bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractBackgroundBasal 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 MethodsIn 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.ResultsThe 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.ConclusionUltrahigh‐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

AbstractComputed 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

AbstractIn 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.
image
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

AbstractIn 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 (&gt;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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.