bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Parallel Elastic and Series Elastic Configurations of Vertical Hopping Spring Mass Model Controlled With Virtual Tuning of Damping
Authors: Candan Sinan Sahin , Saranli Uluc , Yazicioglu Yigit
Published: November 2020

Spring Loaded Inverted Pendulum (SLIP) is a simple, descriptive and accurate model to study dynamic legged locomotion. Critical design decisions to realize SLIP based legged robots with high energy efficiency and control accuracy are actuation topology and controller. Recent studies converge on series elastic actuation (SEA) and parallel elastic actuation (PEA) regarding actuation whereas, a recently introduced control method, virtual tuning of damping (VTD) have proven to be superior for SEA over other control techniques. However, actuation topology is still under discussion and it is a highly coupled problem with the control approach. In this study, vertical hoppers with PEA and SEA configurations are compared under VTD controller to determine the one results in better energy efficiency and accuracy. PEA and SEA models are extended with drive-train details to provide more realistic results. Models are simulated with various gearboxes and motors to understand their effects. Comparisons among optimum topologies showed that VTD-PEA achieves 0.02% percent apex error where VTD-SEA achieves 0.5% apex-to-apex accuracy (25 times). VTD-PEA also achieved 40% better energy efficiency and 38% higher cost of transport than VTD-SEA.
Deep Learning of (Periodic) Minimal Coordinates for Multibody Simulations
Authors: Angeli Andrea , Naets Frank , Desmet Wim
Published: November 2020

Mechanical systems are typically described through multi-body models with redundant coordinates, related by imposed constraints, where the dynamics is expressed with Differential Algebraic Equations. Alternatively, for rigid models, it may be preferable to employ minimal coordinates that do not require additional constraints, thus leading to Ordinary Differential Equations. However, to reduce a general multibody model to minimal coordinates and perform the simulation in the reduced space, the mapping between the minimal coordinates and the full coordinates is required. In this work, it is proposed to approximate such mapping using a neural network. In order to avoid overfitting and guarantee a continuous description of the solution manifold, the multibody dynamics information are included in the neural network training. The particular case where periodic minimal coordinates are required is treated and validated. In general, the methodology can be used when the mapping is unknown such as for spatial mechanisms with closed loops.
The Material Testing of Nanoparticle Doped 3D Printed ABS Strain Gages for Resisitance and Stiffness
Authors: Damas Sara M. , Turner Cameron J.
Published: November 2020

Additive manufacturing methods are becoming more prominent in the world of design and manufacturing due to their reduction of material waste versus traditional machining methods such as milling. The technology to 3D print has been around since the 1970’s. In today’s present time, we now can multi-material 3D print, however. even though we have the technology for multi-material 3D printing, standards in this field are severely lacking. Research on multi-material 3D printing and/or the combination of 3D printing filaments combined with nanoparticles is needed. One of the most common methods of 3D printing is fused deposition modeling (FDM). In this research, FDM was used to dope Acrylonitrile Butadiene Styrene (ABS), to introduce conductive properties for strain measurements.

The researchers in this paper used N-Methyl-2-Pyrrolidinone (NMP) to bind the selected nanoparticles. In the first experiment the researchers tested the conductivity of the strain gages, while in the next experiment they studied the effect the various nanoparticles had on the stiffness of the 3D printed ABS strain gages. This extensive and detailed study concluded several points. First, nickel nanoparticles consistently yields the least amount of resistance. Second, multiple binder doped nanoparticle layers yield the lowest resistance. Third, NMP, does indeed improve the performance of the nanoparticles. Finally, the research demonstrated that the various nanoparticles used, when bound increased the stiffness of the ABS strain gages.
Limits of Extramobile and Intramobile Motion of Cylindrical Developable Mechanisms
Authors: Butler Jared , Greenwood Jacob , Howell Larry L. , Magleby Spencer P.
Published: November 2020

Mechanisms that can both deploy and perform desired tasks offer a multifunctional advantage over traditional mechanisms. Developable mechanisms (DMs) are devices capable of conforming to a predetermined developable surface and deploying from that surface to achieve specific motions. This paper presents new terminology that defines motion of developable mechanisms while interior and exterior to a developable surface. The limits of motion are identified using defined conditions, and it is shown that the more difficult of these conditions may be treated as a non-factor during the design of cylindrical developable mechanisms given certain assumptions.
Unsupervised Method of Determining Cycle Times of Manual Assembly Processes
Authors: Renu Rahul Sharan
Published: November 2020

In recent years, wrist-worn devices that contain inertial measurement units have become prevalent. The data from these sensors can be used to estimate characteristics of manual processes in a manufacturing environment. The goal of this research is to determine cycle times of manually performed assembly processes using data from wrist-worn inertial sensors. Specifically, this work explores an unsupervised method of analyzing time series data to extract patterns (motifs) which represent individual cycles of an operation. From here, cycle time is computed by applying knowledge of the frequency of data collection. Testing shows that the mean cycle times obtained from stopwatch are statistically indifferent from those obtained from the proposed approach. Furthermore, results suggest that the proposed approach is insensitive to high frequency noise in the data. These encouraging results warrant further investigation and more testing.
Multi-Inputs/Outputs and Cascadable MEMS Resonator-Based Computing Devices
Authors: Tella Sherif A. , Younis Mohammad I.
Published: November 2020

