bluuebunny/crossref_metadata_2025_split huggingface dataset:
The global burden of periodontal diseases in 204 countries and territories from 1990 to 2019
Authors: Zhang Xuexue , Wang Xujie , Wu Jingxian , Wang Miaoran , Hu Biaoyan , Qu Hua , Zhang Jiwei , Li Qiuyan 
Published: November 2022

AbstractAimsThe aim of this study was to report the incidence, prevalence, and disability‐adjusted life‐years (DALYs) of periodontal diseases during the period 1990–2019.MethodsData on periodontal diseases were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2019. The estimated annual percentage changes were calculated to evaluate the changing trend of age‐standardized incidence, prevalence, and DALY rates related to periodontal diseases.ResultsGlobally, there were 1,087,367,744.0 cases with 91,518,820.6 new incidence and 7,090,390.3 DALYs of periodontal diseases in 2019, almost twice as many as in 1990. Moreover, the pace of increase in age‐standardized incidence, age‐standardized prevalence, and age‐standardized DALY rates had accelerated during the 1990–2019 time period, with EAPC of 0.29 (95% CI, 0.22 to 0.35), 0.34 (95% CI, 0.26 to 0.43), and 0.35 (95% CI, 0.27 to 0.44) separately. The corresponding age‐standardized percentage changes were more pronounced in females, Southeast Asia, and low‐middle SDI regions. Western Sub‐Saharan Africa was the high‐risk area of standardized periodontal diseases burden in 2019, among which Gambia was the country with the heaviest burden.ConclusionThe globally incidence, prevalence, and DALYs of periodontal diseases are substantially increased from 1990 to 2019, which highlights the importance and urgency of periodontal care.
Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia
Authors: Rodriguez‐Lopez Merida , Leckie George , Kaufman Jay S. , Merlo Juan 
Published: November 2022

AbstractBackgroundMeasuring multiple and higher‐order interaction effects between multiple categorical variables proves challenging.ObjectivesTo illustrate a multilevel modelling approach to studying complex interactions.MethodsWe apply a two‐level random‐intercept linear regression to a binary outcome for individuals (level‐1) nested within strata (level‐2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010.ResultsThe absolute risk of preeclampsia was 4% but was predicted to vary from 1% to 44% across strata. The stratum discriminatory accuracy was 30% according to the variance partition coefficient (VPC) and 0.73 according to the area under the receiver operating characteristic curve (AUC). While the risk heterogeneity across strata was primarily due to the main effects of the categories defining the strata, 5% of the variation was attributable to their two‐ and higher‐way interaction effects. One stratum presented a positive interaction, and two strata presented negative interaction.ConclusionsMultilevel modelling is an innovative tool for identifying and analysing higher‐order interaction effects. Further work is needed to explore how this approach can best be applied to making causal inferences.
Bare bones, or a rich feast? Taking care with context in a data rich world
Authors: Finch Sue , Gordon Ian 
Published: November 2022

AbstractProviding a rich context has become a sine qua non of principled teaching of applied statistical thinking. With increasing opportunities to access secondary data, there should be increasing opportunity to work with rich context. We review the contextual information provided in 41 data sets suitable for introductory tertiary statistics teaching, available in the R “datasets” package, and investigate the source information for four data sets. We find failure to describe and retain important contextual information, including aspects that raise questions about the credibility of the data for statistical inference. The sanitization of data reduces the opportunities for learning meaningful lessons in statistical thinking and the real‐world application of statistics. We advocate for teachers and users of such data to be curious about the provenance and context, and for the curators and distributors to examine, where possible, the primary sources, to accurately preserve the context and optimize pedagogical opportunities.
Research partnerships between blood services and public health authorities: An international, cross‐sectional survey
Authors: Lewin Antoine , Osiowy Carla , Erikstrup Christian , Custer Brian , Renaud Christian , Tiberghien Pierre , Russell Alton , Lieshout‐Krikke Ryanne , O'Brien Sheila F. ,   the Surveillance, Risk Assessment, Policy Sub‐group of the ISBT Transfusion Transmitted Infectious Diseases Working Party
Published: November 2022

