bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms and management of gastrointestinal symptoms in postural orthostatic tachycardia syndrome
Authors: Tu Yixi , Abell Thomas L. , Raj Satish R. , Mar Philip L.
Published: November 2020

Postural orthostatic tachycardia syndrome (POTS) is a disorder of orthostatic intolerance associated with many GI manifestations that can be broadly classified into two different categories: those present all the time (non‐positional) and those that occur with orthostatic position change. There are also many conditions that can co‐exist with POTS such as mast cell activation syndrome and the hypermobile form of Ehlers‐Danlos syndrome (hEDS) that are also oftentimes associated with GI symptoms. In the current issue of Neurogastroenterology and Motility, Tai et al. explored the relationship between functional GI disorders among hEDS patients with and without concomitant POTS and showed that the hEDS‐POTS cohort was more likely to have more than one GI organ involved compared to the cohort with hEDS alone, and certain GI symptoms were also more common in the hEDS‐POTS cohort. In this review article, we will briefly review the literature surrounding putative mechanisms responsible for GI symptoms in POTS with an emphasis on the contributory role of concomitant hEDS and then discuss management strategies for GI symptoms in POTS.
Perioperative anaphylaxis in children: A report from the Wake‐Up Safe collaborative
Authors: Wakimoto Mayuko , Miller Rebecca , Kim Stephani S. , Uffman Joshua C. , NafiuS Olubukola O. , Tobias Joseph D. , Beltran Ralph J.
Published: November 2020

Background

Anaphylactic reactions to antigens in the perioperative environment are uncommon, but they have a potential to lead to serious morbidity and/or mortality. The incidence of anaphylactic reactions is 1:37 000 pediatric anesthetics, and substantially less than the 1:10 000 to 1:20 000 incidence in the adult population. Neuromuscular blocking agents, latex, and antibiotics are the most frequently cited triggers. To date, there is no comprehensive report on perioperative anaphylactic reactions in children in the United States. Using the Wake‐up Safe database, we examined the incidence and consequences of reported perioperative anaphylaxis events.

Methods

We reviewed the Wake‐up Safe database from 2010 to 2017 and identified all reported instances of anaphylaxis. The triggering agent, timing, and location of the registered event, severity of patient harm, and preventability were identified. Narrative review of free‐text comments entered by reporting centers was performed to determine presenting symptoms, and interventions required. Type of case was identified from procedure codes provided in mandatory fields.

Results

Among 2 261 749 cases reported to the Wake‐up Safe database during the study period, perioperative anaphylactic reactions occurred in 1:36 479 (0.003%). Antibiotics, neuromuscular blocking agents, and opioid analgesics were the main triggers. Forty‐nine cases (79%) occurred in the operating room, and 13 cases (21%) occurred in off‐site locations. Seven (11%) patients required cardiopulmonary resuscitation following the onset of symptoms. Thirty‐five (57%) patients were treated with epinephrine or epinephrine plus other medications, whereas 5% were managed only with phenylephrine. Most cases (97%) required escalation of care after the event. Regarding case preventability, 91% of cases were marked as either “likely could not have been prevented” or “almost certainly could not have been prevented.”

Conclusion

The estimated incidence of anaphylaxis and inciting agents among the pediatric population in this study were consistent with the most recent published studies outside of the United States; however, new findings included need for cardiopulmonary resuscitation in 11% of cases, and estimated fatality of 1.6%. The management of perioperative anaphylaxis could be improved for some cases as epinephrine was not administered, or its administration was delayed. Fewer than half of reported cases had additional investigation to formally identify the responsible agent.
Supporting Operations with Financial Hedging: Cash Hedging Vs. Cost Hedging in an Automotive Industry
Authors: Kouvelis Panos , Turcic Danko
Published: November 2020

Financial hedging of raw material prices and exchange rates has become an integral part of many manufacturers' operating practices. Previous empirical research suggests that a desire to avoid financial distress and the affiliated curtailment in operations is one of the strongest hedge motivations. Taking the hedging motivation as given, we examine the effectiveness of two data‐driven hedging policies at mitigating financial distress in the car manufacturing industry. The first policy is the “cost hedging” policy, under which the carmaker hedges raw material and production input purchases. This policy appears to be in wide use in practice. The car manufacturer needs to trade in aluminum, steel, zinc, and plastic to achieve the cost hedge. The second policy is a “cash hedging” policy under which the firm hedges its net cash flow. To determine a cash hedging policy, the firm solves a stochastic program that minimizes its hedge cost subject to cash flow constraints. The program solution suggests that the firm needs to trade S&P500, aluminum, and zinc to implement the hedge. Our results reveal that the most critical drivers of hedging decisions appear to be demand shifts, especially demand elasticity shifts. The least important drivers are car design updates, which change the car's raw material requirements. This finding sheds light on why cost hedging, which focuses on hedging raw materials, is less effective than the cash hedging technique, which hedges both costs and demand.
A Tale of Two Food Chains: The Duality of Practices on Well‐being
Authors: Roth Aleda , Zheng Yanchong
Published: November 2020

