bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechatronic Design of a Mobile Robot for Personal Assistance
Authors: Tagliavini Luigi , Botta Andrea , Carbonari Luca , Quaglia Giuseppe , Gandini Dario , Chiaberge Marcello
Published: November 2021

In this paper, a novel mobile platform for assistive robotics tasks is presented. The machine is designed for working in a home environment, un-structured and possibly occupied by people. To work in this space, the platform must be able to get rid of all the consequent difficulties: to overpass small objects as steps and carpets, to operate with an as-high-as-possible dynamics, to avoid moving obstacles, and to navigate autonomously to track persons for person monitoring purposes. The proposed platform is designed to have an omni-directional mobility that improves the manoeuvrability with respect to state-of-the-art differential drive robots. It also will have a non-axisymmetric shape to easily navigate narrow spaces, and real-time edge computing algorithms for navigation. This work shows the design paradigm adopted for the realization of a novel mobile robot, named Paquitop. For a robust output, the design process used a modular approach which disjointed the several sub-systems which compose the machine. After a brief analysis of the expected features, a set of basic requirements are drawn to guide the functional and executive design. The overall architecture of the platform is presented, together with some details on the mechanical and electrical systems.
Assessing the Social Impacts of Improved Cookstoves in Peri-Urban and Rural Uganda Using Card Sorting
Authors: Peiffer Erin , MacCarty Nordica
Published: November 2021

Card sorting is one method that can be used to solicit meaningful insight from end users on the design and assessment of technologies. The objective of this paper is to present methods for and results from a card sorting activity exploring the social impacts experienced by households that have adopted improved cookstoves in peri-urban and rural Uganda. Using a framework consisting of eleven social impacts (population change, family, gender, education, stratification, employment, health and well-being, human rights, networks and communication, conflict and crime, and cultural identity/heritage), households were asked to sort the cards into most, somewhat, and least impacted categories with conversations facilitated around each card placement. Results from this activity reaffirmed positive impacts for family, gender, health and well-being, and education that have been well documented in the literature while also identifying social impacts often overlooked in the sector such as changes in networks and communication, cultural identity and heritage, and human rights. Reflections on these results in terms of cookstove design as well as improvements that could be made in future card sorting activities are discussed.
Impact Dynamics in Four-Segment Tilting Pad Journal Bearings Subjected to Pad Fluttering
Authors: Rendl Jan , Smolík Luboš , Dyk Štěpán , Hajžman Michal
Published: November 2021

This paper presents a transient analysis of the motion of unloaded upper pads in a tilting pad journal bearing. It is known that such pads can exhibit self-excited vibration called pad fluttering, which can initiate fatigue damage due to elastic contacts between the fluttering pad and the journal. Unlike previous studies, this work attempts to evaluate forces in the contact. This evaluation is done using a robust nonlinear model, which considers hydrodynamic lubrication, out-of-balance forces and Hertzian contacts. Furthermore, qualitative changes of the bearing’s components motions are analysed in a wide range of journal speeds using bifurcation diagrams, phase portraits and estimates of the largest Lyapunov coefficients. The analysis reveals the intriguing nature of the system, which bifurcates between the periodic motion, period-doubling and chaos.
Computationally Assisted Retrieval and Reuse of 3D Solid Models and Assembly Work Instructions
Authors: Renu Rahul Sharan , Mocko Gregory
Published: November 2021

Many manufacturing enterprises have large collections of solid models and text-based assembly processes to support assembly operations. These data are often distributed across their extended enterprise. As these enterprises expand globally, there is often an increase in product and process variability which can often lead to challenges with training, quality control, and obstacles with change management to name a few. Thus, there is a desire to increase the consistency of assembly work instructions within and across assembly locations.

The objective of this research is to retrieve existing 3d models of components and assemblies and their associated assembly work instructions. This is accomplished using 3d solid model similarity and text mining of assembly work instructions.

Initially, a design study was conducted in which participants authored assembly work instructions for several different solid model assemblies. Next, a geometric similarity algorithm was used to compute similarity scores between solid models and latent semantic analysis is used to compute the similarity between text-based assembly work instructions. Finally, a correlation study between solid model-assembly instruction tuples is computed. A moderately strong positive correlation was found to exist between solid model similarity scores and their associated assembly instruction similarity scores. This indicates that designs with a similar shape have a similar assembly process and thus can serve as the basis for authoring new assembly processes. This aids in resolving differences in existing processes by linking three-dimensional solid models and their associated assembly work instructions.
Topology Optimization for Additively Manufactured Self-Supporting Axisymmetric Structures
Authors: Lee Hak Yong , Carroll Julia D. W. , Guest James K.
Published: November 2021

