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Background: Single measures of self-reported nighttime sleep duration and daytime napping duration are associated with adverse health outcomes; However, the association between longitudinal patterns of self-reported nighttime sleep duration and daytime napping duration and multimorbidity remains unclear. We therefore undertook cox regression analyses to explore linkages between sleep trajectories and multimorbidity.Methods: The current study included 5262 participants from China Health and Retirement Longitudinal Study. Self-reported nighttime sleep duration and daytime napping duration were collected from 2011 to 2015. The 4-year sleep duration trajectories were conducted by group-based trajectory modelling. The fourteen medical conditions were diagnosed by self-reported physicians or identified by combining health assessment and medication data. Multimorbidity was diagnosed as Participants with two or more of the 14 chronic diseases after 2015. Associations between sleep trajectories and multimorbidity were assessed by cox regression models.Results: During 6.69 years of follow-up, we observed multimorbidity in 785 participants. Four nighttime sleep duration trajectories and three daytime napping duration trajectories were identified. Participants with persistent short nighttime sleep duration trajectory had the higher risk of multimorbidity (Hazard ratio (HR)=1.24, 95% confidence interval (CI): 1.04-1.49), compared with those with persistent normal nighttime sleep duration trajectory. We have not found a benefit of daytime napping on the development of multimorbidity. Participants with persistent normal nighttime sleep duration and persistent seldom daytime napping duration had a lower risk of multimorbidity.Conclusions: In this study, persistent short nighttime sleep duration trajectory was associated with subsequent multimorbidity risk. Daytime napping cannot fully compensate for the risk of insufficient night sleep.

Cold spray is an attractive and rapidly developing process for additive manufacturing with high efficiency and precision, repairing and coating, especially in aircraft and aerospace applications. Cold spray additive manufacturing deposits micro-particles with large plastic deformation below their melting point, eliminating heat effect zone which could deteriorate the quality of repairing zone. The particle deposition in cold spray is a complex process which involves high strain rate, high contact pressure and high temperature. Here we develop, utilize and validate a thermo-mechanical model to provide a definitive way to predict deposition mechanics and surface deformation evolution for particle deposition process in cold spray additive manufacturing. Both a single particle and dual particles models were developed to investigate the contact interaction between particle/substrate and particle/particle. Different combinations of particle/substrate materials (Cu/Cu, Al/Al, steel/steel, and nickel/nickel) and process parameters were considered in this study. The experimental study was conducted to validate simulation results, providing useful information for understanding the limitations and challenges associated with cold spray additive manufacturing. The framework provides insights into improving the quality and precision of stress/strain formation, particle interactions and particle deposition in cold spray additive manufacturing process.

Up to now, micro milling has been recognized as the most promising technique to mitigate the surface damage of large-aperture KDP crystal used in laser fusion facility. However, there are quantities of damages on the surface of large-aperture KDP crystal to be mitigated. Furthermore, the efficiency and accuracy of manual tool setting is relatively low, and it is easy to damage KDP crystal surface due to mis-operation. Therefore, an automatic tool setting technology for KDP crystal surface damage mitigation based on machine vision is proposed in this research. The automatic tool setting includes fast pre tool setting achieved by image ranging and final tool setting achieved by micro-chip detection. In the process of fast pre tool setting, real-time image of the micro milling cutter is obtained, and the distance between the tool tip and the KDP crystal surface is obtained by image ranging. Finally, the tool tip is quickly positioned 20 μm away from the KDP crystal surface. In the process of final tool setting, the micro milling cutter is retreated to a distance of about 50 μm away from the KDP crystal surface before detecting micro-chips. Therefore, the micro-chips covered by the micro milling cutter will be exposed and appear in the view field of microscope, so as to improve the micro-chip recognition rate. The results showed that the total time of automatic tool setting is 130 s, and the accuracy of automatic tool setting is better than 1.359 μm. Compared with manual tool setting, the automatic tool setting based on machine vision proposed in this research improves the safety, efficiency, and accuracy of independently developed mitigation system for KDP crystal surface damage.

For quantum-dot light-emitting diodes (QD-LED), replacing Cd-based II-VI nanocrystals (NCs) with the Cu-In-Zn-VI counterparts combines the consideration of environmental benignity and device performance. To prove this concept, the chemical composition and nanostructures of Cu-In-Zn-VI nanocrystals need to be thoroughly explored aiming to competitive optoelectronic properties. Herein, we reported a detailed study of Cu–In–Zn–Se–S synthesis and demonstrated how the optical bandgap, emission full width at half-maximum (FWHM) and the performance of QD-LED were tuned by simply changing the dose of precursors in a non-injection synthesis. Evident by optical absorption, the optimization of Se and Cu doses enabled good dispersity and desired emission wavelength. Further analysis of photo-electron spectroscopy revealed the chemical composition from core to surface favored soft confinement of exciton by gradually increasing the loading of Zn element. Finally, we successfully demonstrated solution-processed QD-LEDs with the best external quantum efficiencies as high as 4.2% and emission wavelength centering at 663 nm. To our best knowledge, this is the most efficient solution-processed red QD-LED based on Cu-In-Zn-VI nanocrystals.