In this paper, we honor Stanford University Professor Hau Lee, who is a great inspiration and thought leader in the supply chain and operations management (SC&OM) field. Our discussion centers around one of the most challenging SC&OM problems—food production, distribution, and consumption from dirt to table. We advocate and link our notions of emergent regenerative, organic food value chains (ROFVC) with quadruple‐aim performance (QAP) that connects financial outcomes with ecological, human, and socioeconomic well‐being. To do so, we first overview the systemic problems underlying the conventional food supply chains (CFSC) that render them unsustainable in the long run. In contrast, we introduce salient distinctions between CFSC and the new paradigm of ROFVC that uphold QAP. We believe the ideas generated in this paper can move the food systems’ SC&OM design, implementation, and performance measurement from an efficiency‐oriented industrial paradigm of large‐scale, factory farming toward a more encompassing view of eco‐responsible practices. In CFSC, the many hidden costs are cumulative and have broad deleterious consequences; however, in ROFVC, pollution is shunned and “taxed,” and sustainability, as a public good, is rewarded by sequestering greenhouse gas (GHG) emissions and maintaining biodiversity, living soil, as well as clean air and water. We conclude with research, teaching, and policy agendas. We believe that the underlying principles here cut across sectors by fostering the introduction of regenerative business models that take a system's view in capturing QAP in their value chain strategy and execution.
Supply Chains with a Conscience
Authors: Lee Hau L.
Published: November 2020

As supply chains become more and more globalized, even in times of disruptions and trade frictions, and that consumers are increasingly more demanding on the environmental and social responsibility performances of the supply chains that supply products they are buying, research in supply chain management should also contribute to make an impact under such trends. I call this “supply chains with a conscience,” where supply chains need to continuously strive to minimize the harms and negative impacts to the environment and people, while maximize the values and well‐beings of society at large, especially for those in emerging and developing economies. I want to share some frameworks of perspectives on this subject, some illustrative developments, and an example of a personal journey.
Chinese characters are read using not only visual but also writing motor information
Authors: Yin Yulong , Zhang Qingfang
Published: November 2020

It has been suggested that mature reading systems consist of both a visual analysis decoding system and a motor gesture decoding system that facilitates reading by processing writing motor information. However, there is still uncertainty about the mechanisms and effectiveness of the latter system when reading Chinese characters. This study therefore aimed to provide empirical neural evidence for this phenomenon using a writing video as prompt in a delayed sequential same/different judgment task. We investigated whether and how the orthographic processing of target characters was modulated by the writing direction of the prompt (forward vs. backward) and the character repetition (repeat vs. nonrepeat) between the prompt and target characters. The results indicated that (a) the N170 component was more negative under the forward condition than under the backward condition; and (b) both writing direction and character repetition modulated the centro‐parietal N200 component. These writing‐direction effects were specific to Chinese characters––they did not apply to Korean characters, which are visually similar to Chinese characters but unfamiliar to the participants. These results suggest that the experience of learning Chinese might establish a motor gesture decoding system for reading, which begins to perform general orthographic representation at an early stage and works together with the visual analysis decoding system to achieve deep orthographic processing.
Load‐dependent modulation of alpha oscillations during working memory encoding and retention in young and older adults
Authors: Sghirripa Sabrina , Graetz Lynton , Merkin Ashley , Rogasch Nigel C. , Semmler John G. , Goldsworthy Mitchell R.
Published: November 2020

Working memory (WM) is vulnerable to age‐related decline, particularly under high loads. Visual alpha oscillations contribute to WM performance in younger adults, and although alpha decreases in power and frequency with age, it is unclear if alpha activity supports WM in older adults. We recorded electroencephalography (EEG) while 24 younger (aged 18–35 years) and 30 older (aged 50–86) adults performed a modified Sternberg task with varying load conditions. Older adults demonstrated slower reaction times at all loads, but there were no significant age differences in WM capacity. Regardless of age, alpha power decreased and alpha frequency increased with load during encoding, and the magnitude of alpha suppression during retention was larger at higher loads. While alpha power during retention was lower than fixation in older, but not younger adults, the relative change from fixation was not significantly different between age groups. Individual differences in alpha power did not predict performance for either age groups or at any WM loads. We demonstrate that alpha power and frequency are modulated in a similar task‐ and load‐dependent manner during WM in both older and younger adults when WM performance is comparable across age groups.