This paper discusses the design of axisymmetric structures with self-supporting features that can be additively manufactured without requiring internal support structures. This is motivated by wire-fed additive manufacturing processes, many of which can fabricate designs with enclosed pores that inherently exist in many axisymmetric structures, such as double walled pressure vessels. Although enclosed pores are possible, features that rise at shallow angles from the build plate typically cannot be fabricated without the use of support structures, which require removal and thus are unfavorable in such applications. In this paper, an overhang constraint is applied to ensure that all designed features rise at a designer-prescribed self-supporting angle to eliminate the need for such support structures. This is achieved by coupling the projection-based overhang constraint approach with topology optimization and axisymmetric finite elements whose stiffness is interpolated using Solid Isotropic Material with Penalization (SIMP). Gradients are computed with the adjoint method and the Method of Moving Asymptotes (MMA) is employed as the gradient-based optimizer. Two numerical examples related to a canonical pressure vessel and an optical mirror support structure are used to demonstrate the approach. Solutions are shown to satisfy minimum feature size requirements and designer-prescribed (process dependent) overhang constraint angles, while providing clear and crisp representations of topology. As observed in past works on overhang constraints, a clear trade-off is illustrated between the magnitude of the overhang constraint angle and the structural performance (mass or stiffness), with more strict requirements producing designs with lower performance.
Reducing Waste Outflow to Motivate Water Conservation
Authors: Halabieh S. , Shu L. H.
Published: November 2021

Resource-consumption systems can be defined by a resource inlet, a control volume where the resource is used, and a waste outlet. Specific to water, many existing conservation strategies focus on reducing the in-flow of water into a control volume. Instead, this work explores reducing waste out-flow, which causes accumulation in the control volume. This strategy aims to motivate users to reduce resource in-flow in response to accumulation in the control volume, and thus modify behavior.

To test this strategy, Amazon Mechanical Turk workers completed three randomly ordered handwashing simulations with different sink-outflow rates online. Study participants (N = 74) significantly reduced consumption of water when it accumulated quickly in the sink (p < 0.0001). Participants reduced water consumption, on average by 14% at lower outflow rates, as they decreased inflow rates to prevent sink overflow.

Many pro-environmental behavior interventions are limited in their reliance on user motivation and intention to reduce resource consumption. In contrast, the reduced-outflow intervention significantly reduced water usage (p < 0.001) of individuals, regardless of self-reported daily pro-environmental behavior. This result suggests that the developed intervention relies less on user intention. Overall results support that reducing outflow can increase sustainable user behavior when properly executed. In-person testing is discussed as future work.
Exploring a Temperature-Decreasing Shower Concept to Conserve Water and Energy
Authors: Saniei N. , Shibata E. , Lui S. , Magcalas J. , McPhee B. , Tariq S. , Shu L. H.
Published: November 2021

Climate change is threatening the availability, quality and quantity of water for basic human needs. In much of North America, showering is an activity that consumes significant water, as well as energy to heat the water. This study investigates the feasibility of an intervention that gradually decreases shower-water temperature to encourage shorter shower times, towards reduced water and energy usage.

The two parts of this work were performed over two academic years. The first part explored user acceptance in 23 study participants who underwent a shower while manually decreasing their own water temperature, as prescribed by a protocol. Immediately following the temperature-decreasing shower, participants were asked questions to assess their attitudes and willingness to use or install such a shower concept. Participants also completed questionnaires determining their regulatory focus and environmental attitudes, the effects of which on their attitudes about the shower concept are discussed.

Over 56% of participants were able to abide by the temperature-decreasing showering protocol. Out of 23 participants, only 3 found the temperature-decreasing shower experience to be negative, 12 were neutral, and the remaining 8 found the experience to be a positive one.

Given this result, the second part of the work implemented a microcontroller-based system that automatically controls shower temperature, pressure, and duration. This system is described and simulations are used to project the resource-saving potential of the concept.
Kinematic Modeling and Inverse Kinematics of Serial 6R Fragment of Molecule
Authors: Arikawa Keisuke
Published: November 2021

Depending on their mobilities around bond axes, molecules (e.g., proteins, DNA, and RNA) can be modeled as robotic manipulators. We focus on the serial 6R fragments, or the fragments containing six revolute joints connected in series, extracted from these molecules. We solved the inverse kinematics problems of the fragments. We obtained multiple conformations that maintained the relative position and orientation between both ends. Raghavan and Roth’s solution effectively conveys all real solutions. However, the solution is not directly applicable when some link lengths are zeros. To cope with the problem, in addition to the known method based on the modified elimination, we introduced the small-length link strategy. Here, by setting sufficiently small values for the zero-length links, we solved the inverse kinematics problems based on Raghavan and Roth’s solution combined with the symbolic formulation. Moreover, we formulated a method to systematically build manipulator models from structural data of molecules. We systematically identified the Danavit-Hartenberg parameters (link length, offset, and twist angle) and joint angles at the conformation in the structural data from the seven pairs of positions of atoms. Finally, using the structural data of a protein stored in the protein data bank, we demonstrated an application example of kinematic modeling and inverse kinematics calculation.
Normal Form of Bifurcation for Caputo-Hadamard Fractional Differential System With a Parameter
Authors: Yin Chuntao
Published: November 2021