Due to the increasing demand for smarter solutions and embedded systems, MEMS resonator-based computing devices have been under considerable attention for their simplicity and prospect of low computational power. However, most complex logic functions require multi-input/output lines that are cascadable such that the outputs of one device can be used as inputs into subsequent devices for practical applications, and this is a current limitation for MEMS logic devices. In this study, we demonstrate multi-inputs/outputs half-adder function, AND, and XOR logic gates on the basis of activating and deactivating the localization and delocalization of the multi vibrational modes of a single MEMS resonator with improved energy efficiency.
Structural Design Exploration for Product Architecture Design
Authors: Toi Masato , Nomaguchi Yutaka , Fujita Kikuo
Published: November 2020

This paper proposed a design support method based on structuralization and analysis of various design candidates of product architecture design. The product architecture is a basic scheme that assigns the function of the product to physical components. In the conventional modular design method, a concise model, i.e., a graph or a matrix, is used to express the interactions of the system’s components and aims to support the designer grasping the system behavior. The Design Structure Matrix (DSM) is a representative model of system architecture and enables quantitative evaluation of design candidates. While various design candidates are generated through mathematical operations, it is difficult to understand their relationships from simple comparisons because of discrete behavior and the size of the problem. It must be a critical issue at the stage of selecting and interpreting the design candidates. In the proposed method, the design candidates are classified and structuralized as a dendrogram by the hierarchical clustering method. The comparison of clusters of each branch of dendrogram clarifies the system leverage points. The information of the system is summarized into the hierarchical tree-shaped graph that corresponds to the dendrogram. The designer can explore the design candidates with such a graph-based based interpretation of underlying structures effectively.
Adaptive Linear Programming Algorithm With Parameter Learning for Managing Engineering-Design Problems
Authors: Guo Lin , Balu Nellippallil Anand , Smith Warren F. , Allen Janet K. , Mistree Farrokh
Published: November 2020

The adaptive linear programming (ALP) algorithm is an extension of the sequential linear programming algorithm where nonlinear formulations are iteratively approximated as linear formulations linearized about an iteration starting point. In the ALP algorithm, heuristics are used to determine the value of a critical parameter, namely, the reduced move coefficient (RMC). The RMC defines how far to move towards the solution of iteration “n” from the starting point for iteration “n” in specifying the starting point for iteration “n+1”. The RMC choice affects the efficacy of the approximation; however, there is no mechanism of evaluating the algorithm performance with respect to the RMC value so as to improve the design efficiency and effectiveness. This limitation is addressed in this paper.

In this paper, we enhance the ALP algorithm with parameter learning (ALPPL) and generalize to make the knowledge gained reusable. We propose a three-step procedure of rule-based parameter learning leading to robust solutions. An industry-inspired problem, the integrated design of a hot rolling process chain for the production of a steel rod, is used to demonstrate the implementation. The three-step procedure could be used to improve other critical parameter determinations, especially when there is a lack of mechanisms for algorithm-performance evaluation, evaluation criteria vary with problems, or heuristics are over-used.
Multi-Context Generation in Virtual Reality Environments Using Deep Reinforcement Learning
Authors: Cunningham James , Lopez Christian , Ashour Omar , Tucker Conrad S.
Published: November 2020

In this work, a Deep Reinforcement Learning (RL) approach is proposed for Procedural Content Generation (PCG) that seeks to automate the generation of multiple related virtual reality (VR) environments for enhanced personalized learning. This allows for the user to be exposed to multiple virtual scenarios that demonstrate a consistent theme, which is especially valuable in an educational context. RL approaches to PCG offer the advantage of not requiring training data, as opposed to other PCG approaches that employ supervised learning approaches. This work advances the state of the art in RL-based PCG by demonstrating the ability to generate a diversity of contexts in order to teach the same underlying concept. A case study is presented that demonstrates the feasibility of the proposed RL-based PCG method using examples of probability distributions in both manufacturing facility and grocery store virtual environments. The method demonstrated in this paper has the potential to enable the automatic generation of a variety of virtual environments that are connected by a common concept or theme.
Recursive Newton-Euler Dynamics and Sensitivity Analysis for Robot Manipulator With Revolute Joints
Authors: Barman Shuvrodeb , Xiang Yujiang
Published: November 2020

In this study, recursive Newton-Euler sensitivity equations are derived for robot manipulator motion planning problems. The dynamics and sensitivity equations depend on the 3 × 3 rotation matrices based on the moving coordinates. Compared to recursive Lagrangian formulation, which depends on 4 × 4 Denavit-Hartenberg (DH) transformation matrices, the moving coordinate formulation increases computational efficiency significantly as the number of matrix multiplications required for each optimization iteration is greatly reduced. A two-link manipulator time-optimal trajectory planning problem is solved using the proposed recursive Newton-Euler dynamics formulation. Only revolute joint is considered in the formulation. The predicted joint torque and trajectory are verified with the data in the literature. In addition, the optimal joint forces are retrieved from the optimization using recursive Newton-Euler dynamics.
Predictive Human-in-the-Loop Simulations for Assistive Exoskeletons
Authors: Zhou Xianlian
Published: November 2020