AbstractBackground and ObjectivesThe COVID‐19 pandemic has brought to the fore how blood services can partner with public health (PH) authorities to inform decisions. Yet the scope of partnerships between blood services and PH authorities is inadequately documented. We explored how blood services partner with PH authorities outside the scope of COVID‐19.Materials and MethodsOn 19 January 2022, survey was sent to employees of blood services located throughout the world. Survey questions mainly pertained to partnerships with PH authorities, including how blood specimens are used and collected.ResultsTwenty‐seven recipients—4 (14.8%) in Africa, 3 (11.1%) in Asia, 9 (33.3%) in Europe, 6 (22.2%) in North America, 2 (7.4%) in Oceania and 3 (11.1%) in South America—completed the survey. Fifteen recipients (55.6%) indicated their blood service was directly or indirectly supervised by PH authorities. Twenty‐four recipients (88.9%) indicated currently using or planning to use blood donor data or samples for PH research or pathogen surveillance. A substantial proportion of respondents reported using samples or results from non‐routine tests for the surveillance of non‐transfusion‐transmitted infectious disease pathogens (n = 13 [48.1%]); samples or results of non‐routine tests for PH research unrelated to pathogens (n = 10 [37.0%]); donor data for PH research unrelated to pathogens (n = 12 [44.4%]) and donor data for PH research unrelated to transfusion safety (n = 11 [40.7%]). Fourteen (51.9%) had established (or planned to establish) longitudinal cohorts and 19 (70.4%) biobanks.ConclusionThe majority of responding blood services were already involved in or planned to be involved in PH research or pathogen surveillance.
Xenotransplantation and exotransplantation: Strategies to expand the number of donor organs
Authors: Garry Daniel J , Weiner Joshua I , Greising Sarah M , Sachs David H , Garry Mary G 
Published: November 2022

AbstractCardiovascular disease is common and has a high mortality. Due to the limited number of organs available for orthotopic heart transplantation, alternative therapies have received intense interest. In this commentary we contrast xenotransplantation and blastocyst complementation to produce pigs that will serve as donors for organ transplantation. These strategies hold tremendous promise and have the potential to provide an unlimited number of organs for chronic, terminal diseases.
Equivalent Energy Absorption—A Methodology for Improved Automotive Crash Safety Design
Authors: Narayana Peddi Sai Rama , Prakash Raghu V. , Gunti Srinivas , Raghu Kanugula 
Published: November 2022

Abstract
Safety norms across the world are becoming more and more stringent posing new challenges to achieve lightweight vehicle structures. Structures made of advanced/ultra-high strength steels (AHSS) play a vital role in meeting the vehicle safety targets, by absorbing large amounts of impact energy, as well as by withstanding higher impact loads that occur due to vehicle collisions. Safety simulations usually take longer solution times due to their complexity and nonlinear nature. Engineers often encounter with a problem of quick evaluation of safety performance using different grades of materials to optimize the weight and cost. A new methodology—equivalent energy absorption (EEA)—has been proposed to do a quick trade-off study on performance versus weight for various thicknesses and material combinations. A relationship is established between the gauge and grade of a component to derive an equivalent safety performance so that engineers can make quick decisions by conducting minimal number of simulations. A simple rectangular crush box was considered for study to assess the energy absorption (EA) with various material and thickness combinations. A design of experiments (DOEs) study was done using simulations with many numbers of material grades and gauges to construct a 3D response surface between gauge grade and EA parameters to understand the relationship between each of these parameters. A case study has been discussed in the paper about application of this methodology on a vehicle to evaluate its safety performance. It was found that more than 80% evaluation time is reduced using this methodology.
The Effect of Speed-Varying Micro-Cutting Tool Dynamics on Stability During High-Speed Micromilling of Ti6Al4V
Authors: S. Gururaja , Panigrahi Brajesh , Singh Kundan K. 
Published: November 2022