This paper focuses on the normal form computation of the pitchfork bifurcation for the Caputo-Hadamard fractional differential system with a parameter. By using Taylor’s expansion and Implicit Function Theorem, we derive the normal form of the pitchfork bifurcation for the Caputo-Hadamard fractional differential system with a parameter.
Orientation Control of Self-Righting Tensegrity Landers
Authors: Zhang Alan , Hutchings Douglas , Gupta Mayank , Agogino Alice
Published: November 2021

Squishy Robotics, Inc. has developed a spherical sensor robot that can be rapidly deployed by air drops of up to 1,000 ft for emergency response situations to improve situational awareness for first responders. Although the tensegrity structure has successfully been shown to survive the drop, some payloads require orientation when they land. For example, a payload that contains sensors and communication equipment to relay the data may need the robot to be oriented such that the antennas are pointing upward, or some sensors are positioned in a specific plane for operation. This requirement presents a challenge for a tensegrity-based delivery system because the structure absorbs energy using passive compliance and bounces several times upon landing. Although active systems using motors and actuators could be used to control orientation after landing, they increase the overall weight and complexity of the system. This paper describes the research on a passive control solution that achieves the correct orientation by placing weights on selected rods forming an asymmetrically weighted tensegrity structure that preferentially rolls and orients itself during the impact process. The design approach is applied to three robot sizes and the self-righting behavior is validated through experimental results.
A Simple Approach for the Computation of Lyapunov-Floquet Transformations for the Mathieu Equation
Authors: Sharma Ashu
Published: November 2021

Lyapunov-Floquet (L-F) transformations reduce linear ordinary differential equations with time-periodic coefficients (so-called linear time-periodic systems) to equations with constant coefficients. The present work proposes a simple approach to construct L-F transformations. The solution of a linear time-periodic system can be expressed as a product of an exponential term and a periodic term. Using this Floquet form of a solution, the ordinary differential equation corresponding to a linear time-periodic system reduces to an eigenvalue problem. Next, eigenanalysis is performed to obtain the general solution and subsequently, the state transition matrix of the time-periodic system is constructed. Then, the Lyapunov-Floquet theorem is used to compute L-F transformation. The inverse of L-F transformation is determined by defining the adjoint system to the time-periodic system. Mathieu equation is investigated in this work and L-F transformations and their inverse are generated for stable and unstable cases. These transformations are very useful in the design of controllers using time-invariant methods and in the bifurcation studies of nonlinear time-periodic systems.
Racing Driver Modeling Based on Driving Behavior
Authors: Wang Jinzhen , Cheng Yiming , Yu Liangyao
Published: November 2021

The driver model is an important link in the research of shared autonomy control. In order to simulate the driver’s handling characteristics in the complex human-vehicle-road closed-loop system, the driver model is required to accomplish the driving operation under specific working conditions. In this paper, a lateral-longitudinal combined racing driver model is designed. The lateral control model adopts the preview model with far and near viewpoints and the dynamic velocity controller is added into the longitudinal control model to obtain the expected speed of the target trajectory. Finally, the racing driver model proposed in this paper is validated through simulation on track conditions of FSAE. In the given conditions, the result shows the racing driver model outperforms the typical driver model in lateral path tracking and the speed of racing driver model is higher than typical model on straight and corners. Meanwhile, the representation of driving skills is a key step to enhance the adaptive control of vehicles in the future. The control parameters can be adjusted according to the driver’s skill information to make the vehicle control system adapt to the driver’s skill level. This paper introduces the method of driving skill recognition based on wavelet transform and Lipschitz singularity detection theory and the preliminary test results prove the feasibility of using this method to characterize the driver’s operating skill level.
A Graphical Stability Analysis Method for Cascade Conjugate Order Systems
Authors: Cetintas Gulten , Hamamci Serdar Ethem
Published: November 2021

The theory and applications of complex fractional analysis have recently become a hot topic in the fields of mathematics and engineering. Therefore, studies on the complex order systems and their subset called the complex conjugate order systems began to appear in the control community. On the other hand, the concept of stability has always been an important issue, especially in the analysis and control of dynamical systems. In this paper, a graphical method for stability analysis of the complex conjugate order systems is presented. Since the proposed method is based on the Mikhailov stability criterion known from the stability theory of integer order systems, it is named the generalized modified Mikhailov stability criterion. This method gives stability information about the higher order complex conjugate order systems, i.e. cascade conjugate order systems, according to whether it encloses the origin in the complex plane or not. Three simulation examples for the cascade conjugate order systems are given to show the effectiveness and reliability of the method presented. The results are verified by the poles on the first sheet of Riemann surface and also time responses of the systems, which are calculated analytically in a very complex way.
A User-Centered Medical Device Design Decision Making Approach Using Hybrid Rough Cooperative Game Model
Authors: Jing Liting , Ma Junfeng
Published: November 2021

