Expert consensus on pediatric orthodontic therapies of malocclusions in children

Malocclusion,identified by the World Health Organization(WHO)as one of three major oral diseases,profoundly impacts the dental-maxillofacial functions,facial esthetics,and long-term development of~260 million children in China.Beyond its physical manifestations,malocclusion also significantly influences the psycho-social well-being of these children.Timely intervention in malocclusion can foster an environment conducive to dental-maxillofacial development and substantially decrease the incidence of malocclusion or reduce the severity and complexity of malocclusion in the permanent dentition,by mitigating the negative impact of abnormal environmental influences on the growth.Early orthodontic treatment encompasses accurate identification and treatment of dental and maxillofacial morphological and functional abnormalities during various stages of dental-maxillofacial development,ranging from fetal stages to the early permanent dentition phase.From an economic and societal standpoint,the urgency for effective early orthodontic treatments for malocclusions in childhood cannot be overstated,underlining its profound practical and social importance.This consensus paper discusses the characteristics and the detrimental effects of malocclusion in children,emphasizing critical need for early treatment.It elaborates on corresponding core principles and fundamental approaches in early orthodontics,proposing comprehensive guidance for preventive and interceptive orthodontic treatment,serving as a reference for clinicians engaged in early orthodontic treatment.

蛋白质组学研究方法在蚕丝学中的应用

家蚕既是具有重要经济价值的绢丝昆虫,又是现代生命科学研究的模式生物。近年来,随着蛋白质组学研究技术的飞速发展,有关家蚕性腺、丝腺、血液、中肠、触角等重要组织器官蛋白质组学的研究取得了很大进展,为揭示家蚕重要性状的形成机制、生殖发育调控、组织器官功能、天然免疫等方面提供了丰富的信息。文章对此作了简要的综述,并结合基因组学、生物信息学的研究技术,讨论了家蚕蛋白质组学今后的发展趋势及其应用前景。

Microstructures and interfacial interactions of Al_(2)O_(3)whiskers and graphene nano-platelets co-reinforced copper matrix composites

The mechanical properties and microstructures of Al_(2)O_(3)whiskers and graphene nano-platelets(GNPs)co-reinforced Cu-matrix composites were studied.Cu-matrix composites with a variation of GNPs amount were fabricated by mechanical alloying followed by vacuum hot-pressing sintering and hot isostatic pressing.The Cu-matrix composite with 0.5 wt.%GNPs(GNPs-0.5)suggests a good interfacial bonding of both Cu/C and Cu/Al_(2)O_(3)interfaces.Both the hardness and compressive strength of Cu-matrix composites show a consistent tendency that firstly increases to a critical value and then decreases with increasing GNPs amount.It is suggested that the most possible strengthening mechanisms of both GNPs and Al_(2)O_(3)whisker working in the Cu-matrix composites involve energy dissipating and load transfer,as well as grain refinements for GNPs.The synergetic effect of GNPs and Al_(2)O_(3)whiskers is highlighted that the embedded GNPs would hinder the crack path generated at the Al_(2)O_(3)/Cu interface and enhance the already outstanding strengthening effect that Al_(2)O_(3)whiskers provide.

A Novel S-Box GenerationMethodology Based on the Optimized GANModel

S-boxes can be the core component of block ciphers,and how to efficiently generate S-boxes with strong cryptographic properties appears to be an important task in the design of block ciphers.In this work,an optimized model based on the generative adversarial network(GAN)is proposed to generate 8-bit S-boxes.The central idea of this optimized model is to use loss function constraints for GAN.More specially,the Advanced Encryption Standard(AES)S-box is used to construct the sample dataset via the affine equivalence property.Then,three models are respectively built and cross-trained to generate 8-bit S-boxes based on three extended frameworks of GAN,i.e.,Deep Convolution Generative Adversarial Networks(DCGAN),Wasserstein Generative Adversarial Networks(WGAN),and WassersteinGenerativeAdversarial NetworkwithGradient Penalty(WGANGP).Besides,an optimized model based onWGAN-GP referred to asWGPIM is also proposed,which adds the loss function constraints to the generator network of the WGAN-GP model,including bijection loss,differential uniformity loss,and nonlinearity loss.In this case,8-bit S-boxes can be generated with cross-training.Experimental results illustrate that the WGP-IM model can generate S-boxes with excellent cryptographic properties.In particular,the optimal differential uniformity of the generated S-boxes can be reduced to 8,and the nonlinearity can be up to 104.Compared with previous S-box generation methods,this new method is simpler and it can generate S-boxes with excellent cryptographic properties.

飞行器结构布局与尺寸混合优化方法

针对飞行器结构轻量化设计中的布局和尺寸优化问题,提出了一种高效的混合优化方法。在传统的基结构优化方法中引入尺寸变量,构建结构布局与尺寸混合优化模型,并以遗传算法为基本搜索方法,设计了统一描述0-1型离散布局变量和连续尺寸变量的染色体,建立了结构布局与尺寸混合优化的求解流程。由于种群规模较大,在求解过程中引入了神经网络代理模型,通过预估种群个体的优劣,缩减每一代中需要精确计算的个体数目。以含有55个布局变量和55个尺寸变量的机翼结构优化问题作为算例,验证了该方法的可行性,优化结果相比传统基结构法减重13%,且引入代理模型可使计算成本降低约50%。