Abstract
Chatter-free machining is necessary in micromilling to avoid the catastrophic failure of micro-end mill. The accuracy of the prediction of chatter-free machining conditions in high-speed micromilling has been improved in this work by including speed-varying micro-end mill dynamics. An optimum design of exponential window has been devised to remove the unwanted spindle dynamics from the displacement signal to construct the speed-dependent frequency response function (FRF) of micro-end mill. The stiffness of the micro-end mill has been found to be increasing with increase in spindle speed and the natural frequency of the micro-end mill has been found to be changing with change in spindle speeds. The cutting velocity-chip load-dependent cutting coefficients have been included to predict the stability using Nyquist criterion. The predicted stability lobe with speed-varying micro-end mill dynamics has increased chatter-free depth of cut significantly compared to the chatter-free depth of cut predicted with static micro-end mill dynamics. The increase in depth of cut with speed-varying dynamics has been found to be 28% at 20,000 rpm, 150% at 52,000 rpm, and 250% at 70,000 rpm. A critical value of acceleration of the workpiece has been identified for chatter onset detection and it has been validated with machined surface image analysis. The magnitude of acceleration in both feed and normal to feed direction has been characterized to analyze the effect of spindle speed and depth of cut on the vibration of workpiece.
Learning to Design Without Prior Data: Discovering Generalizable Design Strategies Using Deep Learning and Tree Search
Authors: Raina Ayush , Cagan Jonathan , McComb Christopher 
Published: November 2022

Abstract
Building an Artificial Intelligence (AI) agent that can design on its own has been a goal since the 1980s. Recently, deep learning has shown the ability to learn from large-scale data, enabling significant advances in data-driven design. However, learning over prior data limits us only to solve problems that have been solved before and biases data-driven learning toward existing solutions. The ultimate goal for a design agent is the ability to learn generalizable design behavior in a problem space without having seen it before. We introduce a self-learning agent framework in this work that achieves this goal. This framework integrates a deep policy network with a novel tree search algorithm, where the tree search explores the problem space, and the deep policy network leverages self-generated experience to guide the search further. This framework first demonstrates an ability to discover high-performing generative strategies without any prior data, and second, it illustrates a zero-shot generalization of generative strategies across various unseen boundary conditions. This work evaluates the effectiveness and versatility of the framework by solving multiple versions of two engineering design problems without retraining. Overall, this paper presents a methodology to self-learn high-performing and generalizable problem-solving behavior in an arbitrary problem space, circumventing the need for expert data, existing solutions, and problem-specific learning.
Kinematics and Statics of a 3-UPURobot in Screw Coordinates
Authors: Zhao Jing-Shan , Wei Song-Tao , Sun Han-Lin 
Published: November 2022

AbstractThis paper investigates the kinematics and statics of a 3-UPU robot in screw coordinates. According to the definition of a twist, both the angular velocity of a rigid body and the linear velocity of a point on it are expressed in screw components. The twist equation is established to calculate the position and posture of each joint. This equation can be applied directly to analyze the statics. According to the definition of a wrench, both the force and torque of the planar linkages are expressed in wrench components. As a result, the wrench equations are established to express the resultant action of a force system in one coordinate frame. Compared with the traditional Cartesian coordinate method, the wrench equation is free from complex algebraic manipulation and convenient to obtain wrench matrix by Plücker coordinates of each wrench. Numerical calculation is applied to solve the kinematics which can conveniently depict the position and posture of each joint in the absolute coordinate frame. Six unknown variables can be solved with each equation of wrench that contains three forces and three torques. The kinematics and static analysis of the 3−UPU robot validate this method.
Accuracy of Initially-Curved Cross-Axis Flexural Pivots
Authors: Serafino Simone , Fanghella Pietro , Verotti Matteo 
Published: November 2022