With the advancement of new technologies and diverse customer-centered design requirements, the medical device design decision making becomes challenge. Incorporating multiple stakeholders’ requirements into the medical device design will significantly affect the market competitiveness and performance. The classic design decision making approaches mainly focused on design criteria priority determination and conceptual schemes evaluation, which lack the capacity of reflecting the interdependence of interest among stakeholders and capturing the ambiguous influence on the overall design expectations, leading to the unreliable decision making results. In order to relax these constraints in the medical device design, this paper incorporates rough set theory with cooperative game theory model to develop a novel user-centered design decision making framework. The proposed approach is composed of three components: 1) end/professional user needs identification and classification, 2) evaluation criteria correlation diagram and scheme value matrix establishment using rough set theory; and 3) fuzzy coalition utility model development to obtain optimal desirability considering users’ conflict interests. We used a blood pressure meter case study to demonstrate and validate the proposed approach. Compared with the traditional Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, the proposed approach is more robust.
A Strategy for Fine Mesh Resolution in Contact Mechanics
Authors: Chauda Gaurav , Segalman Daniel J.
Published: November 2021

To obtain detail in elastic, frictional contact problems involving contact many — at least tens, and more suitably hundreds [1] — of nodes are necessary over the contact patch. Generally, this fine discretization results in intractable numbers of system equations that must be solved, but this problem is greatly mitigated when the elasticity of the contacting bodies is represented by elastic compliance matrices rather than stiffness matrices.

An examination of the classical analytic expressions for the contact of disks — an example of smooth contact — shows that for most standard engineering metals, such as brass, steel, or titanium, the pressures that would cause more than one degree of arc of contact would push the materials past the elastic limit.

The discretization necessary to capture the interface tractions would be on the order of at least tens of nodes. With the resulting boundary integral formulation would involve several hundreds of nodes over the disk, and the corresponding finite element mesh would have tens of thousands. The resulting linear system of equations must be solved at each load step and the numerical problem becomes extremely difficult or intractable.

A compliance method of facilitating extremely fine contact patch resolution can be achieved by exploiting Fourier analysis and the Michell solution. The advantages of this compliance method are that only degrees of freedom on the surface are introduced and those not in the region of contact are eliminated from the system of equations to be solved.
Automatic Composition of Encoding Scheme and Search Operators in System Architecture Optimization
Authors: Apaza Gabriel , Selva Daniel
Published: November 2021

The purpose of this paper is to propose a new method for the automatic composition of both encoding schemes and search operators for system architecture optimization. The method leverages prior work that identified a set of six patterns that appear often in system architecture decision problems (down-selecting, combining, assigning, partitioning, permuting, and connecting). First, the user models the architecture space as a directed graph, where nodes are decisions belonging to one of the aforementioned patterns, and edges are dependencies between decisions that affect architecture enumeration (e.g., the outcome of decision 1 affects the number of alternatives available for decision 2). Then, based on a library of encoding scheme and operator fragments that are appropriate for each pattern, an algorithm automatically composes an encoding scheme and corresponding search operators by traversing the graph. The method is demonstrated in two case studies: a study integrating three architectural decisions for constructing a portfolio of earth observing satellite missions, and a study integrating eight architectural decisions for designing a guidance navigation and control system. Results suggest that this method has comparable search performance to hand-crafted formulations from experts. Furthermore, the proposed method drastically reducing the need for practitioners to write new code.
Reliability-Based Co-Design of Lithium-Ion Batteries for Enhanced Fast Charging and Cycle Life Performances
Authors: Cui Tonghui , Wang Pingfeng
Published: November 2021

As enablers of electric vehicles, lithium-ion batteries are drawing much attention for their high energy density and low self-discharging rate. However, “range anxiety” has remained a significant hindrance to its further development. Of the many design objectives, minimizing the charging time and maximizing the cycle life are conflicting design objectives. In the past, enormous efforts have been carried out to resolve the dispute between high charging rates and large capacity losses by either improving the battery design or optimizing the charging/discharging protocols. However, the battery design and the control are usually coupled that integration of the two discipline, or control co-design, may offer improved performances as compared with traditional sequential optimization approaches. In an previous study, we have shown that efficient control co-design is achievable for Lithium-ion batteries through surrogate modeling. In this work, a reliability-based design optimization framework is integrated to guarantee the performances under parametric uncertainties. The challenges, such as simultaneous model update for the dynamic system and excessive computation burden due to optimal control and reliability assessment, are resolved through coupling the first principle model and the empirical models by an adaptive surrogate modeling process. Such a combination captures the multi-scale nature of the battery and allows efficient numerical analysis for the reliability-based co-design (RBCD) problem. A nested co-design approach and a double-loop reliability assessment method were implemented. The results show that the algorithm can shorten the charging time while satisfying the probability constraint on the cycle-life performances under parametric uncertainties.
Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment
Authors: Hu Shuaizhou , Zhang Xinyao , Liao Hao-yu , Liang Xiao , Zheng Minghui , Behdad Sara
Published: November 2021