Impact statement

Aging is associated with a marked decrease in the power and frequency of alpha oscillations. Here, we demonstrate that when verbal working memory performance is matched across age groups, alpha power and frequency are modulated in a similar task‐ and load‐dependent manner in both young and older adults.
Particle‐scale characterization of volcaniclastic dust sources within Iceland
Authors: Richards‐Thomas Tamar , McKenna‐Neuman Cheryl , Power Ian M.
Published: November 2020

Volcaniclastic dust particles are characterized by unique physical properties, which are speculated to influence their rates of entrainment, emission and deposition within the atmospheric boundary layer. Few detailed particle‐scale measurements exist, so that natural particles often are idealized as solid glass spheres in the parameterization of dust dispersion models. This study shows that volcaniclastic dust particles from Iceland contain substantial quantities of amorphous glass, large internal voids and copious dustcoats comprised of nano‐scale flakes. Their high porosity, found to increase with particle diameter, generates particle densities that can be substantially lower than expected for a solid sphere. An abundance of volcanic glass also seems to increase particle porosity and roughness, and thereby strongly correlates with the Brunauer Emmett Teller surface area. An analysis based on Stokes' law further suggests that Icelandic dust with a standardized geometric diameter (10 μm or PM10), but with varying density, shape and origin, may have settling velocities in still air that are up to 20% lower than for a reference glass sphere. As a first approximation, neglecting complex particle interactions and wind speed, which also affect the deposition rate in the atmosphere, their low density and large surface area could increase the expected residence time by a factor of five. Model parameterization should be refined to incorporate these particle‐scale factors in order to improve on the estimation of volcaniclastic dust dispersion.
Women’s Inclusion in the Malian Peace Negotiations: Norms and Practices
Authors: Lorentzen Jenny
Published: November 2020

This article studies the implementation of the global norm of women’s inclusion in the Malian peace negotiations. It constructs a theoretical framework for analyzing practices of resistance, which object to the validity of the norm, and practices of refinement, which engage with the application of the norm. Based on interviews with women who attended the Malian peace negotiations it finds that women face widespread practices of resistance when they demand to be included. However, when pressure is applied concessions often follow, indicating growing acceptance of the norm. Actors also engaged in practices of refinement, observed through a number of disagreements over how, when and which women should be included. The article contributes important insights on the relationship between norms and practices by demonstrating not only that norms influence practice, but how practices of resistance and refinement shape the meanings and life cycles of norms.
Evaluation of ultrahigh‐resolution optical coherence tomography for basal cell carcinoma, seborrheic keratosis, and nevus
Authors: Chen Shufen , Xie Fang , Hao Tian , Xie Jun , Wang Xianghong , Chen Si , Liu Linbo , Li Chengxin
Published: November 2020

Background

Basal cell carcinoma, seborrheic keratosis, and nevus are common skin conditions. Though most of the skin diseases can be distinguished from each other by physician's naked eyes, the diagnostic accuracy is not 100%. The accurate diagnosis and assessment of three diseases make a big difference on the clinical management. Nowadays, biopsy is still the gold standard for diagnosis even it is invasive, time‐consuming, and painful. Ultrahigh‐resolution optical coherence tomography is an emerging technology that can produce in situ, cellular‐resolution, real‐time, continuous, 3D images in a noninvasive way.

Materials and Methods

In our study, four basal cell carcinoma patients, five seborrheic keratosis patients, and 10 nevus patients who were diagnosed by histology were studied by ultrahigh‐resolution optical coherence tomography after visual examination by experienced dermatologists. Cellular contrast was utilized to clearly identify the features of the three skin diseases.

Results

The features including such as hyperkeratosis (horn pseudocysts), papillomatosis, intraepidermal nests, elongated, and expanded rete ridge can be visualized in seborrheic keratosis. Tumor nodular, mucin surrounding with tumor (retraction space in histopathology), tumor subtype, and necrosis were featured in basal cell carcinoma. Pigment was characterized in epidermis and dermis. The comparison of ultrahigh‐resolution optical coherence tomography images reveals a strong correlation with histological images.

