Measurement error models with zero inflation and multiple sources of zeros, with applications to hard zeros.

We consider measurement error models for two variables observed repeatedly and subject to measurement error. One variable is continuous, while the other variable is a mixture of continuous and zero measurements. This second variable has two sources of zeros. The first source is episodic zeros, wherein some of the measurements for an individual may be zero and others positive. The second source is hard zeros, i.e., some individuals will always report zero. An example is the consumption of alcohol from alcoholic beverages: some individuals consume alcoholic beverages episodically, while others never consume alcoholic beverages. However, with a small number of repeat measurements from individuals, it is not possible to determine those who are episodic zeros and those who are hard zeros. We develop a new measurement error model for this problem, and use Bayesian methods to fit it. Simulations and data analyses are used to illustrate our methods. Extensions to parametric models and survival analysis are discussed briefly.

Stab-Resistant Performance of the Well-Engineered Soft Body Armor Materials Using Shear Thickening Fluid.

Stab-resistant body armor can effectively prevent sharp instruments from attacking the protected parts and reduce the threat to human bodies. Shear thickening fluid (STF) is a kind of smart material with variable viscosity and its viscosity can change significantly with external stimuli. The soft and adaptive characteristics of STF provide a new idea for improving the performance of stab-proof materials. In this work, three kinds of soft anti-stabbing materials were designed and prepared with aramid, poly-p-phenylene benzodioxazole (PBO), and carbon fiber fabrics impregnated with STF. Quasi-static puncture tests and dynamic impact tests were conducted to compare the performance of different anti-stabbing structures. The results showed that the peak piercing force of the STF-treated fabrics in the puncture testing was greatly increased than that of neat samples. Against the D2 knife, the maximum impact load of STF/PBO fiber fabric was increased from 55.8 N to 72.9 N, increasing by 30.6%. Against the D3 spike, the maximum impact load of STF/aramid fabric was increased from 128.9 N to 254.7 N, increasing by 197.6%. The mechanical properties of fibers were important factors for the resistance to knives, and the fabric structure was the key point to bear the spike. Optical photographs of fabric fractures and scanning electron microscope analysis indicated that the STF effectively limited the slip of the fiber bundle when the tool penetrated the fabric, which played a positive role in maintaining the tightness and integrity of the fabric structure.

A Biomimetic Basalt Fiber/Epoxy Helical Composite Spring with Hierarchical Triple-Helix Structures Inspired by the Collagen Fibers in Compact Bone.

The lightweight property of helical composite spring (HCS) applied in the transportation field has attracted more and more attention recently. However, it is difficult to maintain stiffness and fatigue resistance at the same time. Herein, inspired by collagen fibers in bone, a bionic basalt fiber/epoxy resin helical composite spring is manufactured. The collagen fibers consist of nanoscale hydroxyapatite (increases stiffness) and collagen molecules composed of helical amino acid chains (can increase fatigue resistance). Such a helical structure of intercalated crystals ensures that bone has good resistance to fracture. Specifically, we first investigated the effect of adding different contents of NS to basalt fibers on the stiffness and fatigue properties of an HCS. The results show that the optimal NS content of 0.4 wt% resulted in 52.1% and 43.5% higher stiffness and fatigue properties of an HCS than those without NS, respectively. Then, two braided fiber bundles (TS-BFB) and four braided fiber bundles (FS-BFB) were designed based on the helical structure of amino acid chains, and the compression tests revealed that the maximum load resistance of TS-BFB and FS-BFB was increased by 29.2% and 44%, respectively, compared with the conventional single fiber bundle (U-BFB). The superior mechanical performance of TS-BFB and FS-BFB is attributed to the more adequate bonding of 0.4 wt% NS to the epoxy resin and the multi-fiber bundles that increase the transverse fiber content of the spring. The findings in this work introduce the bionic collagen fiber structure into the design for an HCS and provide a new idea to improve the spring performance.

Wetting state transition of a liquid gallium drop at the nanoscale.

Wetting state transition regulated by surface roughness has increasing importance for its wide applications. Molecular dynamics simulations have been performed to study the wetting state transition induced by surface roughness in the gallium-carbon system. There is a transition from the Wenzel state to the Cassie state when the roughness is changed. When the surface roughness is more than 1.8, the gallium droplet is in a Cassie state, but when it is less than 1.6, it is in the Wenzel state. The substrate composed of irregular pillars has a similar effect on the wetting state transition. Besides, distinctive variations occur in the interface tension, the mean-squared displacement, the wetted surface and the interaction energy as the wetting state changes, which are further explained by the proposed model. This study would provide significant guidance for designing superhydrophobic surfaces in the future.

Single-Molecule Detection of Acetylcholine by Translating the Neuronal Signal to a Single Distinct Electronic Peak.

The bioelectric signal deriving from acetylcholine (ACh) plays an important role in regulating body function. Translating neuronal signals to electrical current peaks is a promising approach to achieve rapid detection of the bioelectric signal, but direct nanodevice-based single-molecule detection of the neurotransmitter is hampered by technology. Herein, we propose a neurotransmitter molecular nanogap device composed of atomically thin black phosphorus (BP) electrodes, which could rapidly distinguish the single distinct electronic peak of ACh at low positive bias from other central neurotransmitters. It is the first time that this unique electronic signal has been found, which originates from its quaternary ammonium group, and it has been experimentally verified in the linear sweep voltammetry (LSV) curves measured at 0.3 mV s-1 in 0.01 M acetycholine chloride aqueous solution. Furthermore, our results suggest that replacing the N atom with a P atom can not only reverse the current signal but also change the signal magnitude in ACh or choline nanoelectronic devices. Importantly, all these appealing properties can even be assembled as components to make these molecules into parallel heterojunctions, making them a promising candidate for applications in forward or backward rectifying diodes. These results provide a theoretical basis for the creative applications of a BP electrode-based nanogap device in the rapid and single-molecule level detection of ACh, an electrochemical understanding for the mechanism of the signal transmission between neurons, and a physical approach to controlling the complex biological signal transduction in organisms. Ultimately, our findings lay the basis for next-generation biomedical solutions to clinical problems in the neurologic field.

Moment reconstruction and moment-adjusted imputation when exposure is generated by a complex, nonlinear random effects modeling process.

For the classical, homoscedastic measurement error model, moment reconstruction (Freedman et al., 2004, 2008) and moment-adjusted imputation (Thomas et al., 2011) are appealing, computationally simple imputation-like methods for general model fitting. Like classical regression calibration, the idea is to replace the unobserved variable subject to measurement error with a proxy that can be used in a variety of analyses. Moment reconstruction and moment-adjusted imputation differ from regression calibration in that they attempt to match multiple features of the latent variable, and also to match some of the latent variable's relationships with the response and additional covariates. In this note, we consider a problem where true exposure is generated by a complex, nonlinear random effects modeling process, and develop analogues of moment reconstruction and moment-adjusted imputation for this case. This general model includes classical measurement errors, Berkson measurement errors, mixtures of Berkson and classical errors and problems that are not measurement error problems, but also cases where the data-generating process for true exposure is a complex, nonlinear random effects modeling process. The methods are illustrated using the National Institutes of Health-AARP Diet and Health Study where the latent variable is a dietary pattern score called the Healthy Eating Index-2005. We also show how our general model includes methods used in radiation epidemiology as a special case. Simulations are used to illustrate the methods.