bluuebunny/crossref_metadata_2025 huggingface dataset:
Is drift ‘directional’? Unequal breeding sex ratio revisited
Authors: Qin Ben
Published: November 2022

Unequal breeding sex ratio can significantly reduce effective population size, allowing a rare neutral allele to jump to a high frequency through genetic drift. However, this one‐way alteration to allele frequency appears inconsistent with the concept that drift is non‐directional. Based on binomial sampling distribution, this study developed a method to directly and exhaustively measure drift by calculating the mean deviation of change in allele frequency, then applied it to cases of unequal breeding sex ratio. The result shows that, under those cases, (1) the mean deviation can always be divided into two halves that are equal in size but opposite in direction; (2) each half consists of one or several categories represented by various allele proportions in the rare sex; (3) this proportion is another factor that determines the outcome of drift, in addition to effective population size and allele frequency; (4) drift is non‐directional on a global scale, but whether an allele will drift up or down can be predicted based on the above factors. This method enables us to dissect every component of the expected change in allele frequency caused by drift and to find out the combined effect of population size, allele frequency and allele proportion in the rarer sex under neutrality but unequal breeding sex ratio.
Reproductive isolation via divergent genital morphology due to cascade reinforcement inOhomopterusground beetles
Authors: Xia Tian , Nishimura Taira , Nagata Nobuaki , Kubota Kohei , Sota Teiji , Takami Yasuoki
Published: November 2022

Secondary contact between incipient species and selection against maladaptive hybridization can drive reinforcement between populations in contact and result in reproductive character displacement (RCD). Resultant divergence in mating traits within a species may generate downstream reproductive isolation between populations with displaced and non‐displaced traits, referred to as the cascade reinforcement hypothesis. We examined this hypothesis using three allopatric populations of the ground beetleCarabus maiyasanuswith a genital lock‐and‐key system. This species shows RCD in male and female genital morphologies in populations in contact with the sister speciesC. iwawakianus. In a reciprocal mating experiment using three allopatric populations with differences in male and female genital sizes, insemination failure increased as the difference in genital size increased. Based on the reproductive isolation index, insemination failure was the major postmating‐prezygotic isolation barrier, at least in one population pair with comparable total isolation to those of other species pairs. By contrast, there was only incomplete premating isolation among populations. These results suggest that RCD in genital morphologies drives incipient allopatric speciation, supporting the cascade reinforcement hypothesis. These findings provide insight into the roles of interspecific interactions and subsequent trait diversification in speciation processes.
The perinatal outcomes by gestational weight gain range at 30 weeks of gestation among pre‐pregnancy underweight women
Authors: Nagao Takeshi , Fukui Sho , Ohde Sachiko , Yamanaka Michiko
Published: November 2022

Aims

To evaluate the perinatal outcomes by gestational weight gain (GWG) range at 30 weeks of gestation among underweight pregnant women (pre‐pregnancy body mass index ≤ 18.5 kg/m2) in Japan.

Methods

This retrospective study was conducted at a hospital in Japan from 2003 to 2020. The underweight pregnant women (UPW; n = 3643) were divided into quartile groups based on the weight gain at 30 weeks of gestation: group Q1 ≤ 5.7 kg, 5.7 kg < Q2 ≤ 7.2 kg, 7.2 kg < Q3 ≤ 8.8 kg, and 8.8 kg < Q4. Clinical characteristics and outcomes were compared using the t‐test, chi‐square test, and multivariable logistic regression analysis.

Results

The cumulative incidences of preterm births were 7.5% (n = 70), 5.0% (n = 45), 5.4% (n = 50), and 4.9% (n = 44), and the birth rates of small for gestational age (SGA) infants were 15.7% (n = 147), 9.6% (n = 87), 6.9% (n = 64), and 5.9% (n = 53) in Q1, Q2, Q3, and Q4, respectively. Multivariable analysis revealed that Q1 was significantly associated with preterm births (adjusted odds ratio [aOR] = 1.6; 95% confidence interval [CI] = 1.0–2.3), and Q1 and Q2 were significantly associated with SGA (adj. OR = 3.0; 95% CI = 2.2–4.3; adj. OR = 1.7; 95% CI = 1.2–2.5, respectively). None of the quartile groups were significantly associated with the incidence of primary cesarean sections, gestational diabetes mellitus, and macrosomia.

