Short‐Fluorinated iCVD Coatings for Nonwetting Fabrics

Water repellency is often generated by taking advantage of surface textures and low surface energy coatings such as the one afforded by long perfluorinated side‐chains polymers. However, new regulations are phasing out these polymers because of their related health and safety hazard concerns. This is a particular challenge for water‐repellent fabrics as consumers expect safer products with stable performance and new functionalities. In this work, an approach is developed that allows for iCVD deposition of durable, conformal short fluorinated polymers stabilized with a crosslinking agent. As a result, high hydrophobicity and low liquid adhesion are achieved simultaneously while maintaining initial substrate breathability. It is explained why this polymeric coating—1H,1H‐perfluorooctyl methacrylate co divinylbenzene—exhibits remarkable hydrophobic properties amidst a wide range of other possible candidates. In order to further enhance the dynamic water repellency performance, the chemical treatment is combined with physical texturing—obtained through microsandblasting, a process particularly suitable for fabrics—thus making this combined approach a suitable candidate to meet the industrial needs. This work paves the way for the development of environmentally friendly, highly repellent coatings for large volume production and the application of roll‐to‐roll coating techniques, and multifunctionalization of fabrics and wearable devices.     

Trick the body trick the mind: avatar representation affects the perception of available action possibilities in virtual reality

Virtual Reality - In immersive Virtual Reality (VR), your brain can trick you into believing that your virtual hands are your real hands. Manipulating the representation of the body, namely the...     

Task selection in spatial crowdsourcing from worker’s perspective

With the progress of mobile devices and wireless broadband, a new eMarket platform, termed spatial crowdsourcing is emerging, which enables workers (aka crowd) to perform a set of spatial tasks (i.e., tasks related to a geographical location and time) posted by a requester. In this paper, we study a version of the spatial crowdsourcing problem in which the workers autonomously select their tasks, called the worker selected tasks (WST) mode. Towards this end, given a worker, and a set of tasks each of which is associated with a location and an expiration time, we aim to find a schedule for the worker that maximizes the number of performed tasks. We first prove that this problem is NP-hard. Subsequently, for small number of tasks, we propose two exact algorithms based on dynamic programming and branch-and-bound strategies. Since the exact algorithms cannot scale for large number of tasks and/or limited amount of resources on mobile platforms, we propose different approximation algorithms. Finally, to strike a compromise between efficiency and accuracy, we present a progressive algorithms. We conducted a thorough experimental evaluation with both real-world and synthetic data on desktop and mobile platforms to compare the performance and accuracy of our proposed approaches.     

Nanoparticle embedded chitosan film for agglomeration free TEM images

Transmission electron microscopy (TEM) is a very useful and commonly used microscopy technique, used especially for the characterization of nanoparticles. However, the identification of the magnetic nanoparticle could be thought problematic in TEM analysis, due to the fact that the magnetic nanoparticles are usually form aggregates on the TEM grid to form bigger particles generating higher stability. This prevents to see exact shape and size of each nanoparticle. In order to overcome this problem, a simple process for the formation of well‐dispersed nanoparticles was conducted, by covering chitosan film on the unmodified copper grid, it was said to result in aggregation‐free TEM images. It is also important to fix the magnetic nanoparticles on the TEM grids, due to possible contamination of TEM filament which is operated under high vacuum conditions. The chitosan film matrix also helps to protect the TEM filament from contact with magnetic nanoparticles during the imaging process. The proposed procedure offers a quick method to fix the nanoparticles in a conventional copper TEM grid and chitosan matrix prevents agglomeration of nanoparticles, and thus getting TEM images showing well‐dispersed individual nanoparticles.     

Fabrication of a novel polyhedral oligomeric silsesquioxanes/polyether‐block‐amide nano‐hybrid membrane for pervaporative separation of model fuel butanol

The present study reports the pervaporative separation capability of the pristine and polyhedral oligomeric silsesquioxanes (POSS) loaded hybrid polyether‐block ‐amide (PEBA) membranes for n ‐butanol recovery from the dilute n ‐butanol–water mixtures. It is the first study to produce POSS‐loaded PEBA membranes for n ‐butanol recovery. The morphology and crosslinking structure of the pristine and hybrid membrane were characterized by scanning electron microscopy and Fourier transform infrared spectroscopy. The thermal stability and crystallization behaviors of the pristine and hybrid membranes were investigated using thermogravimetric analysis and differential scanning calorimetry methods. Swelling experiments were also done to determine the affinity of the membranes to the n ‐butanol–water mixture. The effect of increasing amount of POSS on pervaporation performance was investigated in terms of flux and the n ‐butanol separation factor at 40 °C and a given n ‐butanol. All the hybrid membranes exhibited high flux and n ‐butanol separation factor than that of the pristine PEBA membrane. The best n ‐butanol separation factor of 27.2 was obtained accompanied with 1.33 Kg m^?2 h^?1 of flux, when the POSS amount was 4 wt %. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 45211.     