Design and evaluation of exoskeletons is often a time consuming and costly process that involves prototyping, human testing, and multiple design iterations. For active exoskeletons, the primary challenge is to detect the wearer’s movement intent and provide potent assistance, which often requires sophisticated control algorithms. The goal of this study is to integrate human musculoskeletal models with robot modeling and control for virtual human-in-the-loop evaluation of exoskeleton design and control. We present potential strategies for assisting various human motions such as squatting, lifting, walking, and running. Several exoskeleton designs (for back, upper extremity, and lower extremity) and their control methods are evaluated with an integrated human-in-the-loop simulation approach to study their functionalities and biomechanical effects on the wearer’ musculoskeletal system. We hope this simulation paradigm can be utilized for virtual design and evaluation of exoskeletons and pave the way to build or optimize exoskeletons.
An Image-Based Approach to Variational Path Synthesis of Linkages
Authors: Deshpande Shrinath , Purwar Anurag
Published: November 2020

This paper brings together computer vision, mechanism synthesis, and machine learning to create an image-based variational path synthesis approach for linkage mechanisms. An image-based approach is particularly amenable to mechanism synthesis when the input from mechanism designers is deliberately imprecise or inherently uncertain due to the nature of the problem. In addition, it also lends itself naturally to the creation of a unified approach to mechanism synthesis since pixels do not care if they were generated from a four-bar or six-bar. Path synthesis problem has generally been solved for a set of precision points on the intended path such that the designed mechanism passes through those points. This approach usually leads to a small set of over-fitting solutions to the particular precision points. However, most kinematic synthesis problems are concept generation problem where a designer cares more about generating a large number of plausible solutions. This paper models the input curve as a probability distribution of image pixels and employs a probabilistic generative model to capture the inherent uncertainty in the input. In addition, it gives feedback on the input quality and provides corrections for a more conducive input. The image representation allows for capturing local spatial correlations, which plays an important role in finding a variety of solutions with similar semantics as the input curve.
Design Framework for Multi-Section Shape Memory Alloy Axial Actuators Considering Material and Geometric Uncertainties
Authors: Guan Weilin , Peraza Hernandez Edwin A.
Published: November 2020

Shape memory alloys are metallic materials with the capability of performing as high energy density actuators driven by temperature control. This paper presents a design framework for shape memory alloy (SMA) axial actuators composed of multiple wire sections connected in series. The various wire sections forming the actuators can have distinct cross-sectional areas and lengths, which can be modulated to adjust the overall thermomechanical response of the actuator. The design framework aims to find the optimal cross-sectional areas and lengths of the wire sections forming the axial actuator such that its displacement vs. temperature actuation path approximates a target path. Constraints on the length-to-diameter aspect ratio and stress of the wire sections are incorporated. A reduced-order numerical model for the multi-section SMA actuators that allows for efficient design evaluations is derived and implemented. An approach to incorporate uncertainty in the geometry and material parameters of the actuators within the design framework is implemented to allow for the determination of robust actuator designs. A representative application example of the design framework is provided illustrating the benefits of using multiple wire sections in axial actuators to modulate their overall response and approximate a target displacement vs. temperature actuation path.
Design of Tensegrity-Based Lattices With Engineered Load-Bearing and Thermal Expansion Properties
Authors: Baldwin Drake D. , Peraza Hernandez Edwin A.
Published: November 2020

Tensegrity lattices are networks of axially loaded members designed to efficiently use material and exhibit properties such as minimum mass load-carrying or energy absorption capabilities. This work entails the modeling and design of tensegrity “D-bar” lattices with specified orthotropic compressive strength. The objectives for the design of the lattices include minimum mass density and minimum error between the orthotropic coefficients of thermal expansion (CTEs) of the lattice and given target values. The studied D-bar structures are formed by joining two equal pyramids base-to-base where tensile strings form the edges of the pyramid bases and compressive bars form the remaining edges. Orthorhombic lattices having D-bars as their edges are designed to support compressive forces and exhibit positive, zero, or negative CTE values along their three principal directions. It is investigated how the geometry of the individual D-bar components may be adjusted, for the given compressive strength, to prevent local yielding and buckling failure with the minimum required material. Analytical formulas for the minimum density and the CTE of the D-bar lattices are provided, and a numerical framework for the integration of these formulas along with size and topological constraints is developed. Design trade-offs between minimum lattice density and minimum error from the target CTE, which are found to be competing structural performance metrics, are visualized and investigated.
Design and Simulations of a Novel Stiction-Free Laterally Actuated NEM Relay With Flexible Source-Drain Contact
Authors: Zandigohar Mehrdad , Shavezipur Mohammad
Published: November 2020