Conclusions

In UPW, GWG at 30 weeks of ≤5.7 kg and ≤7.2 kg are associated with preterm birth and SGA rates, respectively.
Demographic plasticity in an invasive species: The effects of time since invasion and population management history on beavers in Tierra del Fuego, Argentina
Authors: González‐Calderón A. , Escobar J. , Deferrari G. , Schiavini A.
Published: November 2022

The North American beaver (Castor canadensis) has been an invasive species in the Tierra del Fuego archipelago since its intentional introduction in 1946. Its activities have led to such severe impacts on various environments that eradication has been tested as a management strategy. We assessed how vital rates (i.e., survivorship and reproduction) of the beavers were affected by time since invasion and population management history (such as lethal control). We constructed vertical life tables and compared survivorship, age‐specific survivorship, generation time, and life expectancy for different landscapes and management histories. As part of an eradication pilot program conducted between 2016–2018, 922 beavers were removed in seven pilot areas of the Isla Grande de Tierra del Fuego, Argentina. Areas in which beavers have resided longest since invasion, areas without hunting pressure, and areas previously cleared of beavers had higher survivorship and longer generation time and life expectancy. Areas where beaver management was historical (trapping performed by the provincial government) or focused (trapping by landowners) had shorter life expectancy and generation time and advanced age at first reproduction. Beavers showed demographic plasticity in relation to time since invasion (increasing survivorship, generation time, life expectancy, and cohort life expectancy consistent with populations close to carrying capacity in areas with low or null management). They also exhibited plasticity in response to management histories (advanced breeding onset, reduced survivorship, and life expectancy in managed areas—similar to managed populations in their native range). We present management implications from demographic perspective for a future eradication or control program of beavers. We also highlight the importance of landowners in shaping beaver demography for the future management of the species. Beaver demography reacts dynamically and rapidly to local removal, creating challenges for management based on the removal of beavers.
Effectiveness of game‐based core exercise in children with non‐neuropathic bladder dysfunction and comparison to biofeedback therapy
Authors: Kilcik Melek Havva , Ozdemir Filiz , Elmas Ahmet Taner
Published: November 2022

Objectives

This study was planned to evaluate the effectiveness of game‐based core exercises in children diagnosed with non‐neuropathic bladder dysfunction and compare this effectiveness to that of the biofeedback treatment method.

Methods

The study included 48 children, aged 6–13 years, who were diagnosed with non‐neuropathic bladder dysfunction. The children satisfying the inclusion criteria were selected by drawing lots from the population with the method of nonprobability random sampling. The patients were divided into three groups: group I, “game‐based core stabilization exercise training”; group II, “biofeedback program”; and group III, “game‐based core stabilization exercise training in addition to the biofeedback program.” The Dysfunctional Voiding and Incontinence Symptom Scale (DVISS) scores and uroflowmetry values of the patients were evaluated before and after the treatment.

Results

The mean age of the participants was 8.81 ± 2.08 years. There was a statistically significant difference between the pretreatment and post‐treatment DVISS scores in all three groups (p < .05). However, no significant difference was found among the groups. There was no statistically significant difference in the uroflowmetry results of the patients in group I and II before and after the treatment. In group III, the time to maximum flow rate after treatment was significantly reduced, and the average flow rate was significantly increased.

Conclusions

According to the results of this study, the use of game‐based exercises along with biofeedback treatment may reduce DVISS scores in children with non‐neuropathic bladder dysfunction. A combination of the two methods may have positively affected the uroflowmetry results of the patients. We think that game‐based exercises will contribute to the literature as a new treatment option in the treatment of non‐neuropathic bladder dysfunction.
Elastic structural analysis based on graph neural network without labeled data
Authors: Song Ling‐Han , Wang Chen , Fan Jian‐Sheng , Lu Hong‐Ming
Published: November 2022

