A multilayer recognition model for twitter user geolocation

Wireless Networks - Geolocation is important for many emerging applications such as disaster management and recommendation system. In this paper, we propose a multilayer recognition model (MRM) to...     

Facial-sketch Synthesis: A New Challenge

Machine Intelligence Research - This paper aims to conduct a comprehensive study on facial-sketch synthesis (FSS). However, due to the high cost of obtaining hand-drawn sketch datasets, there is a...     

Synthesis and performance evaluation of a new drag reducer based on acrylamide/12-allyloxydodecyl acid sodium

Hydraulic fracturing with slickwater is a field-proven stimulation technology used in tight reservoirs. Because of the high pumping rate associated with slickwater fracturing, drag reduction (DR) is critical in minimizing pressure drop and the success of oilfield operations. In this paper, a new type of drag reducer (SPR) was synthesized with acrylamide and 12-allyloxydodecyl acid sodium, and its drag reduction performance was evaluated. The results showed that the new drag reducer features low molecular weight, fast-dissolving rate and low interfacial tension. The algorithm of estimating the drag reduction rate of non-Newtonian fluid SPR was proposed and validated. Empirical or semianalytical models for estimating the friction ratio (σ) or friction factor (λ or f) were used to simulate the turbulence behavior of the SPR drag reducer under different Reynolds numbers (Re). The modified Virk's correlation could accurately model the turbulent behavior of the SPR drag reducer. A unified calculation formula was established in this study for different pipe diameters.     

Influence of surfactants on rheological behaviors of polyacrylonitrile/dimethyl sulfoxide/silicon blending polymer solutions

KH550, KH560, CTAB, and F127 were adopted to modify silicon (Si) to improve the dispersity and stability of Si in the polyacrylonitrile/dimethyl sulfoxide (PAN/DMSO) polymer solutions. The influence of surfactants on rheological behaviors of PAN/DMSO/Si blending polymer solutions was investigated by an advanced solution and melt rotation rheometer. The homogeneity and stability were also studied. The results showed that the surfactants could change the viscosity dependence of blending polymer solutions on shear rate, temperature and storage time by increase the steric hindrance of Si. Among the four solutions, PAN/DMSO/Si blending polymer solution with F127 exhibited the lowest viscosity, activation energy and the smallest structural viscosity index and exhibited the trend close to the Newtonian fluids. Moreover, PAN/DMSO/Si blending polymer solution with F127 exhibited the best dispersity and stability, indicating its best physical properties and machinability.     

Solution-Synthesized Multifunctional Janus Nanotree Microswimmer

Synthetic active matters are perfect model systems for non-equilibrium thermodynamics and of great potential for novel biomedical and environmental applications. However, most applications are limited by the complicated and low-yield preparation, while a scalable synthesis for highly functional microswimmers is highly desired. In this paper, an all-solution synthesis method is developed where the gold-loaded titania-silica nanotree can be produced as a multi-functional self-propulsion microswimmer. By applying light, heat, and electric field, the Janus nanotree demonstrated multi-mode self-propulsion, including photochemical self-electrophoresis by UV and visible light radiation, thermophoresis by near-infrared light radiation, and induced-charge electrophoresis under AC electric field. Due to the scalable synthesis, the Janus nanotree is further demonstrated as a high-efficiency, low-cost, active adsorbent for water decontamination, where the toxic mercury ions can be reclaimed with enhanced efficiency.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Recent advances during CH4 dry reforming for syngas production: A mini review

Given the continuing issues of environment and energy, methane dry reforming for syngas production have sparked interest among researchers, but struggled with the process immaturity owing to catalyst deactivation. This review summarizes the recent advances in the development of efficient and stable catalysts with strong resistance to coking and metal sintering, including the application of novel materials, the assessment of advanced characterizations and the compatibility to improved reaction system. One feasible option is the crystalline oxide catalysts (perovskite, pyrochlore, spinel and LDHs), which feature a fine metal dispersion and surface confinement effect via a metal exsolution strategy and exhibit superior reactivity and stability. Some new materials (h-BN, clays and MOFs) also extend the option because of their unique morphology and microstructure. It also is elaborated that progresses were achieved in advanced characterizations application, leading to success in the establishment of reaction mechanisms and attributions to the formed robust catalysts. In addition, the perspective described the upgrade of reaction system to a higher reaction efficiency and milder reaction conditions. The combination of efficient reaction systems and robust catalysts paves a way for a scaling-up application of the process.     

Nanogrooved carbon microtubes for wet three‐dimensional printing of conductive composite structures

Recent advances in three‐dimensional (3D) printing have enabled the fabrication of interesting structures which are not achievable using traditional fabrication approaches. The 3D printing of carbon microtube composite inks allows fabrication of conductive structures for practical applications in soft robotics and tissue engineering. However, it is challenging to achieve 3D printed structures from solution‐based composite inks, which requires an additional process to solidify the ink. Here, we introduce a wet 3D printing technique which uses a coagulation bath to fabricate carbon microtube composite structures. We show that through a facile nanogrooving approach which introduces cavitation and channels on carbon microtubes, enhanced interfacial interactions with a chitosan polymer matrix are achieved. Consequently, the mechanical properties of the 3D printed composites improve when nanogrooved carbon microtubes are used, compared to untreated microtubes. We show that by carefully controlling the coagulation bath, extrusion pressure, printing distance and printed line distance, we can 3D print composite lattices which are composed of well‐defined and separated printed lines. The conductive composite 3D structures with highly customised design presented in this work provide a suitable platform for applications ranging from soft robotics to smart tissue engineering scaffolds. © 2019 Society of Chemical Industry     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.