A novel design for laterally actuated nanoelectromechanical (NEM) relays with flexible source-drain contact is presented. The design uses a thin curved source that can provide expandable contact area between the source and the drain in ON-STATE position. The presence of the thin film curved source creates a local nonlinear stiffness in addition to the main stiffness of the source beam. This additional stiffness not only controls the contact area with over-drive voltage after the pull-in, but can also generate repulsive force when the actuation voltage is removed to separate the two contacting surfaces. The additional repulsive force creates a “peel-off” separation mechanism and can overcome relatively large adhesion forces. Finite element simulations are used to verify the applicability of this design and ANSYS® APDL structural solver and contact technology is used to determine the nonlinear stiffness of the curved source and also to simulate the stiction and repulsive forces generated in the curved source. Curved source structures with different curvatures are simulated to examine the applicability of the design idea in overcoming the adhesion between source and drain. FEM results demonstrate that secondary structural stiffness created at the source-drain contact can overcome large adhesion stress and allow the separation in a peel-off mechanism after the actuation voltage is removed.
Robust Relative Hand Placement for Bi-Manual Tasks
Authors: Sinha Anirban , Chakraborty Nilanjan
Published: November 2020

In many bi-manual robotic tasks, like peg-in-a-hole assembly, the success of the task execution depends on the error in achieving the desired relative pose between the peg and the hole in a pre-insertion configuration. Random actuation errors in the joint space usually prevents the two arms from reaching their desired task space poses, which in turn results in random error in relative pose between the two hands. This random error varies from trial to trial, and thus depending on the tolerance between the peg and the hole, the outcome of the assembly task may be random (sometimes the task execution succeeds and sometimes it fails). In general, since the relative pose has 6 degrees-of-freedom, there are an infinite number of joint space solutions for the two arms that correspond to the same task space relative pose. However, in the presence of actuation errors, the joint space solutions are not all identical since they map the joint space error sets differently to the task space. Thus, the goal of this paper is to develop a methodical approach to compute a joint space solution such that the maximum task space error is below a (specified) threshold with high probability. Such a solution is called a robust inverse kinematics solution for the bi-manual robot. Our proposed method also allows the robot to self-evaluate whether it can perform a given bi-manual task reliably. We use a square peg-in-a-hole assembly scenario on the dual-arm Baxter robot for numerical simulations that shows the utility of our approach.
Design Elements Inflatable Origami-Based Forceps
Authors: Abulon Dina Joy K. , McCarthy J. Michael
Published: November 2020

Forceps are a multifunctional tool that can solve various grasping needs. An action origami-based forcep design allows a structure to deploy from a flat state to 3D state plus create motion while in a final 3D state. The origami-based design allows the structure to compact. A fabric inflatable structure allows for shape transformation and stiffness adjustment. This paper explores the design of three prototypes and guides the selection of optimal features of inflatable action origami-based forceps.
Metamodel Based Forward and Inverse Design for Passive Vibration Suppression
Authors: Behjat Amir , Oddiraju Manaswin , Attarzadeh Mohammad Ali , Nouh Mostafa , Chowdhury Souma
Published: November 2020

Aperiodic metamaterials represent a class of structural systems that are composed of different building blocks (cells), instead of a self-repeating chain of the same unit cells. Optimizing aperiodic cellular structural systems thus presents high-dimensional design problems, that become intractable to solve using purely high-fidelity structural analysis coupled with optimization. Specialized analytical modeling along with metamodel based optimization can provide a more tractable alternative to designing such aperiodic metamaterials. To explore this concept, this paper presents an initial design automation framework applied to a case study representative of a simple 1D metamaterial system. The case under consideration is a drill string, where vibration suppression is of utmost importance. The drill string comprises a set of nonuniform rings attached to the outer surface of a longitudinal rod. As such, the resultant system can now be perceived as an aperiodic 1D metamaterial with each ring/gap representing a cell. Despite being a 1D system, the simultaneous consideration of multiple degrees of freedom (associated with torsional, axial, and lateral motions) poses significant computational challenges. To deal with these challenges, a transfer matrix method (TMM) is employed to analytically determine the frequency response of the drill string. However, due to the minute scale cost of the TMM method, the optimization remains computationally burdensome. This latter challenge is addressed by training a suite of neural networks on a set of TMM samples, with each network providing the response w.r.t. a specific frequency. Optimization is then performed to minimize mass subject to constraints on the gap between consecutive resonance peaks in one case, and minimizing this gap in the second case. Crucial improvements are accomplished over the initial baselines in both cases. Further novel contributions occur through the development of an inverse modeling approach that can learn optimal inverse designs with minimum mass and a desirable non-resonant frequency range, which partially mimics band gap behavior in perfectly periodic dispersive structures. To this end, we introduce the use of an emerging modeling formalism called in-vertible neural nets. Our study indicates that the inverse model is able to generate constraint satisfying designs with slightly higher mass.
Increasing the Life Span of Foldable Manipulators With Fabric
Authors: Sharifzadeh Mohammad , Jiang Yuhao , Khodambashi Roozbeh , Aukes Daniel
Published: November 2020