Artificial intelligence is gaining increasing popularity in structural analysis. However, at the structural system level, the appropriateness of data representation, the paucity of data, and the physical interpretability of results are rarely studied and remain profound challenges. To fill such gaps, a physics‐informed model named StructGNN‐E (i.e., structural analysis based on graph neural network [GNN]–elastic) based on the GNN architecture, which is capable of implementing the elastic analysis of structural systems without labeled data, is proposed in this study. The systems with structural topologies and member configurations are organized as graph data and later processed by a modified graph isomorphism network. Moreover, to avoid dependence on big data, a novel physics‐informed paradigm is proposed to incorporate mechanics into deep learning (DL), ensuring the theoretical correctness of the results. Numerical experiments and ablation studies demonstrate the unique effectiveness of StructGNN‐E against common DL models, with an average accuracy of 99% and excellent computational efficiency. Due to its differentiability, StructGNN‐E is promising for bidirectionally linking structural parameters and analysis results, paving the way for a new end‐to‐end structural optimization method in the future.
Migration of Rhipicephalus microplus ticks among cattle
Authors: Mazzucco Panizza Matilde N. , Rossner Maria V. , Signorini Marcelo L. , Nava Santiago
Published: November 2022

The aim of this work was to quantitatively analyse the magnitude of the migration of Rhipicephalus microplus ticks among cattle under field conditions, in groups of bovines with different stocking rates. The role of this phenomenon in the epidemiology of Anaplasma marginale has been discussed. Cattle naturally infested with R. microplus (donors) and cattle non‐infested with R. microplus (recipients) were clustered for 13 days into two groups with low and high stocking rates (G1 and G2 respectively). The initial prevalence of infestation (infested cattle / total cattle) was 20% in both groups. Adult migratory ticks from donor to recipient cattle were recorded by examination of the recipient cattle on days 2, 6, 9, and 13. The tick infestation rate, calculated using the Kaplan–Meier survival test, was higher in G2 (p = 0.05). The cumulative incidence on day 13 was 25% in G1 and 65% in G2, with no significant differences. The results demonstrate that migration of adults of R. microplus under field conditions occurs, in accordance with previous studies, and that its magnitude is associated with the stocking rate. These results highlight the relevance of R. microplus in the epidemiology of A. marginale through its role as a vector in the intrastadial transmission of this pathogen of cattle.
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

Aims

The aim of this study was to report the incidence, prevalence, and disability‐adjusted life‐years (DALYs) of periodontal diseases during the period 1990–2019.

Methods

Data 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.

Results

Globally, 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.

Conclusion

The 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

Background

Measuring multiple and higher‐order interaction effects between multiple categorical variables proves challenging.

Objectives

To illustrate a multilevel modelling approach to studying complex interactions.

Methods

We 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.

Results

The 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.

Conclusions

Multilevel 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

Providing 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

Background and Objectives

The 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 Methods

On 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.

Results

Twenty‐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.

Conclusion

The 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

Cardiovascular 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

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

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

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

This 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

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

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

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

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

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

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.
Reinforcement Learning As an Alternative for Parameter Prediction In Design for Sheet Bulk Metal Forming
Authors: Dworschak Fabian , Sauer Christopher , Schleich Benjamin , Wartzack Sandro
Published: November 2022

This contribution presents an approach and a case study to compare Reinforcement Learning (RL) and Genetic Algorithms (GA) for parameter prediction in Sheet Bulk Metal Forming (SBMF). Machine Learning (ML) and Multi-Objective Optimization (MOO) to provide different points of view for the prediction of manufacturing parameters. While supervised learning depends on sufficient training data, GA lack the ability to explain how sufficient parameters were achieved. RL could help to overcome both issues, as it is independent from training data and can be used to learn a policy leading towards suitable parameter combinations, which can be tracked through the solution space. To probe RL in terms of feasibility for parameter prediction and necessary training effort SBMF serves as an appropriate use case because solution and objective function space are multidimensional, and their relations are challenging for MOO. The results of a Reinforcement Learner and a GA are compared and discussed to answer the question under which circumstances RL can provide an alternative for parameter prediction.
Vibration Energy Harvesting in Light Vehicles: Road Tests and Interpretative Models
Authors: Doria Alberto , Moro Federico , Tommasino Domenico
Published: November 2022