Abstract
Accuracy of the cross-axis flexural pivot is a fundamental requirement in a variety of applications, from robotics to precision engineering. Many studies have been conducted to improve this feature by investigating the effects of various geometric parameters of the cross-axis pivot, such as orientation of the flexures and position of the intersection point. In the present study, the rotational performance is improved by considering two different features. The first one consists in defining an arrangement based on the position of the flexure centroids, instead of considering the position of their intersection point. The second one consists in introducing an initial curvature for the flexible elements. The constraints introduced by these features lead to the definition of a geometry characterized by two degrees of freedom, that is developed for the design of the curved cross-axis flexural pivot. Different layouts are introduced and nonlinear numerical simulations are carried out to evaluate the pivot accuracy. In particular, accuracy is compared to the one of the straight cross-axis flexural pivot by introducing a proper parameter, based on the determination of the pole of the finite displacements. The results are presented as accuracy design maps, useful to define the geometric layout meeting the accuracy requirements.
Classification-Directed Conceptual Structure Design Based on Topology Optimization, Deep Clustering, and Logistic Regression
Authors: Tsumoto Ryo , Fujita Kikuo , Nomaguchi Yutaka , Yamasaki Shintaro , Yaji Kentaro 
Published: November 2022

Abstract
The structure design of mechanical parts and components has been a significant theme of design automation. Today, topology optimization techniques have become relevant for effectively embodying optimal geometries of structures. However, their optimality is restricted to a particular category through design conditions, parameters, and optimization settings. When viewing the structure design as conceptual design, identifying the optimal category is essential rather than precise details. The category means configuration, morphology, or form rather than shape or geometry. This paper proposes a conceptual structure design framework for overcoming this gap. The framework considers that conceptual design results from classifying potentially possible geometries and identifying the best appropriate category from them. In detail, a topology optimization technique generates diverse optimal geometries under various settings of conditions and parameters, a deep clustering technique, i.e., the variational deep embedding, clusters them into several categories, and a logistic regression technique retrieves the criteria that distinct respective categories as design knowledge. A designer can interactively identify the relevant criteria that lead to the optimal structure for the design requirement by simultaneously revealing and refining those criteria under the retrieved knowledge. This paper applies the framework to a simple bridge design problem to demonstrate its validity and possibilities.
An Algorithm for Multi-Objective Efficient Parametric Optimization
Authors: Weaver-Rosen Jonathan M. , Malak Richard J. 
Published: November 2022

Abstract
Parametric optimization is the process of solving an optimization problem as a function of currently unknown or changing variables known as parameters. Parametric optimization methods have been shown to benefit engineering design and optimal morphing applications through its specialized problem formulation and specialized algorithms. Despite its benefits to engineering design, existing parametric optimization algorithms (similar to many optimization algorithms) can be inefficient when design analyses are expensive. Since many engineering design problems involve some level of expensive analysis, a more efficient parametric optimization algorithm is needed. Therefore, the multi-objective efficient parametric optimization (MO-EPO) algorithm is developed to allow for the efficient optimization of problems with multiple parameters and objectives. This technique relies on the new parametric hypervolume indicator (pHVI) which measures the space dominated by a given set of data involving both objectives and parameters. The novel MO-EPO algorithm is demonstrated on a number of analytical benchmarking problems with various numbers of objectives and parameters. In each case, MO-EPO is shown to find solutions that are as good as or better than those found from the existing P3GA (i.e., equal or greater pHVI value) when the number of design evaluations is limited.
Context-Aware Industrial Robot Testing: Low-Cost Virtual Prototyping Environment
Authors: Pozzi Alessandro , Puricelli Luca , Rossoni Marco , Spadoni Elena , Carulli Marina , Bordegoni Monica , Colombo Giorgio 
Published: November 2022