Remanufacturing sites often receive products with different brands, models, conditions, and quality levels. Proper sorting and classification of the waste stream is a primary step in efficiently recovering and handling used products. The correct classification is particularly crucial in future electronic waste (e-waste) management sites equipped with Artificial Intelligence (AI) and robotic technologies. Robots should be enabled with proper algorithms to recognize and classify products with different features and prepare them for assembly and disassembly tasks. In this study, two categories of Machine Learning (ML) and Deep Learning (DL) techniques are used to classify consumer electronics. ML models include Naïve Bayes with Bernoulli, Gaussian, Multinomial distributions, and Support Vector Machine (SVM) algorithms with four kernels of Linear, Radial Basis Function (RBF), Polynomial, and Sigmoid. While DL models include VGG-16, GoogLeNet, Inception-v3, Inception-v4, and ResNet-50. The above-mentioned models are used to classify three laptop brands, including Apple, HP, and ThinkPad. First the Edge Histogram Descriptor (EHD) and Scale Invariant Feature Transform (SIFT) are used to extract features as inputs to ML models for classification. DL models use laptop images without pre-processing on feature extraction. The trained models are slightly overfitting due to the limited dataset and complexity of model parameters. Despite slight overfitting, the models can identify each brand. The findings prove that DL models outperform them of ML. Among DL models, GoogLeNet has the highest performance in identifying the laptop brands.
Physics-Informed Machine Learning for Degradation Diagnostics of Lithium-Ion Batteries
Authors: Thelen Adam , Lui Yu Hui , Shen Sheng , Laflamme Simon , Hu Shan , Hu Chao
Published: November 2021

State of health (SOH) estimation of lithium-ion batteries has typically been focused on estimating present cell capacity relative to initial cell capacity. While many successes have been achieved in this area, it is generally more advantageous to not only estimate cell capacity, but also the underlying degradation modes which cause capacity fade because these modes give further insight into maximizing cell usage. There have been some successes in estimating cell degradation modes, however, these methods either require long-term degradation data, are demonstrated solely on artificially constructed cells, or exhibit high error in estimating late-life degradation. To address these shortfalls and alleviate the need for long-term cycling data, we propose a method for estimating the capacity of a battery cell and diagnosing its primary degradation mechanisms using limited early-life degradation data. The proposed method uses simulation data from a physics-based half-cell model and early-life degradation data from 16 cells cycled under two temperatures and C rates to train a machine learning model. Results obtained from a four-fold cross validation study indicate that the proposed physics-informed machine learning method trained with only 60 early life data (five data from each of the 12 training cells) and 30 high-degradation simulated data can decrease estimation error by up to a total of 9.77 root mean square error % when compared to models which were trained only on the early-life experimental data.
Design 3D Printed Coils for WPT
Authors: Xu Jun , Doubrovski E. (Zjenja) L. , Geraedts Jo M. P. , Song Yu (Wolf)
Published: November 2021

The geometric shapes of coils influence the performance of a 3D IPT system. In this paper, we proposed a 3D coil design method based on (3D) printing electronics. Given a 3D transmitter coil, the center position of the receiver coil is estimated as a random seed position in the corresponding 3D surface first. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the coil. For each extension of the coil, i.e. a new turn, the shape of the coil is optimized by calculating the convex hull of the new turn in the 2D projection plane. Using this method, we are able to generate a receiver coil to transmit “just enough” power at a given seed position. Then, by fixing the receiver coil, the 3D shape of the transmitter coil can be optimized as well. This zig-zag optimization process iterates until there are few changes of the position and 3D shapes in the iteration. Experiment results with Ansys Maxwell verified the effectiveness of the proposed 3D coil design method, and highlighted possible future research directions as well.
Modelling and Parameter Identification for a Flexible Rotor With Periodic Impacts
Authors: Holzinger Stefan , Schieferle Manuel , Gerstmayr Johannes , Hofer Manfred , Gutmann Christoph
Published: November 2021