This paper evaluates how laminated techniques may be used to replicate the performance of more traditionally manufactured robotic manipulators. This evaluation is conducted by addressing the advantages and challenges of laminated manufacturing techniques, specifcally mechanism durability. In this study, we propose a novel fabric-polyester hinge design with an improved life-span. We additionally provide an overview of the design and construction workfow for a laminated 2-DOF spherical parallel manipulator for use as a camera stabilizer. Using the proposed manipulator as a case study, we demonstrate that mechanisms fabricated with lamination techniques can achieve similar performance to devices made using conventional methods.
Characterization of On-Field Head Impact Exposure in Youth Soccer
Authors: Tomblin Brian T. , Pritchard N. Stewart , Filben Tanner M. , Miller Logan E. , Miles Christopher M. , Urban Jillian E. , Stitzel Joel D.
Published: November 2020

The objective of this research was to characterize head impacts with a validated mouthpiece sensor in competitive youth female soccer players during a single season with a validated mouthpiece sensor. Participants included 14 youth female soccer athletes across 2 club-level teams at different age levels (team 1, ages 12–13 y; team 2, ages 14–15 y). Head impact and time-synchronized video data were collected for 66 practices and games. Video data were reviewed to characterize the type and frequency of contact experienced by each athlete. A total of 2216 contact scenarios were observed; heading the ball (n = 681, 30.7%) was most common. Other observed contact scenarios included collisions, dives, falls, and unintentional ball contact. Team 1 experienced a higher rate of headers per player per hour of play than team 2, while team 2 experienced a higher rate of collisions and dives. A total of 935 video-verified contact scenarios were concurrent with recorded head kinematics. While headers resulted in a maximum linear acceleration of 56.1g, the less frequent head-to-head collisions (n = 6) resulted in a maximum of 113.5g. The results of this study improve the understanding of head impact exposure in youth female soccer players and inform head impact exposure reduction in youth soccer.
The nucleus acts as a ruler tailoring cell responses to spatial constraints
Authors: Lomakin A. J. , Cattin C. J. , Cuvelier D. , Alraies Z. , Molina M. , Nader G. P. F. , Srivastava N. , Sáez P. J. , Garcia-Arcos J. M. , Zhitnyak I. Y. , Bhargava A. , Driscoll M. K. , Welf E. S. , Fiolka R. , Petrie R. J. , De Silva N. S. , González-Granado J. M. , Manel N. , Lennon-Duménil A. M. , Müller D. J. , Piel M.
Published: November 2020

The nucleus makes the rules

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

Science
, this issue p.
eaba2644
, p.
eaba2894
; see also p.
295
Apical stress fibers enable a scaling between cell mechanical response and area in epithelial tissue
Authors: López-Gay Jesús M. , Nunley Hayden , Spencer Meryl , di Pietro Florencia , Guirao Boris , Bosveld Floris , Markova Olga , Gaugue Isabelle , Pelletier Stéphane , Lubensky David K. , Bellaïche Yohanns
Published: November 2020

Fiber tension enables tissue scaling

Tissue development, homeostasis, and repair require cells to sense mechanical forces. Although many molecular actors implicated in cell mechanosensitivity have been extensively studied, the basis by which cells adapt their mechanical responses to their geometry remains poorly defined. López-Gay
et al.
now identify how two fundamental epithelial structures—stress fibers and tricellular junctions—endow
Drosophila
cells with an internal ruler to scale their mechanical response with their area. This work explains how cells of different sizes within an epithelial tissue collectively adapt their mechanical response to control tissue shape and proliferation. Scaling of biological properties with size is a core property of other biological systems.

Science
, this issue p.
eabb2169
Comprehensive quantification of fuel use by the failing and nonfailing human heart
Authors: Murashige Danielle , Jang Cholsoon , Neinast Michael , Edwards Jonathan J. , Cowan Alexis , Hyman Matthew C. , Rabinowitz Joshua D. , Frankel David S. , Arany Zolt
Published: November 2020

Metabolomics, at the heart

With heart failure a leading cause of death, a better understanding of metabolic function in the heart is a welcome advance. Murashige
et al.
measured more than 270 metabolites using liquid chromatography–mass spectrometry in human blood samples taken from an artery entering the heart and from a vein leaving it. Differences thus reflected the metabolic processes at work in the heart. Their results confirmed that hearts voraciously consume fatty acids. Hearts secreted, rather than consumed, amino acids, thus revealing active proteolysis. In patients with heart failure, ketone and lactate consumption increased, as did proteolysis. These findings could lead to strategies for fighting heart disease by altering metabolism.