Conclusion

Ultrahigh‐resolution optical coherence tomography can complement existing diagnostic techniques for investigating seborrheic keratosis, basal cell carcinoma and nevus, and show enormous potential in vivo applications for the three skin diseases in the future.
Pre‐contrast CT attenuation of the thyroid gland is lower in brachycephalic dogs versus non‐brachycephalic dogs
Authors: Amorós Olga , Espada Yvonne , Vila Anna , Jiménez Alejandro , Novellas Rosa
Published: November 2020

Computed tomography has been used in human medicine to evaluate the thyroid gland functional status by means of Hounsfield units (HU). Studies describing attenuation value abnormalities, other than those in thyroid neoplasia, lack in veterinary medicine. The authors have observed a subjective reduction in thyroid attenuation in some patients undergoing CT for reasons other than thyroid disease. This finding has been identified more frequently in brachycephalic breeds compared to non‐brachycephalic breeds. In order to determine the thyroid gland attenuation variability on CT, a retrospective and prospective, analytical, cross‐sectional study was performed. The thyroid attenuation values of 65 client‐owned dogs were assessed using a 16‐slice helical CT scanner. Differences in attenuation between brachycephalic and non‐brachycephalic dogs were estimated by Welch'st‐test. Serum TT4 and TSH levels were available in 26 patients. Statistically significant differences were observed in the pre‐contrast attenuation value ranges between brachycephalic and non‐brachycephalic dogs (P = .04). The pre‐contrast attenuation value range for the brachycephalic group was 69.1‐108 HU while being 75.8‐121 HU for the non‐brachycephalic group. No significant correlation was found between thyroid attenuation and serum thyroid hormone levels in our population (P > .6). All patients with hypoattenuating thyroid were brachycephalic and reported euthyroid. In conclusion, brachycephalic dogs seem to have a pre‐contrast attenuation thyroid gland range lower than non‐brachycephalic dogs. The present study contributes to the veterinary literature by providing a new thyroid attenuation value range for brachycephalic breeds. Additionally, hypoattenuating thyroid glands may be found in dogs with normal TT4 and TSH values.
NMDA receptors in axons: there's no coincidence
Authors: Wong Hovy Ho‐Wai , Rannio Sabine , Jones Victoria , Thomazeau Aurore , Sjöström P. Jesper
Published: November 2020

In the textbook view, N‐methyl‐d‐aspartate (NMDA) receptors are postsynaptically located detectors of coincident activity in Hebbian learning. However, controversial presynaptically located NMDA receptors (preNMDARs) have for decades been repeatedly reported in the literature. These preNMDARs have typically been implicated in the regulation of short‐term and long‐term plasticity, but precisely how they signal and what their functional roles are have been poorly understood. The functional roles of preNMDARs across several brain regions and different forms of plasticity can differ vastly, with recent discoveries showing key involvement of unusual subunit composition. Increasing evidence shows preNMDAR can signal through both ionotropic action by fluxing calcium and in metabotropic mode even in the presence of magnesium blockade. We argue that these unusual properties may explain why controversy has surrounded this receptor type. In addition, the expression of preNMDARs at some synapse types but not others can underlie synapse‐type‐specific plasticity. Last but not least, preNMDARs are emerging therapeutic targets in disease states such as neuropathic pain. We conclude that axonally located preNMDARs are required for specific purposes and do not end up there by accident.

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Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions
Authors: Pal Pinaki , Kalvakala Krishna , Wu Yunchao , McNenly Matthew , Lapointe Simon , Whitesides Russell , Lu Tianfeng , Aggarwal Suresh K. , Som Sibendu
Published: November 2020

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.
Design of Control Systems Using Active Uncertainty Reduction-Based Reinforcement Learning
Authors: Wang Zequn , Patwardhan Narendra
Published: November 2020

Model-free reinforcement learning based methods such as Proximal Policy Optimization, or Q-learning typically require thousands of interactions with the environment to approximate the optimal controller which may not always be feasible in robotics due to safety and time consumption. Model-based methods such as PILCO or BlackDrops, while data-efficient, provide solutions with limited robustness and complexity. To address this tradeoff, we introduce active uncertainty reduction-based virtual environments, which are formed through limited trials conducted in the original environment. We provide an efficient method for uncertainty management, which is used as a metric for self-improvement by identification of the points with maximum expected improvement through adaptive sampling. Capturing the uncertainty also allows for better mimicking of the reward responses of the original system. Our approach enables the use of complex policy structures and reward functions through a unique combination of model-based and model-free methods, while still retaining the data efficiency. We demonstrate the validity of our method on several classic reinforcement learning problems in OpenAI gym. We prove that our approach offers a better modeling capacity for complex system dynamics as compared to established methods.
Spiral Tool Path Generation for CNC Machining Using Cloud of Points
Authors: Dhanda Mandeep , Kukreja Aman , Pande S. S.
Published: November 2020