Abstract
This paper presents a case study regarding the simulation of a robotic workstation to virtually test objects detection and obstacle avoidance. Testing these features inside a virtual environment is useful, especially when human-robot cooperation and interaction are involved. Indeed, it allows users to avoid real dangerous conditions, lowering the possible risks of injuries by the users and cutting down the costs compared to a real testing environment.
The work presented here exploits a framework where a virtual environment is connected to a Robot Operating System (ROS) able to simulate the kinematic of the robot and, on the other side, a physical ultrasonic sensor acts as the bridge with the real world. The latter, driven by an Arduino board, allows the virtual robot to recognize static obstacles in the real world, mapping the surrounding environment and computing a suitable trajectory to accomplish the given task. Thanks to the sensing capability, the virtual robot is also able to react to the presence of other obstacles (e.g. humans) entering the workspace at runtime.
The seamless connection between the virtual and the physical world makes the framework suitable for the fast testing of new algorithms driving the behavior of the robot when interacting with dynamic environments.
Estimation of Vehicle Speed for Low Curvatures Assuming Ideal Steering Behaviour
Authors: Kolachalama Srikanth , Hay Curtis L. , Malik Hafiz 
Published: November 2022

Abstract
In the current scenario, the vehicle is integrated with advanced sensors, infotainment maps and a telematics module, which provide extensive information regarding the terrain and dynamic state, including the radius of curvature (R). The transportation authority had imposed guidelines regarding the range of allowable vehicle speeds for low curvatures (e.g. [15 25] MPH for R = 18.4m), but a unique optimal speed for a definite curvature was not investigated. The maximum allowable speed for R = 8.34m (U-turn) is 6.7 m.s−1, whereas for R = 42.57m (cloverleaf interchange) is 11.17 m.s−1. Therefore, in this article, the concept of Ideal Steering Behavior (ISB) was utilised to estimate a unique speed for a definite R. The functionality of ISB was formulated with steering parameters [Speed, Lateral acceleration, Yaw rate, R] whose boundary conditions were derived from real-time analysis. The test vehicle 2019 Cadillac Escalade provided by General Motors Inc., was driven by four drivers on the test track with R = 18.4m, and in this research, historic driver data under normal driving conditions were utilized to adapt “human-like” driving behaviour. Basic convex optimization and polynomial interpolation techniques were adopted to generate the empirical quadratic function correlating the parameters speed and R. The optimal speed for the test track R = 18.4m was estimated using by known statistical methods which resulted in a similar value of 7.485 m.s−1, and similar procedure was adopted for R = [8.34 42.57] m. The validation of the results was performed by comparing the roll and slip coefficients for the drivers and estimated speed. Traversing the vehicle with the estimated speed is safer as it falls in the recommended range, reflects ISB, and achieves optimal lateral dynamics.
Experimental Investigation of Topology-Optimized Beams With Isotropic and Anisotropic Base Material Assumptions
Authors: Kim Hajin , Carstensen Josephine V. 
Published: November 2022

Abstract
Additive Manufacturing (AM) technologies are promising fabrication methods with the potential to increase customizability and structural complexity. It is well established that the nature of AM typically results in base materials that exhibit an extent of anisotropy. Since topology optimization is a freeform approach that generally achieves high performing designs, it is often suggested as a powerful design-for-AM method. However, most topology optimization frameworks ignore anisotropic effects and assume isotropy of the base material. Although frameworks that consider anisotropy have been suggested, the influence anisotropy has on the physical behavior of fabricated designs is not well understood. Therefore, this work presents an experimental study of topology-optimized structures designed with both isotropic and anisotropic linear elastic material assumptions to explore how much anisotropic considerations matter when it comes to the discrepancy in numerical and experimental performance. The experimental investigation is conducted using a Fused Filament Fabrication print process that allows us to prescribe the anisotropy. The Young’s Modulus of the designated print setup is experimentally determined and used for design of 3D simply supported beams with various material volumes. Samples are fabricated and evaluated using 3-point bending tests. It is seen that the isotropic designs have a slightly better average performance at the design load (1.8–2.0%), but that inclusion of the anisotropic behavior significantly limits behavioral differences across samples (84.4–171.5% decrease in standard deviation) and improves the print success rate.