Science
, this issue p.
364
Atypical Mutation in Neisseria gonorrhoeae 23S rRNA Associated with High-Level Azithromycin Resistance
Authors: Pham Cau D. , Nash Evelyn , Liu Hsi , Schmerer Matthew W. , Sharpe Samera , Woods Grace , Roland Brad , Schlanger Karen , St. Cyr Sancta B. , Carlson Jonathan , Sellers Kevin , Olsen Aaron , Sanon Ruth , Hardin Henrietta , Soge Olusegun O. , Raphael Brian H. , Kersh Ellen N.
Published: November 2020

A2059G mutation in the 23S rRNA gene is the only reported mechanism conferring high-level azithromycin resistance (HL-AZMR) in
Neisseria gonorrhoeae
. Through U.S. gonococcal antimicrobial resistance surveillance projects, we identified four HL-AZMR gonococcal isolates lacking this mutational genotype. Genetic analysis revealed an A2058G mutation of 23S rRNA alleles in all four isolates.
In vitro
selected gonococcal strains with homozygous A2058G recapitulated the HL-AZMR phenotype.
The Ecology and Evolution of Amoeba-Bacterium Interactions
Authors: Shi Yijing , Queller David C. , Tian Yuehui , Zhang Siyi , Yan Qingyun , He Zhili , He Zhenzhen , Wu Chenyuan , Wang Cheng , Shu Longfei
Published: November 2020

Amoebae are protists that have complicated relationships with bacteria, covering the whole spectrum of symbiosis. Amoeba-bacterium interactions contribute to the study of predation, symbiosis, pathogenesis, and human health. Given the complexity of their relationships, it is necessary to understand the ecology and evolution of their interactions. In this paper, we provide an updated review of the current understanding of amoeba-bacterium interactions. We start by discussing the diversity of amoebae and their bacterial partners.
Bacterial-Like Nonribosomal Peptide Synthetases Produce Cyclopeptides in the Zygomycetous Fungus Mortierella alpina
Authors: Wurlitzer Jacob M. , Stanišić Aleksa , Wasmuth Ina , Jungmann Sandra , Fischer Dagmar , Kries Hajo , Gressler Markus
Published: November 2020

Fungal natural compounds are industrially produced, with application in antibiotic treatment, cancer medications, and crop plant protection. Traditionally, higher fungi have been intensively investigated concerning their metabolic potential, but reidentification of already known compounds is frequently observed. Hence, alternative strategies to acquire novel bioactive molecules are required. We present the genus
Mortierella
as representative of the early-diverging fungi as an underestimated resource of natural products.
Mortierella alpina
produces two families of cyclopeptides, designated malpicyclins and malpibaldins, respectively, via two pentamodular nonribosomal peptide synthetases (NRPSs). These enzymes are much more closely related to bacterial than to other fungal NRPSs, suggesting a bacterial origin of these NRPS genes in
Mortierella
. Both enzymes were biochemically characterized and are involved in as-yet-unknown biosynthetic pathways of natural products in basal fungi. Hence, this report establishes early-diverging fungi as prolific natural compound producers and sheds light on the origin of their biosynthetic capacity.
Sediment Metagenomes as Time Capsules of Lake Microbiomes
Authors: Garner Rebecca E. , Gregory-Eaves Irene , Walsh David A.
Published: November 2020

Lakes are critical freshwater resources under mounting pressure from climate change and other anthropogenic stressors. The reconstruction of ecological time series from sediment archives with paleolimnological techniques has been shown to be an effective means of understanding how humans are modifying lake ecosystems over extended timescales. In this study, we combined shotgun DNA sequencing with a novel comparative analysis of surface water and sediment metagenomes to expose the diversity of microorganisms preserved in lake sediments. The detection of DNA from a broad diversity of preserved microbes serves to more fully reconstruct historical microbiomes and describe preimpact lake conditions.
Enhanced Enterovirus D68 Replication in Neuroblastoma Cells Is Associated with a Cell Culture-Adaptive Amino Acid Substitution in VP1
Authors: Sooksawasdi Na Ayudhya Syriam , Meijer Adam , Bauer Lisa , Oude Munnink Bas , Embregts Carmen , Leijten Lonneke , Siegers Jurre Y. , Laksono Brigitta M. , van Kuppeveld Frank , Kuiken Thijs , GeurtsvanKessel Corine , van Riel Debby
Published: November 2020

Enterovirus D68 (EV-D68) causes mild to severe respiratory disease and is associated with acute flaccid myelitis since 2014. Currently, the understanding of the ability of EV-D68 to replicate in the central nervous system (CNS), and whether it is associated with a specific clade of EV-D68 viruses or specific viral factors, is lacking. Comparing different EV-D68 clades did not reveal clade-specific phenotypic characteristics. However, we did show that viruses which acquired a cell culture-adapted amino acid substitution in VP1 (E271K) recognized heparan sulfate as an additional receptor. Recognition of heparan sulfate resulted in an increase in attachment, infection, and replication in neuroblastoma cells compared with viruses without this specific amino acid substitution. The ability of EV-D68 viruses to acquire cell culture-adaptive substitutions which have a large effect in experimental settings emphasizes the need to sequence virus stocks.
In Situ
Imaging of Candida albicans Hyphal Growth via Atomic Force Microscopy
Authors: Çolak Arzu , Ikeh Mélanie A. C. , Nobile Clarissa J. , Baykara Mehmet Z.
Published: November 2020

