Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics

Background:Traumatic brain injury can be caused by head impacts,but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo,and the characteristics of different types of impacts are not well studied.We investigated the spectral characteristics of different head impact types with kinematics classification.Methods:Data were analyzed from 3262 head impacts from lab reconstruction,American football,mixed martial arts,and publicly available car crash data.A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types(e.g.,football,car crash,mixed martial arts).To test the classifier robustness,another 271 lab-reconstructed impacts were obtained from 5 other instrumented mouthguards.Finally,with the classifier,type-specific,nearest-neighbor regression models were built for brain strain.Results:The classifier reached a median accuracy of 96% over 1000 random partitions of training and test sets.The most important features in the classification included both low-and high-frequency features,both linear acceleration features and angular velocity features.Different head impact types had different distributions of spectral densities in low-and high-frequency ranges(e.g.,the spectral densities of mixed martial arts impacts were higher in the high-frequency range than in the low-frequency range).The type-specific regression showed a generally higher R2value than baseline models without classification.Conclusion:The machine-learning-based classifier enables a better understanding of the impact kinematics spectral density in different sports,and it can be applied to evaluate the quality of impact-simulation systems and on-field data augmentation.

Versatile zeolite overlayer on ZnO film enabling high-performance bilayer NO_(2) sensoring

Bilayer structure with functional overlayer has been commonly adopted to resolve the issue of moisture poisoning in chemiresistors.However,the conventional overlayers always suffer from blocking access of gas molecules to sensing layer due to lacking porosity and deteriorated adsorption capability.Herein,taking advantages of the well-defined porous structure and hydrophobic nature of pure silica zeolite,we assembled an overlayer of Pd-PdO clusters-encapsulated mesoporous silicalite-1(MFI)zeolite(named M-S-1)on ZnO sensing layer,to prevent moisture poisoning,and enhance gas diffusion and adsorption capabilities.The inherent capability of MFI zeolite to incorporate monodispersed nanometric(ca.3 nm)Pd-PdO cluster in its void space is of great importance for the NO_(2) adsorption.The Pd-PdO@M-S-1 overlayer can attain negligible moisture interference to the ZnO layer without significantly altering the gas selectivity and baseline resistance,and enhance gas response.Consequently,the Pd-PdO@M-S-1/ZnO bilayer sensor can ultra-selectively(S_(nitrogen dioxide)/S_(interference gas)>4),and ultra-stably detect trace level of NO_(2)(9.5 ppb)at low temperature(370 K)under high levels of humidity(90%RH).This work exemplifies a next-generation solution to design bilayer sensors using zeolite overlayer for eliminating the humidity dependence of the gas-sensing properties.

Regulatable interfacial adhesion between stamp and ink for transfer printing

As an emerging processing technology,transfer printing enables the assembly of functional material arrays(called inks)on various substrates with micro/nanoscale resolution and has been widely used in the fabrication of flexible electronics and display systems.The critical steps in transfer printing are the ink pick-up and printing processes governed by the switching of adhesion states at the stamp/ink interface.In this review,we first introduce the history of transfer printing in terms of the transfer methods,transferred materials,and applications.Then,the fundamental characteristics of the transfer printing system and typical strategies for regulating the stamp/ink interfacial adhesion strength are summarized and exemplified.Finally,future challenges and opportunities for developing the novel stamps,inks,and substrates with intelligent adhesion capability are discussed,aiming to inspire the innovation in the design of transfer printing systems.

嫦娥五号月壤Rb-Sr同位素组成及其记录的复杂热改造过程

嫦娥五号月壤是迄今为止返回的最为年轻的月球样品,它为研究月球表面20亿年以来的改造历史提供了绝佳的机会.Rb-Sr同位素体系常被用作定年和示踪的工具,同时由于其放射性体系具有较低的封闭温度以及Rb具有较强的挥发性,该体系可以更好地记录月表的改造细节.本文报道了嫦娥五号返回月壤和玄武岩角砾的全岩Sr同位素以及凝结集块、岩屑和玄武质角砾的原位Sr同位素数据.斜长石具有较为均一的Sr同位素组成,代表了嫦娥五号玄武岩的初始Sr同位素在0.69971±0.0033(2SD,n=22).月壤、玄武岩岩屑和矿物晶屑的Rb-Sr同位素体系不同程度地偏离了20亿年等时线,作者认为这表明这些角砾记录了不同程度的热改造过程,可能与不同程度和不同阶段的Rb丢失有关.这些结果表明嫦娥五号月壤经历了复杂的元素挥发和热改造过程,月壤各组分具有不均一的Rb-Sr同位素组成,与嫦娥五号着陆区不同阶段的陨石撞击事件有关.

A novel method for simultaneous analysis of particle size and mineralogy for Chang’E-5 lunar soil with minimum sample consumption

The successful return of lunar soil samples from the northern Oceanus Procellarum by the Chang’E 5(CE-5) mission has provided unprecedented ground-truth information for the previously unexplored region of the Moon. In particular, the particle size and mineral constituents of the CE-5 soil samples are of critical importance to interpret remote sensing data. With a Raman-based particle analysis system, we show that the particle size properties and mineral constituents of the CE-5 soil can be simultaneously determined with a small sample size(ca. 30 μg). The CE-5 sample scooped from the lunar surface has an overall small size between 0.4 μm and 73.9 μm(mean=3.5 μm), and mainly consists of pyroxene(39.4%), plagioclase(37.5%), olivine(9.8%), Fe-Ti oxides(1.9%), glass(8.3%) and other minor or trace phases. The results are consistent with previous analyses with larger sample sizes. In addition to minimum sample consumption, this method requires very little sample preparation, and can rapidly build a large database with each particle precisely traceable. Therefore, this novel technique is particularly suitable for the analysis of future returned soil samples from extraterrestrial bodies.