In robust design, associated with each quality characteristic, the design objective often involves multiple aspects such as “bringing the mean of performance on target” and “minimizing the variations.” Current ways of handling these multiple aspects using either the Taguchi’s signal-to-noise ratio or the weighted-sum method are not adequate. In this paper, we solve bi-objective robust design problems from a utility perspective by following upon the recent developments on relating utility function optimization to a Compromise Programming (CP) method. A robust design procedure is developed to allow a designer to express his/her preference structure of multiple aspects of robust design. The CP approach, i.e., the Tchebycheff method, is then used to determine the robust design solution which is guaranteed to belong to the set of efficient solutions (Pareto points). The quality utility at the candidate solution is represented by means of a quadratic function in a certain sense equivalent to the weighted Tchebycheff metric. The obtained utility function can be used to explore the set of efficient solutions in a neighborhood of the candidate solution. The iterative nature of our proposed procedure will assist decision making in quality engineering and the applications of robust design.

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0–3 YO population. In this study, head CT scans from fifty-six 0–3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

In this study, a statistical model of cranium geometry for 0- to 3-month-old children was developed by analyzing 11 CT scans using a combination of principal component analysis and multivariate regression analysis. Radial basis function was used to morph the geometry of a baseline child head finite element (FE) model into models with geometries representing a newborn, a 1.5-month-old, and a 3-month-old infant head. These three FE models were used in a parametric study of near-vertex impact conditions to quantify the sensitivity of different material parameters. Finally, model validation was conducted against peak head accelerations in cadaver tests under different impact conditions, and optimization techniques were used to determine the material properties. The results showed that the statistical model of cranium geometry produced realistic cranium size and shape, suture size, and skull/suture thickness, for 0- to 3-month-old children. The three pediatric head models generated by morphing had mesh quality comparable to the baseline model. The elastic modulus of skull had a greater effect on most head impact response measurements than other parameters. Head geometry was a significant factor affecting the maximal principal stress of the skull (p = 0.002) and maximal principal strain of the suture (p = 0.021) after controlling for the skull material. Compared with the newborn head, the 3-month-old head model produced 6.5% higher peak head acceleration, 64.8% higher maximal principal stress, and 66.3% higher strain in the suture. However, in the skull, the 3-month-old model produced 25.7% lower maximal principal stress and 11.5% lower strain than the newborn head. Material properties of the brain had little effects on head acceleration and strain/stress within the skull and suture. Elastic moduli of the skull, suture, dura, and scalp determined using optimization techniques were within reported literature ranges and produced impact response that closely matched those measured in previous cadaver tests. The method developed in this study made it possible to investigate the age effects from geometry changes on pediatric head impact responses. The parametric study demonstrated that it is important to consider the material properties and geometric variations together when estimating pediatric head responses and predicting head injury risks.

No abstract

Objectives: To summarize development processes and research hotspots of MRI research on acupuncture and to provide new insights for researchers in future studies.Methods: Publications regarding MRI on acupuncture from inception to 2020 were downloaded from the Web of Science Core Collection. VOSviewer 1.6.15 and CiteSpace V software were used for bibliometric analyses. The main analyses include collaboration analyses between countries/institutions/authors, co-occurrence analysis between keywords, as well as analyses on keyword bursts, citation references, and clusters of references.Results: A total of 829 papers were obtained with a continually increased trend over time. The most productive country and institution in this field were the People's Republic of China (475) and KyungHee University (70), respectively. Evidence-based Complementary and Alternative Medicine (83) was the most productive journal, and Neuroimage (454) was the most co-cited journal. Dhond's et al. (2008) article (co-citation counts: 58) and Napadow's et al. (2005) article (centrality: 0.21) were the most representative and symbolic references, with the highest co-citation number and centrality, respectively. Jie Tian had the highest number of publications (35) and Kathleen K S Hui was the most influential author (280 co-citations). The four hot topics in MRI on acupuncture were acupuncture, fMRI, pain, and stimulation. The three frontier topics were connectivity, modulation, and fMRI. Based on the clustering of co-cited documents, chronic low back pain, sham electro-acupuncture treatment, and clinical research were the main research directions.Conclusion: This study provides an in-depth perspective for MRI research on acupuncture and provides researchers with valuable information to determine the current status, hot spots, and frontier trends of MRI research on acupuncture.

This erratum is to correct for a gantry tilt effect that was not considered in the CT image processing in the original publication. Figures 3-8, 10-12, and Table 2 have been updated to reflect the geometry changes of the pediatric heads in both the CT segmentation results and the parametric FE model. The p-values of material and geometry factors in the parametric study in Fig. 6 changed slightly from the original publication, but these changes did not affect statistical significance. After correction, on average, the model of the 3-monthold head still predicted higher maximal principal stress and strain in the suture than the model of the newborn head, but this age effect dropped from 64.8 to 32.0% for the stress and from 66.3 to 51.1% for the strain. Similarly, after correction, the model of the 3-month-old head still predicted lower maximal principal stress and strain in the skull than the model of the newborn head, but the age effect changed from -25.7 to -35.5% for the stress and from -11.5 to -6.2% for the strain. The optimal material parameters shown in Table 2 also changed slightly from the original publication. In particular, the optimal elastic moduli of skull, suture, dura, and scalp were 164.3, 15.8, 17.3, and 8.5 MPa, respectively, after correction.

No abstract

Skull fracture is one of the most common pediatric traumas. However, injury assessment tools for predicting pediatric skull fracture risk is not well established mainly due to the lack of cadaver tests. Weber conducted 50 pediatric cadaver drop tests for forensic research on child abuse in the mid-1980s (Experimental studies of skull fractures in infants, Z Rechtsmed. 92: 87-94, 1984; Biomechanical fragility of the infant skull, Z Rechtsmed. 94: 93-101, 1985). To our knowledge, these studies contained the largest sample size among pediatric cadaver tests in the literature. However, the lack of injury measurements limited their direct application in investigating pediatric skull fracture risks. In this study, 50 pediatric cadaver tests from Weber's studies were reconstructed using a parametric pediatric head finite element (FE) model which were morphed into subjects with ages, head sizes/shapes, and skull thickness values that reported in the tests. The skull fracture risk curves for infants from 0 to 9 months old were developed based on the model-predicted head injury measures through logistic regression analysis. It was found that the model-predicted stress responses in the skull (maximal von Mises stress, maximal shear stress, and maximal first principal stress) were better predictors than global kinematic-based injury measures (peak head acceleration and head injury criterion (HIC)) in predicting pediatric skull fracture. This study demonstrated the feasibility of using age- and size/shape-appropriate head FE models to predict pediatric head injuries. Such models can account for the morphological variations among the subjects, which cannot be considered by a single FE human model.