Candida albicans
is one of the most common pathogens of humans. One important virulence factor of
C. albicans
is its ability to form elongated hyphae that can invade host tissues and cause disseminated infections. Here, we show the effect of different physiologically relevant temperatures and common antifungal drugs on the growth and mechanical properties of
C. albicans
hyphae using atomic force microscopy. We demonstrate that minor temperature fluctuations within the normal range can have profound effects on hyphal cell growth and that different antifungal drugs impact hyphal cell stiffness and adhesion in different ways.
Struggle To Survive: the Choir of Target Alteration, Hydrolyzing Enzyme, and Plasmid Expression as a Novel Aztreonam-Avibactam Resistance Mechanism
Authors: Ma Ke , Feng Yu , McNally Alan , Zong Zhiyong
Published: November 2020

Carbapenemase-producing
Enterobacterales
(CPE) is a serious global challenge with limited therapeutic options. Aztreonam-avibactam is a promising antimicrobial combination with activity against CPE producing serine-based carbapenemases and metallo-β-lactamases and has the potential to be a major option for combatting CPE. Aztreonam-avibactam resistance has been found, but resistance mechanisms remain largely unknown. Understanding resistance mechanisms is essential for optimizing treatment and developing alternative therapies. Here, we found that either penicillin-binding protein 3 modification or the elevated expression of cephalosporinase CMY-42 due to increased plasmid copy numbers does not confer resistance to aztreonam-avibactam, but their combination does. We demonstrate that increased plasmid copy numbers result from mutations in antisense RNA-encoding
inc
of the IncIγ replicon. The findings reveal that antimicrobial resistance may be due to concerted combinatorial effects of target alteration, hydrolyzing enzyme, and plasmid expression and also highlight that resistance to any antimicrobial combination will inevitably emerge.
Human Gene Functional Network-Informed Prediction of HIV-1 Host Dependency Factors
Authors: Fu Chen , Yang Shiping , Yang Xiaodi , Lian Xianyi , Huang Yan , Dong Xiaobao , Zhang Ziding
Published: November 2020

Identification of HIV-1 HDFs remains a crucial step to understand the complicated relationships between human and HIV-1. To complement the experimental identification of HDFs, we have implemented an existing network-based gene discovery strategy to predict HDFs from the human genome. The core idea of the proposed method is that the rich information deposited in host gene functional networks can be effectively utilized to infer the potential HDFs. We hope the proposed prediction method could further guide hypothesis-driven experimental efforts to interrogate human–HIV-1 relationships and provide new hints for the development of antiviral drugs to combat HIV-1 infection.
Supplemental Material: Can we relate the surface expression of dike-induced normal faults to subsurface dike geometry?
Authors: Magee Craig , Jackson Christopher
Published: November 2020

Uninterpreted seismic reflection images, a video of the seismic data, tables and figure describing the resolution and depth-conversion of the data, text and a figure discussing the methodology, and a comprehensive table of measurements and calculation.
Supplemental Material: Characterizing strain between rigid crustal blocks in the southern Cascadia forearc: Quaternary faults and folds of the northern Sacramento Valley, California
Authors: Angster Stephen , al. et
Published: November 2020

Supplemental figures and information about datasets and methods used for mapping and terrace profiling, and OSL dating methods, results, and discussion.
Injury characteristics in male youth athletics: a five-season prospective study in a full-time sports academy
Authors: Martínez-Silván Daniel , Wik Eirik Halvorsen , Alonso Juan Manuel , Jeanguyot Evan , Salcinovic Benjamin , Johnson Amanda , Cardinale Marco
Published: November 2020

Objectives

To describe the injury characteristics of male youth athletes exposed to year-round athletics programmes.

Methods

Injury surveillance data were prospectively collected by medical staff in a cohort of youth athletics athletes participating in a full-time sports academy from 2014–2015 to 2018–2019. Time-loss injuries (>1 day) were recorded following consensus procedures for athletics. Athletes were clustered into five event groups (sprints, jumps, endurance, throws and non-specialised) and the number of completed training and competition sessions (athletics exposures (AE)) were calculated for each athlete per completed season (one athlete season). Injury characteristics were reported overall and by event groups as injury incidence (injuries per 1000 AE) and injury burden (days lost per 1000 AE).

Results

One-hundred and seventy-eight boys (14.9±1.8 years old) completed 391 athlete seasons, sustaining 290 injuries. The overall incidence was 4.0 injuries per 1000 AE and the overall burden was 79.1 days lost per 1000 AE. The thigh was the most common injury location (19%). Muscle strains (0.7 injuries per 1000 AE) and bone stress injuries (0.5 injuries per 1000 AE) presented the highest incidence and stress fractures the highest burden (17.6 days lost per 1000 AE). The most burdensome injury types by event group were: bone stress injuries for endurance, hamstring strains for sprints, stress fractures for jumps, lesion of meniscus/cartilage for throws and growth plate injuries for non-specialised athletes.

