Biomechanical analyses of static and dynamic fixation techniques of retrograde interlocking femoral nailing using nonlinear finite element methods

Femoral shaft fractures can be treated using retrograde interlocking nailing systems; however, fracture nonunion still occurs. Dynamic fixation techniques, which remove either the proximal or distal locking screws, have been used to solve the problem of nonunion. In addition, a surgical rule for dynamic fixation techniques has been defined based on past clinical reports. However, the biomechanical performance of the retrograde interlocking nailing systems with either the traditional static fixation technique or the dynamic fixation techniques has not been investigated by using nonlinear numerical modeling. Three-dimensional nonlinear finite element models were developed, and the implant strength, fixation stability, and contact area of the fracture surfaces were evaluated. Three types of femoral shaft fractures (a proximal femoral shaft fracture, a middle femoral shaft fracture, and a distal femoral shaft fracture) fixed by three fixation techniques (insertion of all the locking screws, removal of the proximal locking screws, or removal of the distal locking screws) were analyzed. The results showed that the static fixation technique resulted in sufficient fixation stability and that the dynamic fixation techniques decreased the failure risk of the implant and produced a larger contact area of the fracture surfaces. The outcomes of the current study could assist orthopedic surgeons in comprehending the biomechanical performances of both static and dynamic fixation techniques. In addition, the surgeons could also select a fixation technique based on the specific patient situation using the numerical outcomes of this study.     

Detecting removed attributes in the cyber system for smart manufacturing

The Journal of Supercomputing - According to the concept of edge computing, some service and data should be moved from the centralized data server to the data source for enhancing the computational...     

Correcting vindictive bidding behaviors in sponsored search auctions

In this study, we aim to develop a pricing mechanism that reduces the effects resulted by vindictive advertisers who bid on sponsored search auctions run by search engine providers. In particular, we aim to ensure payment fairness and price stability in these auctions. With the generalized second price principle, advertisers pay the next-ranked bid value rather than the price that they bid. Vindictive bidders take advantage of this principle to manipulate the payment of a previously-ranked advertiser. Vindictive bidding results in unfair outcomes and eliminates equilibria. However, it is difficult to compute rational payments for all advertisers as advertisers’ valuations are private. Our proposed mechanism decreases the payment to make up for the utility loss that is induced by vindictive bidding. The vindictive advertiser is simultaneously punished with an additional payment. According to our theoretical analyses and simulations, the proposed mechanism efficiently decreases the effects that result from vindictive bidding, and guarantees equilibrium outcomes.     

Designing the rule classification with oversampling approach with high accuracy for imbalanced data in semiconductor production lines

The product quality is the major factor for enhancing the production ability and competitiveness. Decreasing the cost and increasing production capacity are common approaches to realize the enhancement of the product quality. The production managers apply various multimedia data to evaluate the product quality. For example, capturing the stamping sound to evaluate the correct cutting and taking the component image to measure the chip positions are common heterogeneous multimedia data that are applied to manufacturing. However, the production managers prefer to minimize the number of defective products, e. g. the secondary operation and fixing the product tolerance in the assembly stage, to fitting the production target. Therefore, contrasting the defective product identification procedure with high accuracy becomes a challenge due to the decrease of the number of the defective products. In this paper, we propose the Rule Classification with Oversampling (RCOS) approach to provide the high accuracy with few defective products. The proposed RCOS includes the oversampling technique and the rule classification approach to emphasize the properties of the defective products and provide the precise classes. Given few defective products, capturing the properties of the failure is difficult. The RCOS considers the revised Synthetic Minority Over-Sampling Technique (SMOTE) to highlight the failure properties, and then the rule model is considered to extract the root cause of the defective products. We implement the proposed RCOS in the semiconductor production line. From the experiment results, the proposed RCOS provide about at most 98% in accuracy, and the comparison shows that the results have been improved in common criteria e. g. the true-positive rate, G mean, F1 score, and False Alarm Rate. Therefore, the proposed RCOS provides high practicality for the implementation consideration.