This paper presents a new method to generate an adaptive spiral tool path for 3-axis CNC machining of the complex freeform surface directly from its representation in the form of the point cloud. The algorithm first constructs the uniform 2D circular mesh-grid to compute the Z (CL) points by applying the tool inverse offset method (IOM). Adaptive grid refinement is carried out iteratively until the surface form errors converge below the prescribed tolerance limits in both circumferential (forward) and radial (step) directions. Adaptive CL points are further refined to minimize the no. of tool lifts and generate an optimum sequence of machining regions. The optimized CL points are post-processed to generate the final CNC part programs in the ISO format. The part programs generated by our algorithm were extensively tested for various case studies using the commercial CNC simulator. The results were compared with those from the commercial CAM software. Our system was found to generate more efficient tool paths in terms of enhanced productivity, part quality, and reduced memory requirement.
Hinges and Curved Lamina Emergent Torsional Joints in Cylindrical Developable Mechanisms
Authors: Seymour Kendall , Bilancia Pietro , Magleby Spencer , Howell Larry
Published: November 2020

Cylindrical developable mechanisms are devices that conform to and emerge from a cylindrical surface. These mechanisms can be formed or cut from the cylinder wall itself. This paper presents a study on adapting traditional hinge options to achieve revolute motion in these mechanisms. A brief overview of options is given, including classical pin hinges, small-length flexural pivots, initially curved beams, and an adaptation of the membrane thickness-accommodation technique. Curved Lamina Emergent Torsional (LET) joints are then evaluated in detail, and a thin-walled modeling assumption is checked analytically and empirically. A small-scale cylindrical developable mechanism is then evaluated with Nitinol curved LET joints.
Controller Design and Road-Friendly Suspension Optimization: Half Vehicle Model
Authors: Prasad Vikas , Seshu P. , Pawaskar Dnyanesh N.
Published: November 2020

In this paper, the design of the suspension system for Heavy Goods Vehicles (HGV) is proposed, which deals with two performance criteria simultaneously. A semi-tractor trailer is used in present work and modeled with half vehicle model. Four types of linear, as well as non-linear, passive and semi-active suspension systems, are presented in this work. The control law is proposed for the semi-active suspension system using a PID controller to remove the need for passive damper along with active damper. Two objective optimization is performed using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Road Damage (RD) is taken as the first objective along with Goods Damage (GD) as the second objective. All problems are minimization problems. It is concluded based on Pareto front comparison of different suspension systems that the semi-active suspension system with the proposed control law performs well for HGV.
Injury Prevention by Design: Measuring Greenhouse Worker Social Sustainability for Redesigned Equipment
Authors: Klesmith Andrew , Clarke-Sather Abigail R. , Schofield Katherine
Published: November 2020

The greenhouse industry is a multibillion-dollar sector of U.S. agricultural production. Greenhouse workers often experience hazardous working conditions placing them at risk for injury. These injuries include but are not limited to mechanized operations causing machine and tool related injuries, on-site shipping and loading practices placing excessive strain on a worker’s body, working from height leading to slips and falls, and a strenuous indoor working environment exceeding workers’ physical capabilities. This project focused on identifying greenhouse worker injury trends using workers’ compensation data from the Midwest region and observing and interviewing workers at one specific greenhouse company host site. Physical exertion, lifting and handling, and falls were all high value workers’ compensation problems for Midwestern regional greenhouses. A new piece of equipment and process was designed to prevent worker injury identified within the host site. The baseline risk from the original equipment was compared to the new equipment using a newly proposed indicator of social sustainability based on a validated safety professional tool, the risk assessment matrix (RAM), was utilized. The RAM found a reduction in risk between the original and new equipment. The new equipment design and process exhibited improvement in six out of the eleven hazards identified in the RAM. These improvements addressed lifting and handling concerns. Combining workers’ compensation data analysis, on-site observation, and worker interviews together was an effective method to rapidly deploy and design safer and thus more socially sustainable equipment for greenhouse workers.
Identifying High-Potential Work Areas in Engineering for Global Development: Linking Industry Sectors to the Human Development Index
Authors: Smith Daniel O. , Mattson Christopher A. , Dahlin Eric C.
Published: November 2020