The ability of a multibody dynamics model to accurately predict the behavior of a real system depends heavily on the correct choice of model parameters. The identification of unknown system parameters, which cannot be directly computed or measured is usually time consuming and costly. If experimental measurement data of the real system is available, the parameters in the mathematical model can be determined by minimizing the error between the model response and the measurement data. The latter task can be solved by means of optimization. While many optimization methods are available, optimization with a genetic algorithm is a promising approach for searching optimal solutions for complex engineering problems, as reported in a paper of one of the authors. So far, however, there is no general approach how to apply genetic optimization algorithms for complex multibody system dynamics models in order to obtain unknown parameters automatically — which is however of great importance when dealing with real flexible multibody systems. In the present paper we present a methodology to determine several unknown system parameters applied to a flexible rotor system which is excited with periodic impacts. Experiments were performed on the physical system to obtain measurement data which is used to identify the impact force as well as the support stiffnesses of the rotor system using genetic optimization.
Development and Characterization of a Modular Soft Actuator Enabled Elbow Exoskeleton for Assistive Movements
Authors: Erel Veysel , Singh Inderjeet , Lindsay Alexandra R. , Shi W. Y. , Wijesundara Muthu B. J.
Published: November 2021

Exoskeletons are poised to provide motion assistance to aid in rehabilitation and compensate for muscle weaknesses, augment human performance, and reduce repetitive stress injuries in healthcare, industry, and occupation settings, respectively. Soft actuator enabled systems are gaining widespread attention due to their mechanical simplicity, low weight, and compliance to the human body. Regardless of promises shown, the progress for these systems is slow due to a wide variety of actuator types and geometries, which complicate designs and model predictive performance to create application-specific systems. Learning from conventional hard robotic actuator approaches, this paper investigates a modular actuator concept that can be used for creating many exoskeletons and is easily customized for fitting different sized humans, joint types, and application scenarios. The preliminary investigation details the development of an elbow exoskeleton by implementing a modular corrugated diaphragm actuator arranged in a serial configuration. Numerical simulation and experimental evaluations were carried out to investigate the torque, load-bearing, and motion characteristics of the exoskeleton. Results confirmed the viability of the concept by showing that the exoskeleton can provide assistive motion to a forearm and hand of average weight. Additionally, the exoskeleton is able to apply continuous passive motion to an elbow joint, which can be used in rehabilitation settings.
What Happened to Roth’s Design Catalogues? - A Review of Usage and Future Research
Authors: Inkermann David
Published: November 2021

In 1971, Roth and his group first proposed an algorithmic selection procedure for the design of mechanical systems using catalogues. Core element were Design Catalogues that provide established solution elements, models and operations for different engineering tasks. In different books and guidelines, the theory of Design Catalogues was promoted and comprehensive catalogues were elaborated. These works highlight the basic character as structured information bases, with knowledge and access criteria tailored to the needs of engineering tasks. An essential characteristic is the consequent classification of solutions, objects, and operations and thus a complete exploration of the area of interest. In science and industrial practice, Design Catalogues were recognized as tools to structure knowledge and improve reuse of solutions, operations or objects that are frequently used in the design process. This contribution analyses the use and evolution of Design Catalogues in the past 50 years. Main objective is to point out how Design Catalogues and underlying principles and tools to structure design knowledge were used in different fields of application. Moreover, future fields of research to classify knowledge elements and identify suitable access criteria to build up Design Catalogues will be pointed out.
Using Unsupervised Learning for Regulating Deposition Speed During Robotic Wire Arc Additive Manufacturing
Authors: Kulkarni Ashish , Bhatt Prahar M. , Kanyuck Alec , Gupta Satyandra K.
Published: November 2021

Robotic Wire Arc Additive Manufacturing (WAAM) is the layer-by-layer deposition of molten metal to build a three-dimensional part. In this process, the fed metal wire is melted using an electric arc as a heat source. The process is sensitive to the arc conditions, such as arc length. While building WAAM parts, the metal beads overlap at corners causing material accumulation. Material accumulation is undesirable as it leads to uneven build height and process failures caused by arc length variation. This paper introduces a deposition speed regulation scheme to avoid the corner accumulation problem and build parts with uniform build height. The regulated speed has a complex relationship with the corner angle, bead geometry, and molten metal dynamics. So we need to train a model that can predict suitable speed regulations for corner angles encountered while building the part. We develop an unsupervised learning technique to characterize the uniformity of the bead profile of a WAAM built layer and check for anomalous bead profiles. We train a model using these results that can predict suitable speed regulation parameters for different corner angles. We test this model by building a WAAM part using our speed regulation scheme and validate if the built part has uniform build height and reduced corner defects.
Orientation Optimization in Additive Manufacturing: Evaluation of Recent Trends
Authors: Bushra Jannatul , Budinoff Hannah D.
Published: November 2021