     

Biocompatibility and Biological Performance Evaluation of Additive-Manufactured Bioabsorbable Iron-Based Porous Suture Anchor in a Rabbit Model

This study evaluated the biocompatibility and biological performance of novel additive-manufactured bioabsorbable iron-based porous suture anchors (iron_SAs). Two types of bioabsorbable iron_SAs, with double- and triple-helical structures (iron_SA_2_helix and iron_SA_3_helix, respectively), were compared with the synthetic polymer-based bioabsorbable suture anchor (polymer_SAs). An in vitro mechanical test, MTT assay, and scanning electron microscope (SEM) analysis were performed. An in vivo animal study was also performed. The three types of suture anchors were randomly implanted in the outer cortex of the lateral femoral condyle. The ultimate in vitro pullout strength of the iron_SA_3_helix group was significantly higher than the iron_SA_2_helix and polymer_SA groups. The MTT assay findings demonstrated no significant cytotoxicity, and the SEM analysis showed cells attachment on implant surface. The ultimate failure load of the iron_SA_3_helix group was significantly higher than that of the polymer_SA group. The micro-CT analysis indicated the iron_SA_3_helix group showed a higher bone volume fraction (BV/TV) after surgery. Moreover, both iron SAs underwent degradation with time. Iron_SAs with triple-helical threads and a porous structure demonstrated better mechanical strength and high biocompatibility after short-term implantation. The combined advantages of the mechanical superiority of the iron metal and the possibility of absorption after implantation make the iron_SA a suitable candidate for further development.     

Study on aging of clay–rubber masterbatch from modified clay

Clay was modified by using a polymeric coating agent, a silicane coupling agent, and a titanate coupling agent together with the antioxidant for preparing the clay–rubber masterbatch. After the thermooxidative, photooxidative, and ozone aging, the properties of the masterbatch were also determined. The results indicate that, under the synergistic actions of the polymeric coating agent, antioxidant, and coupling agent, the thermooxidative and photooxidative aging resistances of the masterbatch were greatly improved. The properties of ozone aging resistance of the masterbatch can be increased by 50% under the combined action of a new kind of amine antioxidant with a titanate coupling agent. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 338–342, 2001     

基于生成对抗网络的雾霾场景图像转换算法

本文提出了一种新的基于生成对抗网络的雾霾场景图像转换算法.生成对抗网络GAN作为无监督学习的方法,无法实现图像像素与像素之间映射,即生成图像不可控.因此,基于模型的加雾算法存在参数不确定性和应用场景局限性,本文提出了一种新方法的新应用,利用生成对抗网络实现图像转换.该方法基于生成对抗网络GAN模型,改进了GAN的生成器和判别器,进行有监督学习,以训练雾霾图像生成像素与像素之间的映射关系,实现无雾图像与有雾图像之间的转换.以图像加雾为例,本文分别设计了生成网络和判决网络,生成网络用于合成有雾图像,判决网络用于辨别合成的雾霾图像的真伪.考虑到雾霾场景图像转换的对应效果,设计了一种快捷链接沙漏形生成器网络结构,采用无雾图像作为生成网络输入,并输出合成后的有雾霾图像;具体来看,将生成网络分成编码和解码两部分,并通过相加对应间隔的卷积层来保留图像的底层纹理信息.为了更好地检验合成雾霾图像的真实程度,设计了漏斗形全域卷积判决器网络,将合成图像和目标图像分别通过判决器辨别真伪,采用全域卷积,利用神经网络进行多层下采样,最终实现分类判决,辨别图像风格.此外,本文提出了一种新的网络损失函数,通过计算GAN损失和绝对值损失之和,以训练得到更为优秀的图像转换结果.GAN损失函数的作用是使生成对抗网络GAN模型训练更加准确,而雾霾图像合成算法实际上是一个回归问题而非分类问题,生成器的作用不仅是训练判决器更加灵敏,更重要的是要生成与目标图像相似的图像.因此利用优化回归问题的绝对值损失函数,作用是为了准确学习像素间的映射关系,避免出现偏差和失真.最后本文对多类不同图像进行图像的雾霾场景转换并进行评估,分别测试该算法的图像加雾和去雾效果,并与其他算法进行对比测试.对于加雾效果,在合成场景、虚拟场景下,与软件合成效果进行对比,本文算法效果明显比软件合成效果好,不会出现色彩失真;在真实场景下,本文算法与真实拍摄的雾霾天气进行对比,结果十分相近;并且与其他GAN图像转换算法进行对比,本文算法具有明显的优势.同样本文算法在去雾效果上优势也十分明显.结果表明,本文所提基于生成对抗网络的雾霾场景图像转换算法,在主观效果和客观指标上均具有明显优势.