Autophagic dysfunction related cascade events might induce the accumulation of α-synuclein (αSyn) in Parkinson's disease (PD). Triptolide (T

The adherent behaviors of hydroxyl-terminated polybutadiene (HTPB), a typical high viscosity liquid widely used as a binder in rocket motor propellants, onto the copper (Cu) surfaces with/without the interference of Al nanoparticles were investigated by classical molecular dynamics (MD) simulations. The results indicate that HTPB molecules adsorbed directly onto Cu(001) surface exhibit the tendency to distribute parallel to the 〈110〉 crystal direction family as a result of tense atom arrangement along the close-packed crystal directions. The dynamic hydrogen-bonded network, formed by inter-/intra-molecular interactions among neighbouring hydroxyl groups, is also suggested to exert strong influence on the distribution of HTPB molecules. Moreover, Al nanoparticles have been proved to be readily enveloped by HTPB chains when placed close to the pure high viscosity liquid, which will in turn restrict the mobility of HTPB molecules, eventually resulting in the decrease of wettability of HTPB droplet on Cu surface. The flow slip behavior of HTPB liquid on Cu surface, regardless of the presence of Al nanoparticles, was tested and directly compared by confined shear simulations. The Al hemispheres, acting as convex obstacles on the flat surface, seem to be capable of suppressing the slippage of chain-like HTPB molecules, which will be easily entangled by local protrusions. Therefore, it can be inferred that the flow behavior and interfacial wettability of high viscosity liquid will be largely influenced by the discontinuous solid-phase particles dispersed in it.

Mutual dependence and shared geographic distributions of ectomycorrhizal fungi and their hosts suggest that comigration has had an influential role in the evolution of the ectomycorrhizal symbiosis. To test the hypothesis of comigration of ectomycorrhizal symbionts we conducted a phylogeographic analysis of host specific ectomycorrhizal fungi in genus Rhizopogon sampled throughout the natural range of their Pseudotsuga (Douglas fir) hosts. Low coverage genome assemblies were sequenced for all Rhizopogon species-level clades and a novel data mining method, genome-scale sequence typing, was developed to produce a genome-scale phylogenetic dataset. Phylogenetic and phylogeographic analyses support a single evolutionary origin of the Rhizopogon-Pseudotsuga ectomycorrhizal symbiosis in coastal western North America with a single migration into Asia and two independent migrations east into the North American Intermountain West. Our results suggest that the Rhizopogon-Pseudotsuga ectomycorrhizal symbiosis predates species radiation in Pseudotsuga and that these genera have undergone processes of comigration and codiversification.

Wetting test and classical molecular dynamics (MD) simulations were employed to investigate the adherent behaviors of hydroxyl-terminated polybutadiene (HTPB), a typical high viscosity liquid widely used as a binder in rocket motor propellants, onto the copper (Cu) surfaces with different topographies. Experimental data show that the microstructures protruding above the substrate surfaces can be ‘sensed’ by the HTPB droplet, which has been indicated by the smaller contact angles and higher interface tension for this specific liquid on the rough surfaces (featured with sinusoidal structures or square pillars) than that on the smooth surface. Simulation results reveal the atomic details of spreading process of HTPB chains, with diverse diffusion propensities presented on different surfaces. The HTPB droplet spreads widely on the smooth surface, exhibiting a roughly isotropic trend. On the contrary, the state of this high viscosity liquid on the sinusoidal-structured surface is featured by wide contact diffusion along the run of groove, but relatively restricted extension in the direction perpendicular to the groove, as a result of the barriers exerted by the nearest neighbouring peaks. The existence of nanoscale pillars increases the exterior surface area of Cu substrate, therefore the HTPB chains can penetrate deep to envelop the peripheries of the pillars, forming abundant direct contacts with Cu surface and producing a highest HTPB–Cu interaction energy, which well accords with the experimental results about the adherent strength of HTPB.

In this work, a special grinding machine tool using a small ball-end grinding wheel is designed to achieve ultra-precision grinding of complex components with small concave surfaces. A comprehensive error propagation model is established, considering kinematic errors, setup errors and structure parameters. Sensitivity analysis is performed by the Sobol' method to quantify the relationship between the errors, structure parameters and geometric accuracy of the machine tool. On this basis, error allocation is carried out, and the inclination angle of the grinding wheel spindle and the working range of the C-axis are optimized to reduce the influence of the setup errors on machining accuracy. Then, the predicted geometric accuracy of the machine is 0.3 μm, contributing only to half of the profile accuracy requirement for peak-to-valley PV