several
C. krusei
outbreaks in health care facilities have been described.
Short-Stalk Isoforms of CADM1 and CADM2 Trigger Neuropathogenic Measles Virus-Mediated Membrane Fusion by Interacting with the Viral Hemagglutinin
Authors: Takemoto Ryuichi , Suzuki Tateki , Hashiguchi Takao , Yanagi Yusuke , Shirogane Yuta
Published: November 2021

Measles, an acute febrile illness with skin rash, is still an important cause of childhood morbidity and mortality worldwide. Measles virus (MeV), the causative agent of measles, may also cause a progressive neurological disorder, subacute sclerosing panencephalitis (SSPE), several years after acute infection.
Identification of Multiple Low-Level Resistance Determinants and Coselection of Motility Impairment upon Sub-MIC Ceftriaxone Exposure in Escherichia coli
Authors: Ching Carly , Zaman Muhammad H.
Published: November 2021

Ceftriaxone is a widely consumed antibiotic used to treat bacterial infections. Bacteria, however, are increasingly becoming resistant to ceftriaxone.
Supplemental Material: Geologic map of central Panamint Range, California
Authors: Andrew J.E.
Published: November 2021

Digital map data files in ArcGIS shapefile format for data collection points, geologic contacts, and geologic unit polygons.
I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts
Authors: Sen Procheta , Ganguly Debasis , Jones Gareth J. F.
Published: November 2021

Reducing user effort in finding relevant information is one of the key objectives of search systems. Existing approaches have been shown to effectively exploit the context from the current search session of users for automatically suggesting queries to reduce their search efforts. However, these approaches do not accomplish the end goal of a search system—that of retrieving a set of potentially relevant documents for the evolving information need during a search session. This article takes the problem of query prediction one step further by investigating the problem of contextual recommendation within a search session. More specifically, given the partial context information of a session in the form of a small number of queries, we investigate how a search system can effectively predict the documents that a user would have been presented with had he continued the search session by submitting subsequent queries. To address the problem, we propose a model of contextual recommendation that seeks to capture the underlying semantics of information need transitions of a current user’s search context. This model leverages information from a number of past interactions of other users with similar interactions from an existing search log. To identify similar interactions, as a novel contribution, we propose an embedding approach that jointly learns representations of both individual query terms and also those of queries (in their entirety) from a search log data by leveraging session-level containment relationships. Our experiments conducted on a large query log, namely the AOL, demonstrate that using a joint embedding of queries and their terms within our proposed framework of document retrieval outperforms a number of text-only and sequence modeling based baselines.
Correlation between Contact Angle and Surface Roughness of Silicon Carbide Wafers
Authors: Kim Jung Gon , Yoo Woo Sik , Kim Woo Yeon , Lee Won Jae
Published: November 2021

Two-inch diameter 6H-SiC wafers were sliced from a SiC ingot and the wafers were ground and polished using different diamond slurries (1 μm and 0.1 μm in particles size) to investigate their dependence on wetting on surface roughness (Ra) and polarity using precisely dispensed de-ionized (DI) water drops. The Ra of the Si-face (0001) SiC wafer, after grinding and polishing, was 5.6 and 1.6 nm, respectively, as measured by atomic force microscopy (AFM). For C-face (000–1) SiC wafers, the Ra was 7.2 nm after grinding and 3.3 nm after polishing. The average contact angle measurement of the SiC wafers after final polishing showed clear differences between surface polarity; the contact angle for the Si-face (0001) was ~7o greater than that for the C-face (000–1). The difference in contact angles between the Si-face (0001) and the C-face (000–1) tends to increase as the reduction of surface roughness approaches the final stage of polishing. The uniformity of Raman peak intensity in the folded transverse optical phonon band at ~780 cm−1 in scanned areas correlated well with the surface roughness measured by AFM. The contact angle measurement can be used as a convenient surface polarity and surface roughness testing technique for SiC wafers.
Influence of Long Boreholes Layout and Drilling Length on Gas Drainage Based on Multifield Coupling Model of Gas‐Bearing Coal
Authors: Feng Renjun
Published: November 2021

Gas drainage through long seam boreholes is an effective method to prevent gas disasters in coal mines. In this paper, a multifield coupling model of gas migration in gas‐bearing coal was first established. Then, a quantitative characterization method of gas drainage effect was put forward. Finally, the extraction effect of long boreholes was obtained under different layouts and drilling lengths. The research results show that, under the arrangement of long boreholes along the seam, the gas pressure around the borehole decreases significantly with the extraction time. There is no extraction blank in the middle of the working face. However, it is easy to cause uneven gas drainage in the combined arrangement of the long boreholes along the seam and the penetrating boreholes. Furthermore, it is found that the drainage volume of the long boreholes along the seam is similar to that of the joint layout under the same drainage time. As the length of the borehole increases, the influencing range of gas drainage increases. When the borehole lengths are 150 m and 240 m, the drainage volumes are about 1.31 and 2.50 times that of the 90 m boreholes, respectively. The research achievements could provide a specific reference for the layout of long boreholes along the bedding and the determination of reasonable parameters for gas drainage on site.