Conclusion

Acute muscle strains, stress fractures and bone stress injuries were identified as the main injury concerns in this cohort of young male athletics athletes. The injury characteristics differed between event groups.
Are web-based personally tailored physical activity videos more effective than personally tailored text-based interventions? Results from the three-arm randomised controlled TaylorActive trial
Authors: Vandelanotte Corneel , Short Camille E , Plotnikoff Ronald C , Rebar Amanda , Alley Stephanie , Schoeppe Stephanie , Canoy Doreen F , Hooker Cindy , Power Deborah , Oldmeadow Christopher , Leigh Lucy , To Quyen , Mummery W Kerry , Duncan Mitch J
Published: November 2020

Objectives

Some online, personally tailored, text-based physical activity interventions have proven effective. However, people tend to ‘skim’ and ‘scan’ web-based text rather than thoroughly read their contents. In contrast, online videos are more engaging and popular. We examined whether web-based personally tailored physical activity videos were more effective in promoting physical activity than personally tailored text and generic information.

Methods

501 adults were randomised into a video-tailored intervention, text-tailored intervention or control. Over a 3-month period, intervention groups received access to eight sessions of web-based personally tailored physical activity advice. Only the delivery method differed between intervention groups: tailored video versus tailored text. The primary outcome was 7-day ActiGraph-GT3X+ measured moderate-to-vigorous physical activity (MVPA) assessed at 0, 3 and 9 months. Secondary outcomes included self-reported MVPA and website engagement. Differences were examined using generalised linear mixed models with intention-to-treat and multiple imputation.

Results

Accelerometer-assessed MVPA increased 23% in the control (1.23 (1.06, 1.43)), 12% in the text-tailored (1.12 (0.95, 1.32)) and 28% in the video-tailored (1.28 (1.06, 1.53)) groups at the 3-month follow-up only, though there were no significant between-group differences. Both text-tailored (1.77 (1.37, 2.28]) and video-tailored (1.37 (1.04, 1.79)) groups significantly increased self-reported MVPA more than the control group at 3 months only, but there were no differences between video-tailored and text-tailored groups. The video-tailored group spent significantly more time on the website compared with text-tailored participants (90 vs 77 min, p=0.02).

Conclusions

The personally tailored videos were not more effective than personally tailored text in increasing MVPA. The findings from this study conflict with pilot study outcomes and previous literature. Process evaluation and mediation analyses will provide further insights.

Trial registration number

ACTRN12615000057583
‘Supportive and Palliative Care Indicators Tool (SPICT) improves renal nurses’ confidence in recognising patients approaching end of life’
Authors: Lunardi Laura , Hill Kathy , Crail Susan , Esterman Adrian , Le Leu Richard , Drummond Christine
Published: November 2020

Background

Identification of people with deteriorating health is essential for quality patient-centred care and optimal management. The Supportive and Palliative Care Indicators Tool (SPICT) is a guide to identifying people with deteriorating health for care planning without incorporating a prognostic time frame.

Objectives

To improve renal nursing staff confidence in identifying patients approaching end-of-life and advocate for appropriate multidisciplinary care planning.

Design

This pilot feasibility prospective cohort study conducted in the renal ward of a major metropolitan health service during 2019 included a preintervention/postintervention survey questionnaire. A programme of education was implemented training staff to recognise end-of-life and facilitate appropriate care planning.

Results

Several domains in the postintervention survey demonstrated a statistically significant improvement in renal nurses’ perception of confidence in their ability to recognise end of life. Of the 210 patients admitted during the study period, 16% were recognised as SPICT positive triggering renal physicians to initiate discussions about end-of-life care planning with patients and their families and to document a plan. Six months poststudy, 72% of those patients recognised as SPICT positive had died with a documented plan of care in place.

Conclusion

The use of SPICT for hospital admissions and the application of education in topics related to end-of-life care resulted in a significant improvement in nurses’ confidence in recognising deteriorating and frail patients approaching their end of life. The use of this tool also increased the number of deteriorating patients approaching end of life with goals of care documented.
Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge?
Authors: McCartney Gerry , Leyland Alastair , Walsh David , Ruth Dundas
Published: November 2020

Background

The mortality impact of COVID-19 has thus far been described in terms of crude death counts. We aimed to calibrate the scale of the modelled mortality impact of COVID-19 using age-standardised mortality rates and life expectancy contribution against other, socially determined, causes of death in order to inform governments and the public.

Methods

We compared mortality attributable to suicide, drug poisoning and socioeconomic inequality with estimates of mortality from an infectious disease model of COVID-19. We calculated age-standardised mortality rates and life expectancy contributions for the UK and its constituent nations.

Results

Mortality from a fully unmitigated COVID-19 pandemic is estimated to be responsible for a negative life expectancy contribution of −5.96 years for the UK. This is reduced to −0.33 years in the fully mitigated scenario. The equivalent annual life expectancy contributions of suicide, drug poisoning and socioeconomic inequality-related deaths are −0.25, −0.20 and −3.51 years, respectively. The negative impact of fully unmitigated COVID-19 on life expectancy is therefore equivalent to 24 years of suicide deaths, 30 years of drug poisoning deaths and 1.7 years of inequality-related deaths for the UK.

Conclusion

Fully mitigating COVID-19 is estimated to prevent a loss of 5.63 years of life expectancy for the UK. Over 10 years, there is a greater negative life expectancy contribution from inequality than around six unmitigated COVID-19 pandemics. To achieve long-term population health improvements it is therefore important to take this opportunity to introduce post-pandemic economic policies to ‘build back better’.