Those working in Engineering for Global Development seek to improve the conditions in under-served regions. A common metric for understanding the development state of a given country is the Human Development Index (HDI), which focuses on three dimensions: health, education, and income. An engineer’s expertise does not always align with any of those dimensions directly, while they still hope to perform impactful work for human development. To discover other areas of expertise that are highly associated with the HDI, correlations and variable selection were performed between all World Development Indicators and the HDI. The resultant associations are presented according to industry sector for a straightforward connection to engineering expertise, such that they can be used during opportunity development where associated areas of expertise act as surrogates for focusing on the HDI dimensions themselves. The data analysis shows that work related to “Trade, Transportation, and Utilities”, such as merchandise exports and imports and electricity distribution, and “Manufacturing”, especially electronics manufacturing and employment in manufacturing are insightful associations with improvements in the HDI in developing countries. Also, because the associations were discovered at country-level, they geographically direct where particular areas of expertise have been historically associated with improving HDI.
Remote Data Collection Devices for Social Impact Indicators of Products in Developing Countries
Authors: Stringham Bryan J. , Mattson Christopher A.
Published: November 2020

Social impact indicators provide one effective way to measure the social impacts of products in developing countries and ensure that engineering design is producing positive impacts on individuals. Internet-connected, remote data collection devices can provide an effective way to use sensors to collect data required to calculate social impact indicators. These devices often allow data to be collected remotely, continuously, and less expensively than other methods that require direct interaction with users. However, many key decisions and questions must be considered during the development and deployment of such devices to avoid risk of failure. To provide a systematic way for researchers interested in employing sensor devices to identify and answer critical development questions, the stages of device development can be decomposed into Data Identification, Device Design, and Device Deployment. This paper discusses the key decisions within each stage of development along with critical questions, common options, and considerations that should be addressed during each stage of device development, thus increasing the likelihood of success. A sensor development canvas outlining the key decisions is also provided as a design tool to easily identify deficiencies in the device during development. Considering these critical questions while developing and deploying data collection devices can help researchers successfully collect social impact indicator data to ensure engineered products are producing desired positive impacts on individuals.
Numerical Procedure for Non-Hertzian Wheel-Rail Contact Model Integrated in Quasi-Steady Railway Vehicle Motion Solver
Authors: Tanaka Takayuki , Sugiyama Hiroyuki
Published: November 2020

Although the Hertzian contact theory is widely utilized in railway vehicle simulations with new wheel and rail profiles, the Hertzian contact assumptions would lead to inaccurate contact prediction for severely worn wheel and rail profiles due to their geometric conformity, causing non-elliptical contact shapes as well as pressure distribution. For this reason, various non-Hertzian contact models have been studied for use in vehicle dynamics simulations. Among others, a method proposed by Piotrowski and Kik has gained acceptance in predicting non-elliptical wheel-rail contact for vehicle dynamics simulations. Despite the elegant formulation and its accuracy, detailed online geometric calculation for non-elliptical contact shape is required for all the contact patches at every iteration, along with iterative evaluation of the force-deflection relationship. It leads to computation burdens for use in long-distance vehicle simulations. Therefore, in this study, an off-line based numerical procedure for non-Hertzian contact model is developed and integrated in the quasi-steady railway vehicle motion solver.
Investigating the Relationship Between Digital Prototyping Tool Use and Student Designers’ Perceptions of Design Processes
Authors: Berlin Andrew , Nelson Jacob , Menold Jessica
Published: November 2020

With the rise of the “maker” culture, the prevalence of affordable and rapid “maker” tools has increased dramatically, and the mass proliferation of 3D printers has become a staple of engineering design and engineering design education. The increased use of digital prototyping tools, such as Additive Manufacturing (AM) technologies, is fundamentally transforming the way students and educators approach engineering design courses and hands-on projects. This work investigates the effect of AM prototyping efforts on student perceptions of design processes through an in-situ study conducted across two project-based design courses. Results suggest that students’ perceptions of prototype value, time spent prototyping, and the development of designer knowledge is significantly affected due to AM use during prototyping activities.
Quantification of Uncertainties Distributed in Network-Like Systems
Authors: Wang Zihan , Xu Hongyi
Published: November 2020