The interest towards piezoelectric energy harvesters has been fostered in recent years by the development of ultra-low power electronics. An experimental analysis approach based on modal testing is here proposed in order to detect the best position on a bicycle of a piezo-harvester. Road tests show that vibrations are in the low frequency range so that the energy harvester has to be properly tuned to get its largest electrical response. Different tuning strategies of the same piezo-harvester, mounted in the best location, are tested and compared. The best setup is selected by considering as figures of merit the average stress inside the piezo-layer of the harvester (which affects its lifespan) and the maximum electric power which can be harvested. These figures are both analytically estimated from the measured power spectral density of the output open circuit voltage, which is experimentally determined. It is shown that the configuration with the largest tip mass provides the largest delivered power. Nevertheless, in order to preserve the device lifespan, harvesters with oscillator and liquid tip mass may represent a good tradeoff between the amount of generated stress and delivered power. The methods presented in this paper can be also adopted for predicting the behavior of harvesters mounted on other light vehicles.
Hybrid Predictive Model for Assessing Spinal Loads for 3d Asymmetric Lifting
Authors: Zaman Rahid , Quarnstrom Joel , Xiang Yujiang , Rakshit Ritwik , Yang James
Published: November 2022

In this study, a hybrid predictive model is used to predict 3D asymmetric lifting motion and assess potential musculoskeletal lower back injuries for asymmetric lifting tasks. The hybrid model has two modules: a skeletal module and an OpenSim musculoskeletal module. The skeletal module consists of a dynamic joint strength based 40 degrees of freedom spatial skeletal model. The skeletal module can predict the lifting motion, ground reaction forces (GRFs), and center of pressure (COP) trajectory using an inverse dynamics based optimization method. The equations of motion are built by recursive Lagrangian dynamics. The musculoskeletal module consists of a 324-muscle-actuated full-body lumbar spine model. Based on the generated kinematics, GRFs and COP data from the skeletal module, the musculoskeletal module estimates muscle activations using static optimization and joint reaction forces through the joint reaction analysis tool. Muscle activation results between simulated and experimental EMG are compared to validate the model. Finally, potential lower back injuries are evaluated for a specific-weight asymmetric lifting task. The shear and compression spine loads are compared to NIOSH recommended limits. At the beginning of the dynamic lifting process, the simulated compressive spine load beyond the NIOSH action limit but less than the permissible limit. This is due to the fatigue factors considered in NIOSH lifting equation.
A Computational Framework for the Evaluation of Resilience in Deep Space Habitat Systems
Authors: Behjat Amir , Ibrahimov Roman , Lenjani Ali , Barket Aaron , Martinus Kathleen , Maghareh Amin , Whitaker Dawn , Bilionis Illias , Dyke Shirley
Published: November 2022

Resilience is a vital consideration for designing and operating a deep space habitat system. The numerous hazards that may affect a deep space habitat and its crew during its lifecycle need to be considered early in the design. Trade-off studies are the typical method used to assess the cost and value of different design choices. Here we develop a modular dynamic computational framework intended for rapid simulation and evaluation of the resilience of different system configurations. The framework uses a system-level phenomeno-logical Markov model of the habitat systems, enabling us to assess multiple habitat configurations and evaluate their performance in the presence of several hazards and user-defined control policies. System fault detection and repairs are modeled. External disturbances, including meteorites impact, temperature fluctuations, and dust, are modeled based on the lunar environment, envisioning a deep space habitat design. We use a reflexive health management subsystem that prioritizes recovery actions based on the robotic agent’s availability to close the loop. In addition to performance, a resilience metric is included to quantify the system’s resilience over the design lifecycle. We illustrate the use of the framework for supporting early-stage design decisions of a habitat system. Our case study focuses on designing the power generation system considering cost and energy efficiency.
On Practical Aspects of Variational Consistency in Contact Dynamics
Authors: Recuero Antonio , Lindsay Alexander
Published: November 2022