Particle swarm optimization for bitmap join indexes selection problem in data warehouses

Data warehouses are very large databases usually designed using the star schema. Queries defined on data warehouses are generally complex due to join operations involved. The performance of star schema queries in data warehouses is highly critical and its optimization is hard in general. Several query performance optimization methods exist, such as indexes and table partitioning. In this paper, we propose a new approach based on binary particle swarm optimization for solving the bitmap join index selection problem in data warehouses. This approach selects the optimal set of bitmap join indexes based on a mathematical cost model. Several experiments are performed to demonstrate the effectiveness of the proposed method on the bitmap join index selection problem. Further testing of the method is performed using a database environment specific cost function. The binary particle swarm optimization is found to be more effective than both the genetic algorithm and data mining based approaches.     

Eudragit S (methyl methacrylate methacrylic acid copolymer)/fatty acid blends as form‐stable phase change material for latent heat thermal energy storage

By composing (Eudragit S) with fatty acids (stearic acid (SA), palmitic acid (PA), and myristic acid (MA)), form‐stable phase change materials (PCMs), which can retain the same shape in a solid state even when the temperature of the PCMs is over the melting points of the fatty acids, are prepared. The compatibility of fatty acids with the Eudragit S is proved by microscopic investigation and infrared (FTIR) spectroscopy. The melting and crystallization temperatures and the latent heats of melting and crystallization of the form‐stable PCMs are measured by Differential Scanning Calorimetry (DSC) method. The maximum mass percentage of all fatty acids in the form‐stable PCMs is found as 70%, and no leakage of fatty acid is observed at the temperature range of 50–70°C for several heating cycles. Thermal properties obtained from the DSC analysis indicate that the Eudragit S/fatty acid blends as form‐stable PCM have great potential for passive solar latent heat thermal energy storage (LHTES) applications in terms of their satisfactory thermal properties and utility advantage. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 1402–1406, 2006     

Two-phase transport and the role of micro-porous layer in polymer electrolyte fuel cells

Two-phase transport of reactants and products constitutes an important limit in performance of polymer electrolyte fuel cells (PEFC). Particularly, at high current densities and/or low gas flow rates, product water condenses in open pores of the cathode gas diffusion layer (GDL) and limits the effective oxygen transport to the active catalyst sites. Furthermore, liquid water covers some of the active catalytic surface, rendering them inactive for electrochemical reaction. Traditionally, these two-phase transport processes in the GDL are modeled using so-called unsaturated flow theory (UFT), in which a uniform gas-phase pressure is assumed across the entire porous layer, thereby ignoring the gas-phase flow counter to capillarity-induced liquid motion. In this work, using multi-phase mixture (M²) formalism, the constant gas pressure assumption is relaxed and the effects of counter gas-flow are studied and found to be a new oxygen transport mechanism. Further, we analyze the multi-layer diffusion media, composed of two or more layers of porous materials having different pore sizes and/or wetting characteristics. Particularly, the effects of porosity, thickness and wettability of a micro-porous layer (MPL) on the two-phase transport in PEFC are elucidated.     

Goal emulation and planning in perceptual space using learned affordances

In this paper, we show that through self-interaction and self-observation, an anthropomorphic robot equipped with a range camera can learn object affordances and use this knowledge for planning. In the first step of learning, the robot discovers commonalities in its action-effect experiences by discovering effect categories. Once the effect categories are discovered, in the second step, affordance predictors for each behavior are obtained by learning the mapping from the object features to the effect categories. After learning, the robot can make plans to achieve desired goals, emulate end states of demonstrated actions, monitor the plan execution and take corrective actions using the perceptual structures employed or discovered during learning. We argue that the learning system proposed shares crucial elements with the development of infants of 7–10 months age, who explore the environment and learn the dynamics of the objects through goal-free exploration. In addition, we discuss goal emulation and planning in relation to older infants with no symbolic inference capability and non-linguistic animals which utilize object affordances to make action plans.