Network-like engineering systems, such as transport networks and lattice metamaterials, are featured by high dimensional, complex topological characteristics, which pose a great challenge for uncertainty quantification (UQ). Existing UQ approaches are only applicable to parametric uncertainties, or high dimensional random quantities distributed in a simply connected space (e.g., line section, rectangular area, etc.). The topological characteristics of the input space cannot be captured by existing UQ models. To resolve this issue, a network-based Gaussian random process UQ approach is proposed in this work. By representing the topological input space as a node-edge network, network distance is employed to replace the Euclidean distance in characterizing the spatial correlations. Furthermore, a conditional simulation-based approach is proposed for sampling. Realizations of random quantities on each edge of the network is sampled conditionally on the node values, which are modeled by a multivariable Gaussian distribution. The effectiveness of the proposed approach is demonstrated with two engineering case studies: stochastic thermal conduction analysis of a 3D lattice structure, and characterization of the distortion pattern of an additively manufactured cellular structure.
Non-Linear Finite Element Analysis of an Open Spline Connection
Authors: Vinaud Felipe J. , Bosqueiro Thiago de A.
Published: November 2020

Splines are geared mechanical connections widely used for torque transmission. The analysis of splined connections follows straightforward techniques that take into account the stresses developed at the gear root and flanks. Special difficulties arise when the spline connection needs to eliminate backlash and the part’s geometry is not symmetrical. Misalignment, combined loads and differences in stiffness are responsible for causing a non even contact profile between teeth along the spline circumference. These conditions lead to dissimilar stress profiles and some teeth end up being subject to significantly higher stresses. This work analyses the stress profile of a peculiar spline component used in flight control actuation systems of EMBRAER aircraft, tailored to eliminate backlash due to the need of accurate positioning feedback. Normally, for this kind of application, the external spline has an open geometry and the backlash is avoided by means of a bolt used to tighten both sides of the open spline. There are no known analytic solutions that consider the bolt tightening effect and the contact stress distribution appearing on the gear teeth which depends on the spline geometry and local stiffness of the parts being joined. To approximate the spline local stress distributions, a non-linear finite element model was developed and the resulting stresses were compared to those from methodologies available in the literature. Finally the finite element model results were used to successfully approximate the fatigue life and damage tolerance cycles of a spline connection that broke during certification tests of the flap mechanism of an EMBRAER aircraft.
A Defect Prevention Concept Using Artificial Intelligence
Authors: Eddy Douglas , Krishnamurty Sundar , Grosse Ian , White Michael , Blanchette Damon
Published: November 2020

Defect prevention is particularly critical in operations such as aircraft assembly or service. Failure Modes and Effects Analysis (FMEA) procedures have been deployed manually for many years. However, the manual procedures fail to utilize capability to build intelligence into inspection processes that can facilitate elimination of human error. In this work, we introduce an artificial intelligence (AI)-based concept that can iteratively learn to assure zero defects from a given inspection process. This work introduces a schema that can serve as a knowledge management framework in a relational database for instantiation with inspection process information and data from a detection system. A companion algorithm is presented for the case of a wiring harness bracket installation in a fuselage. The schema and algorithm analyze and assess potential defects posed by Foreign Object Debris (FOD) in parallel to the assembly inspection. A closed loop of logic was introduced to enable anomaly detection by this algorithm to assure zero defects.
Design and Laboratory Validation of a Force-Amplified Piezoelectric Energy Harvesting Unit
Authors: Chen Cheng , Sharafi Amir , Flores Jason , Louie Dela Pena Ralph , Mendoza Priscilla , Ayala Helen , Ortiz-Donato Steven , Sun Jian-Qiao
Published: November 2020

In this paper, an innovative piezoelectric energy harvesting unit (PEHU) for the piezoelectric energy harvesting system (PEHS) from highway traffic is introduced. The proposed PEHU contains a non-linear force amplification mechanism, which substantially increases the electricity output of the PEHU in contrast to the conventional designs with direct loading to the piezoelectric stacks. Quasi-static laboratory tests have been performed to validate the design and the mathematical model. In a quasi-static load cycle of 1333N, a preloaded PEHU prototype is able to generate a voltage of 128V and a potential electric energy of 120mJ with a displacement as small as 2.54mm. The energy density that the PEHS can potentially deliver is estimated to be 8.64J/(m.pass.lane) and is the highest reported in the literature. This level of power generation suggests that the PEHU has a great potential for roadway energy harvesting.
Design a Four-Bar Linkage for Upper Limb Muscle Rehabilitation Exercise: A Simulation Study
Authors: Quarnstrom Joel , Xiang Yujiang
Published: November 2020

In this study, a four-bar linkage with coupler point is designed to guide the arm motion exercise for muscle strength rehabilitation. The hand grasps the coupler point during rotation. The coupler point can generate different shape of trajectories by changing the coupler point’s relative location and the linkage’s dimensions. The rotating coupler point is used to guide the user’s hand to exercise arm muscles for rehabilitation. A two-dimensional (2D) musculoskeletal arm model is used to simulate the arm motion. The inverse-dynamics-based optimization method is used for trajectory reconstruction to determine the joint torque and muscle forces. The effect of different shapes of coupler point trajectory on specific muscle force excise is investigated, such as kidney shape, heart shape, and woven shape trajectories.
Error Quantification in Dynamic Applications of Weakly Nonlinear Transducers
Authors: Cilenti Lautaro , Chijioke Akobuije , Vlajic Nicholas , Balachandran Balakumar
Published: November 2020