Usage of contact mechanics methodologies is a pervasive modeling requirement in dynamic simulations. While for some trivial problems, solutions taken from analytical geometry are available, use of a finite element framework is common to achieve formulation generality. This work explores two dynamic contact formulations: one based on the traditional node-to-segment (NTS) approach, and a variationally consistent segment-to-segment (STS) mortar formulation. The NTS formulation employed here enforces the constraints kinematically (i.e., the interpenetration is enforced to the solver tolerance), whereas the mortar approach uses Lagrange multipliers to enforce the contact constraints. Both approaches are implemented in the open-source finite element framework Multiphysics Object-Oriented Simulation Environment (MOOSE). The results highlight two relevant contact-interface-related dynamic phenomena in finite element simulations. First, stabilization of contact constraints is discussed, taking into account the evolution of the total energy in a benchmark problem. Second, the influence of finite element discretization on both of the aforementioned contact formulations is analyzed by exercising a large-deformation example with continuous relative sliding. Variationally consistent contact approaches such as the mortar formulation lead to improved energy preservation and avoid spurious excitation of the system’s frequencies. This is especially relevant in settings where inertia and vibrations are of importance.
Tablets, Pens, and Pencils: The Influence of Tools on Sketching in Early Stage Design
Authors: Das Madhurima , Huang May , Yang Maria C.
Published: November 2022

Sketching is often used as a tool during idea generation in the early stages of engineering design. At the same time, the rapid increase in remote engineering and design work paves the way for an increased reliance on digital design tools and technologies throughout the design process. Sketch quality and quantity have been shown to be linked to design perceptions and design outcomes. Additionally, sketch quality and style have been linked with the gender of the sketcher. Thus, there are financial, social, and ethical motivations for understanding how digital design tools influence sketching during early stages of engineering design.

In this study, we investigate the influence of hand sketching on a tablet as compared to pencil or pen and paper on early stage sketching for concept generation. We also assess the influence of gender on sketching attributes. We ask three mixed gender groups of participants (using pen, pencil, and a tablet) to sketch concepts in response to an open-ended design prompt. We hypothesize that participants using tablet and pencil will produce fewer drawings than those using pen due to their ability to erase and focus on perfecting drawings, and we expect participants using the tablet to produce cleaner drawings with smoother strokes due to the tablet’s ability to auto-smooth lines. Based on prior literature, we posit that women and gender minorities will produce fewer sketches and use the feathering style of sketching more than men.

We find that sketch quality is highest for pencil drawings and lower for tablet and pen drawings. We also find that concept novelty is negatively correlated with how understandable the concept is. Participants reported that experiences of drawing on paper and on the tablet differ in terms of missing the feeling of friction on the tablet and finding that too many features in a tool can be distracting during concept generation. Interestingly, participants from all groups mentioned that they were not good at sketching. Finally, we find several interesting results with respect to gender differences in sketching performance: namely, women and other gender minorities produced a higher quantity of sketches but did not have any difference in their sketch quality or style.
Practical End-Effector Development Through Task Interface Taxonomy Analysis
Authors: Sharp Andrew , Lovan Austin , Herrera Eduardo , Laske Evan
Published: November 2022

This paper was motivated by the need for reliable robotic agents to maintain spacecraft systems in orbit around the moon, Gateway, and other distant locations, that will be uninhabited for long periods. This effort outlines an analysis methodology for determining the manipulation potential required of a robotic gripper based on a set of tasks. The core of the method is to determine all the possible ways for manipulating the task set interfaces (turning a knob) and defining each of the motions (grasping) in terms of taxonomy (contact, prehensile, motion). By eliminating all but the lowest taxonomy, the minimum manipulation potential can be determined. Using the minimum manipulation potential to choose the gripper means it can be the most robust possible, something vital to long-term distant missions. The methodology was applied to a set of interfaces drawn from !SS and expected Gateway operations. The next step was to apply the methodology to each interface and filter the results. Several interfaces with complicated motions were replaced with simpler interfaces that fulfill the same role. The group also agreed that other interfaces, drills, and fire extinguishers should be specially designed robotic tools. After the analysis, a Commercial off-the-shelf gripper’s fingers were specially designed for the operation interfaces. This approach effectively resulted in a co-design of the gripper and the environment. Several successful demonstrations (first using commercial software and then using ROS, Movelt, and NASA software) were performed to ensure the analysis method and gripper were fully capable.