Build orientation in additive manufacturing influences the mechanical properties, surface quality, build time, and cost of the product. Rather than relying on trial-and-error or prior experience, the choice of build orientation can be formulated as an optimization problem. Consequently, orientation optimization has been a popular research topic for several decades, with new optimization methods being proposed each year. However, despite the rapid pace of research in additive manufacturing, there has not been a critical comparison of different orientation optimization methods. In this study, we present a critical review of 50 articles published since 2015 that proposes a method for orientation optimization for additive manufacturing. We classify included papers by optimization methods used, AM process modeled, and objective functions considered. While the pace of research in recent years has been rapid, most approaches we identified utilized similar objective functions and computational optimization techniques to research from the early 2000s. The most common optimization method in the included research was exhaustive search. Most methods focused on broad applicability to all additive manufacturing processes, rather than a specific process, but a few works focused on powder bed fusion and material extrusion. We also identified several areas for future work including integration with other design and process planning tasks such as topology optimization, more focus on practical implementation with users, testing of computational efficiency, and experimental validation of utilized objective functions.
Optimization of Permanent Magnet Structure Parameters in Tubular Permanent Magnet Synchronous Linear Motor for HF Square-Wave Injection Sensorless Algorithm
Authors: Zhang Luhong , Li Bingran , Zhang Chunlei , Zhang Hui , Ye Peiqing
Published: November 2021

The high frequency (HF) square-wave injection sensorless algorithm uses saliency to estimate the motor position affected by the inductance. The structure of the permanent magnets will affect the inductance of the motor, then affect the position estimation performance of the sensorless algorithm. This paper studies the relationship between the inductance and the position estimation accuracy of the HF square-wave injection sensorless algorithm for tubular permanent magnet synchronous linear motor (TPMSLM). Through the finite element simulation, the distribution law of the TPMSLM inductance with the change of the PM structure is quantitatively analyzed, and the influence of the PM structure parameters on the differential amplitude of the HF current is given. The HF square-wave voltage is injected into the stationary reference frame, and the frequency is half of the PWM switching frequency. The HF current differential equation is obtained without any filter, and the estimated position of the mover is extracted by a phase-locked loop. Finally, the experiment of sensorless position estimation is carried out by two prototypes with different PM structure parameters at different speeds, verifying the effectiveness of the analysis.
Stretch-Shortening Cycle Performance and Muscle–Tendon Properties in Dancers and Runners
Authors: Rice Paige E. , Nishikawa Kiisa , Zwetsloot Kevin A. , Bruce Amelia S. , Guthrie Caroline D. , Nimphius Sophia
Published: November 2021

The purpose of this investigation was to elucidate whether ankle joint stretch-shortening cycle performance, isometric and isokinetic plantarflexion strength, and maximal Achilles tendon force and elongation differ between dancers, endurance runners, and untrained controls. To differentiate between dancers, endurance runners, and controls, the authors measured maximal Achilles tendon force and elongation during isometric ramp contractions with ultrasonic imaging, maximal isometric and isokinetic plantarflexion strength with dynamometry, and stretch-shortening cycle function during countermovement hopping and 30-cm drop hopping with a custom-designed sled. The Achilles tendon of dancers elongated significantly (P ≤ .05) more than runners and controls. Dancers were significantly stronger than controls during isometric contractions at different ankle angles. Concentric and eccentric strength during isokinetic contractions at 60°·s−1 and 120°·s−1 was significantly higher in dancers and runners than controls. Dancers hopped significantly higher than runners and controls during hopping tasks. Dancers also possessed significantly greater countermovement hop relative peak power, drop hop relative impulse, and drop hop relative peak power than controls. Finally, dancers reached significantly greater velocities during countermovement hops than runners and controls. Our findings suggest dancing and running require or likely enhance plantarflexion strength. Furthermore, dancing appears to require and enhance ankle joint stretch-shortening cycle performance and tendon elongation.
Noninvasive detection of spatiotemporal activation-repolarization interactions that prime idiopathic ventricular fibrillation
Authors: Cluitmans Matthijs J. M. , Bear Laura R. , Nguyên Uyên C. , van Rees Bianca , Stoks Job , ter Bekke Rachel M. A. , Mihl Casper , Heijman Jordi , Lau Kevin D. , Vigmond Edward , Bayer Jason , Belterman Charly N. W. , Abell Emma , Labrousse Louis , Rogier Julien , Bernus Olivier , Haïssaguerre Michel , Hassink Rutger J. , Dubois Rémi , Coronel Ruben , Volders Paul G. A.
Published: November 2021

Premature beats originating in clinically concealed areas of local early repolarization promote ventricular arrhythmias and sudden cardiac arrest.
Contrasting Microbiome Dynamics of Putative Denitrifying Bacteria in Two Octocoral Species Exposed to Dissolved Organic Carbon (DOC) and Warming
Authors: Xiang Nan , Hassenrück Christiane , Pogoreutz Claudia , Rädecker Nils , Simancas-Giraldo Susana Marcela , Voolstra Christian R. , Wild Christian , Gärdes Astrid
Published: November 2021

