An improved Henry gas solubility optimization for optimization tasks

Applied Intelligence - The henry gas solubility optimization (HGSO) is a new nature-inspired algorithm that mimics Henry Gas Solubility to solve global optimization problems. The main changes of...     

Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors

All‐solution processed, high‐performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal–insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC‐based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC‐based and solution‐processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low‐cost and high‐performance electronic skin or wearable devices.     

In-situ synthesis of TiO2 nanostructures on Ti foil for enhanced and stable photocatalytic performance

TiO_2 nanostructures with strong interfacial adhesion and diverse morphologies have been in-situ grown on Ti foil substrate through a multiple-step method based on conventional plasma electrolytic oxidation(PEO) technology, hydrothermal reaction and ion exchange process. The PEO process is critical to the formation of TiO_2 seeding layer for the nucleation of Na_2Ti_3O_7 and H_2Ti_3O_7 mediates that are strongly attached to the Ti foil. An ion exchange reaction can finally lead to the formation of H_2Ti_3O_7 nanostructures with diverse morphologies and the calcination process can turn the H_2Ti_3O_7 nanostructures into TiO_2 nanostructures with enhanced crystallinity. The morphology of the TiO_2 nanostructures including nanoparticles(NP), nanowhiskers(NWK), nanowires(NW) and nanosheets(NS) can be easily tailored by controlling the NaOH concentration and reaction time during hydrothermal process. The morphology, composition and optical properties of TiO_2 photocatalysts were analyzed using scanning electron microscope(SEM), X-ray diffraction(XRD), photoluminescence(PL) spectroscopy and UV–vis absorption spectrum. Photocatalytic tests indicate that the TiO_2 nanosheets calcined at 500?C show good crystallization and the best capability of decomposing organic pollutants. The decoration of Ag cocatalyst can further improve the photocatalytic performance of the TiO_2 nanosheets as a result of the enhanced charger separation efficiency. Cyclic photocatalytic test using TiO_2 nanostructures grown on Ti foil substrate demonstrates the superior stability in the photodegradation of organic pollutant, suggesting the promising potential of in-situ growth technology for industrial application.     

Property-microstructure correlation in in situ formed Al2O3, TiB2 and Al3Ti mixture-reinforced aluminium composites

The in situ formed Al₂O₃, TiB₂ and Al₃Ti mixture-reinforced aluminium composites were successfully fabricated by the reaction sintering of the TiO₂-B-Al system in a vacuum. With increasing boron content in the TiO₂-B-Al system, the amount of generated TiB₂ in the composites increased and Al₃Ti content decreased. At the same time the distribution uniformity of the in situ formed Al₂O₃ and TiB₂ particulates was obviously improved, and the size of the Al₃Ti particles was reduced. The in situ Al₂O₃ and TiB₂ particulates had sizes from 0.096–1.88 m. The interface between the in situ formed particulates and the aluminium matrix was clean, and no consistent crystallographic orientation relationship was found. The strength and elastic modulus of the composites was significantly improved by lowering the Al₃Ti content. When the boron content in the TiO₂-B-Al system rose, the morphology of the tensile fracture surface of the composites was changed from large fractured Al₃Ti blocks and fine dimples, to fine dimples and pulled-out particulates. The strengthening and fracture of the composites have been modelled.     

基于蚁群算法的网格资源发现模型研究

本文通过对传统的网格资源发现存在的问题进行分析,针对其不足,引入蚁群算法,提出基于蚁群算法的网格资源发现模型（AA_GRRM）,设计并分析AA_GRRM的体系结构,并对其关键模块分析设计,以提高网格资源发现效率。     

Using jump-diffusion modeling for valuing real options in infrastructure projects

In infrastructure financed projects, in order to attract private investors, host governments often provide some guarantees. This paper develops a value model of minimum revenue guarantee with multiple-exercise real options under the impact of the emergency incident. The model is applied to infrastructure financed projects using the minimum revenue guarantee under simulation. The simulation results indicate that, before quantifying the value of the minimum revenue guarantee, it is necessary to forecast the jump degree and intensity of the emergency incident, as well as prevent and control risks arising from such emergencies. Otherwise, underestimation of the guarantee value will occur and the government will have to bear huge debt in this condition. We also analyze the dependence of the guaranteed value on the minimum guaranteed revenue level, initial revenue and number of exercise rights. For various conditions, the diagrams of the guaranteed value are also presented.     

A new phase unwrapping method based on region recognition and region expansion

Phase unwrapping is a key step in retrieving digital elevation models (DEMs) from across-track interferometric synthetic aperture radar (InSAR) data. The coherence of synthetic aperture radar (SAR) data set is an effective indicator for the quality of phase unwrapping. However, the coherence of different regions usually distributes unevenly in SAR images monitoring heterogeneous areas. Errors in low-coherence areas are prone to pollute the whole image. In order to mitigate propagation error, a new phase unwrapping algorithm based on region recognition and region expansion is proposed. In the region recognition step, optical images are incorporated to recognize low-coherence regions by virtue of supervised classification technique. Low-coherence regions and the ones that are not of interest for the application are then discarded. In the region expansion step, stable pixels of high coherence are selected as growing seeds, and then phase unwrapping grows from high-quality regions to low-quality ones guided by coherence information and weighted numbers of neighbouring unwrapped pixels. The ambiguity number of a wrapped pixel is estimated from its neighbouring pixels under the criteria of pixel distance and phase gradient. Iterative examination continues until the whole image is unwrapped. Experiments on PALSAR and ASAR data demonstrate its validity and advantages over other classical methods.     

Neuroproteomics and its applications in research on nicotine and other drugs of abuse

The rapidly growing field of neuroproteomics is able to track changes in protein expression and protein modifications underlying various physiological conditions, including the neural diseases related to drug addiction. Thus, it presents great promise in characterizing protein function, biochemical pathways, and networks to understand the mechanisms underlying drug dependence. In this article, we first provide an overview of proteomics technologies and bioinformatics tools available to analyze proteomics data. Then we summarize the recent applications of proteomics to profile the protein expression pattern in animal or human brain tissues after the administration of nicotine, alcohol, amphetamine, butorphanol, cocaine, and morphine. By comparing the protein expression profiles in response to chronic nicotine exposure with those appearing in response to treatment with other drugs of abuse, we identified three biological processes that appears to be regulated by multiple drugs of abuse: energy metabolism, oxidative stress response, and protein degradation and modification. Such similarity indicates that despite the obvious differences among their chemical properties and the receptors with which they interact, different substances of abuse may cause some similar changes in cellular activities and biological processes in neurons.     

多层次弹性养老保障制度探讨

建立多层次弹性养老保障制度可以分散和降低人口老龄化带来的养老风险。针对我国社会养老保险制度所面临的严峻的人口老龄化挑战,分析了现行社会养老保险制度的缺陷;提出了包括一个救助层、两个强制层、一个补充层和一个自助层的五层次弹性养老保障制度模型。     

Spectral Method for Thermal Conductivity Calculations

We discuss several post-processing issues in molecular dynamics (MD) calculation of lattice thermal conductivity using the Green–Kubo formula. For crystals with high thermal conductivity such as SiC, converting the MD raw data on heat current fluctuations into thermal conductivity result is non-trivial. One can accelerate the process using Fast Fourier Transform and the spectral method. A few mathematical subtleties are cleared up. Due to finite data length, integration of the correlation function must be terminated before noise takes over; two termination criteria are proposed which give reasonable results for crystalline β-SiC. A simple solvable model that illustrates the above points and can be used for code-checking is presented.