Characterization and quantification of dynamic measurements is an ongoing area of research in the metrological community, as new calibration methods are being developed to address dynamic measurement applications. In the development undertaken to date, one largely assumes that nominally linear transducers can be used with linear assumptions in deconvolution of the input from the response and in system identification. To quantify the errors that arise from these assumptions, in this article, the effects of weak nonlinearities in transducers that are assumed to behave linearly during dynamic excitations are studied. Specifically, a set of first-order and second-order systems, which can model many transducers with weak nonlinearities, are used to numerically quantify the systemic errors due to the linear assumptions underlying the deconvolution. We show through the presented results the evolution of different error metrics over a large parameter space of possible transducers. Additionally, an example of quantification of the errors due to linear assumptions in system identification is demonstrated by using a time-series sparse regression system identification strategy. It is shown that the errors generated from linear identification of a nonlinear transducer can counteract the systemic errors that arise in linear deconvolution when the linear system identification is performed in similar loading conditions. In general, the methodology and results presented here can be useful for understanding the effect of nonlinearity in single degree of freedom transient dynamics deconvolution and specifically in specifying certain metrics of errors in transducers with known weak nonlinearities.
Towards Data-Driven Modeling of Pathological Tremors
Authors: Wang Jiamin , Gupta Sunit K. , Barry Oumar
Published: November 2020

Understanding the dynamics of pathological tremors (e.g., Parkinson’s Disease, Essential Tremor) is crucial to developing effective treatments for these neurological disorders. This paper studies the data-driven modeling of periodic and quasiperiodic tremors. A general neuromusculoskeletal model is proposed to serve as the theoretical basis of this study. The Parkinsonian tremor data is first observed in terms of periodicity, frequency composition, and chaotic characteristics, which confirm tremor is a nonlinear dynamics problem. Two data-driven models are then proposed to predict the nonlinear dynamics of tremor: (1) a model-free approach via long short-term memory recurrent neural network, and (2) a model-based approach via extended dynamical mode decomposition. These models are compared to existing models and the results show that the proposed models outperform existing models for long term prediction of tremor.
Design of Single-DOF Immersive Upper Limb Rehabilitation System via Kinematic Mapping and Virtual Reality
Authors: Zhao Ping , Guan Haiwei , Zhang Yating , Chen Yuwen , Deng Xueting , Chen Haodong
Published: November 2020

Mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patients usually has its individual pattern, thus we adopt clustering-based machine learning technique to find a limited number of motion patterns for upper-limb rehabilitation, so that they could represent the large amount of those from people who have various body parameters. Using the regression motion of the clustering result as the task motion, in this paper we seek to apply kinematic-mapping-based motion synthesis framework to design a one-DOF mechanism such that it could lead the patients’ upper limb through the task motion. Also,considering rehab training generally involves a large amount of repetition in daily basis, this paper has developed an immersive rehab system with Unity3D based on Virtual Reality (VR). A patient user interface as well as an administrator user interface are presented, and a two-mode rehabilitation strategy is proposed. The construction of the integrated system and a prototype of the upper limb rehab device are also shown in the end of this paper.
Excimer Laser Treatment of Steel Fibers for Improved Adhesion to Silicone Rubber
Authors: Sancaktar Erol , Liu Xiaoxiao
Published: November 2020

Former investigators observed characteristic laser-induced structure on synthetic fibers and steel cord surfaces after irradiation, which is considered by us as an advantageous factor in developing bonding strength of fiber-elastomer composites. We applied various UV laser treatments on the surfaces of steel fiber in order to obtain similar topographic features. Surface modification was observed under scanning electron microscope (SEM). In consideration as factors in bonding strength, mechanical properties of the matrix elastomer (silicon rubber) had been tested in addition to its thermal properties by differential scanning calorimetry (DSC) and Carbon Black (CB) filler dispersion properties by atomic force microscopy (AFM). As the main test for adhesion strength, we performed a fiber pull-out test method developed by our research group for bonding strength of cord fibers to silicon rubber in both neat and CB filled forms for comparison purposes. Our experiment results revealed better adhesion strength when using silicone rubber matrix reinforced with CB.