Octocorals are important members of reef-associated benthic communities that can rapidly replace scleractinian corals as the dominant ecosystem engineers on degraded reefs. Considering the substantial change in the (a)biotic environment that is commonly driving reef degradation, maintaining a dynamic and metabolically diverse microbial community might contribute to octocoral acclimatization and ecological adaptation.
Functional Diversity of TonB-Like Proteins in the Heterocyst-Forming Cyanobacterium
Anabaena
sp. PCC 7120
Authors: Schätzle Hannah , Arévalo Sergio , Fresenborg Leonard , Seitz Hans-Michael , Flores Enrique , Schleiff Enrico
Published: November 2021

The genomes of many organisms encode more than one TonB protein, and their number does not necessarily correlate with that of TonB-dependent outer membrane transporters. Consequently, specific as well as redundant functions of the different TonB proteins have been identified.
Exploring experiences of infertility amongst women and men in low-income and middle-income countries: protocol for a qualitative systematic review
Authors: Sripad Pooja , Desai Sapna , Regules Ricardo , Chakraborty Suchandrima , Habib Helen , Viloria Anny Rodriguez , Ankomah Augustine , Fuseini Kamil , Jarvis Leah , Kirk Karen , Tawab Nahla , Hindin Michelle
Published: November 2021

Introduction

Infertility is increasingly recognised as a global public health issue for women and men that merits further investigation to support policy and programming. While research in high-income settings has examined the consequences of infertility and access to services, there has been limited synthesis of how individuals experience infertility in low-income and middle-income countries (LMICs). This protocol describes a systematic review that will synthesise qualitative evidence on experiences of infertility among women and men in LMICs.

Methods and analysis

The review will follow the Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) guidelines for reporting on qualitative evidence syntheses. The study team will search for published literature in PubMed, CINAHL and Scopus and PsycINFO databases and review available grey literature. Using Covidence software, two independent reviewers will conduct title and abstract screening based on inclusion and exclusion criteria, followed by full-text reviews and extraction by a larger team. Quality will be appraised using an adapted version of the Critical Appraisal Skills Programme guidelines. We will conduct thematic synthesis to characterise individual experiences and related factors at the individual, interpersonal, community and health system levels. We will develop a conceptual framework to describe evidence on experiences of infertility in LMICs and to help inform interventions across settings.

Ethics and dissemination

This protocol has been internally approved as exempt by the Institutional Review Board of the Population Council, as it does not involve contact with human subjects or personally identifying data. Results of the review will be published in a peer-reviewed journal and will be used to inform future infertility research and programming in LMICs.

PROSPERO registration number

CRD42021227742.
Identifying barriers to evidence-based care for sickle cell disease: results from the Sickle Cell Disease Implementation Consortium cross-sectional survey of healthcare providers in the USA
Authors: Smeltzer Matthew P , Howell Kristen E , Treadwell Marsha , Preiss Liliana , King Allison A , Glassberg Jeffrey A , Tanabe Paula , Badawy Sherif M , DiMartino Lisa , Gibson Robert , Kanter Julie , Klesges Lisa M , Hankins Jane S
Published: November 2021

Objectives

Sickle cell disease (SCD) leads to chronic and acute complications that require specialised care to manage symptoms and optimise clinical results. The National Heart Lung and Blood Institute (NHLBI) evidence-based guidelines assist providers in caring for individuals with SCD, but adoption of these guidelines by providers has not been optimal. The objective of this study was to identify barriers to treating individuals with SCD.

Methods

The SCD Implementation Consortium aimed to investigate the perception and level of comfort of providers regarding evidence-based care by surveying providers in the regions of six clinical centres across the USA, focusing on non-emergency care from the providers’ perspective.

Results

Respondents included 105 providers delivering clinical care for individuals with SCD. Areas of practice were most frequently paediatrics (24%) or haematology/SCD specialist (24%). The majority (77%) reported that they were comfortable managing acute pain episodes while 63% expressed comfort with managing chronic pain. Haematologists and SCD specialists showed higher comfort levels prescribing opioids (100% vs 67%, p=0.004) and managing care with hydroxyurea (90% vs 51%, p=0.005) compared with non-haematology providers. Approximately 33% of providers were unaware of the 2014 NHLBI guidelines. Nearly 63% of providers felt patients’ medical needs were addressed while only 22% felt their mental health needs were met.

Conclusions

A substantial number of providers did not know about NHLBI’s SCD care guidelines. Barriers to providing care for patients with SCD were influenced by providers’ specialty, training and practice setting. Increasing provider knowledge could improve hydroxyurea utilisation, pain management and mental health support.