Hybrid intelligent framework for one-day ahead wind speed forecasting

Neural Computing and Applications - Nowadays wind power is considered as one of the fastest growing alternative energies, that is expected to continue to grow rapidly in the upcoming...     

Object segmentation and labeling by learning from examples

We propose a system that employs low-level image segmentation followed by color and two-dimensional (2-D) shape matching to automatically group those low-level segments into objects based on their similarity to a set of example object templates presented by the user. A hierarchical content tree data structure is used for each database image to store matching combinations of low-level regions as objects. The system automatically initializes the content tree with only "elementary nodes" representing homogeneous low-level regions. The "learning" phase refers to labeling of combinations of low-level regions that have resulted in successful color and/or 2-D shape matches with the example template(s). These combinations are labeled as "object nodes" in the hierarchical content tree. Once learning is performed, the speed of second-time retrieval of learned objects in the database increases significantly. The learning step can be performed off-line provided that example objects are given in the form of user interest profiles. Experimental results are presented to demonstrate the effectiveness of the proposed system with hierarchical content tree representation and learning by color and 2-D shape matching on collections of car and face images.     

Binders for jute-reinforced unsaturated polyester resin

Reinforcement of polyester resin with jute cloth under constant load is studied, The pretreatment of jute cloth with tetrahydrofuran and the effect of binding properties of poly(vinyl acetate) and acrylic acid and their effect on the impact, tensile, and water absorptions of jute cloth polyester composites are reported and their chemical reactions are discussed.     

On an evolutionary approach for constrained optimization problem solving

Over the last few decades, many different evolutionary algorithms have been introduced for solving constrained optimization problems. However, due to the variability of problem characteristics, no single algorithm performs consistently over a range of problems. In this paper, instead of introducing another such algorithm, we propose an evolutionary framework that utilizes existing knowledge to make logical changes for better performance. The algorithmic aspects considered here are: the way of using search operators, dealing with feasibility, setting parameters, and refining solutions. The combined impact of such modifications is significant as has been shown by solving two sets of test problems: (i) a set of 24 test problems that were used for the CEC2006 constrained optimization competition and (ii) a second set of 36 test instances introduced for the CEC2010 constrained optimization competition. The results demonstrate that the proposed algorithm shows better performance in comparison to the state-of-the-art algorithms.     

AES and XPS study on the tarnishing of silver in alkaline sulphide solutions

Auger electron spectroscopy (AES) and X-ray photoelectron spectroscopy (XPS) were used to follow the changes that occur on the surfaces of silver sheets when reacting with sulphide solutions of pH 12. The results obtained enabled conclusions to be drawn about the nature of the Ag₂S films. Immersion in dilute sulphide solutions ( 3 × 10^–4 M) resulted in highly irregular films that were interrupted by shallow depressions (cavities). Inside these cavities AES analysis proved the existence of massive carbon species, the presence of which delayed healing of the cavities by the formation of Ag₂S film, thus allowing the silver metal interface to continue in contact with the solution oxygen. This explains why silver electrodes maintain the Ag/Ag₂O potential while immersed in dilute sulphide solutions. Equilibration of silver with more concentrated sulphide solutions (5 × 10^–4 to 5 × 10^–3 M) effected healing of the cavities through the formation of a continuous Ag₂S film. Once this continuous film is formed, the metal interface is no longer accessible to the solution oxygen. At this point the transition of potential from Ag/Ag₂O to Ag/Ag₂S occurs.     

Analytical Modeling of Short-Channel Fully-Depleted Triple Work Function Metal Gate (TWFMG) SOI MESFET

Silicon - In this paper, a new structure: triple work function metal gate SOI MESFET, intended for integration into the deep-submicron CMOS technology, is proposed. The gate of the device consists...     

An Engineered sgsh Mutant Zebrafish Recapitulates Molecular and Behavioural Pathobiology of Sanfilippo Syndrome A/MPS IIIA

Mucopolysaccharidosis IIIA (MPS IIIA, Sanfilippo syndrome type A), a paediatric neurological lysosomal storage disease, is caused by impaired function of the enzyme N-sulfoglucosamine sulfohydrolase (SGSH) resulting in impaired catabolism of heparan sulfate glycosaminoglycan (HS GAG) and its accumulation in tissues. MPS IIIA represents a significant proportion of childhood dementias. This condition generally leads to patient death in the teenage years, yet no effective therapy exists for MPS IIIA and a complete understanding of the mechanisms of MPS IIIA pathogenesis is lacking. Here, we employ targeted CRISPR/Cas9 mutagenesis to generate a model of MPS IIIA in the zebrafish, a model organism with strong genetic tractability and amenity for high-throughput screening. The sgsh^Δex5−6 zebrafish mutant exhibits a complete absence of Sgsh enzymatic activity, leading to progressive accumulation of HS degradation products with age. sgsh^Δex5−6 zebrafish faithfully recapitulate diverse CNS-specific features of MPS IIIA, including neuronal lysosomal overabundance, complex behavioural phenotypes, and profound, lifelong neuroinflammation. We further demonstrate that neuroinflammation in sgsh^Δex5−6 zebrafish is largely dependent on interleukin-1β and can be attenuated via the pharmacological inhibition of Caspase-1, which partially rescues behavioural abnormalities in sgsh^Δex5−6 mutant larvae in a context-dependent manner. We expect the sgsh^Δex5−6 zebrafish mutant to be a valuable resource in gaining a better understanding of MPS IIIA pathobiology towards the development of timely and effective therapeutic interventions.     

A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints

In the present paper, the dynamic facilities layout problem is studied in presence of ambiguity of information flow. Product demand (and consequently material flow) is defined as fuzzy numbers with different membership functions. The problem is modeled in fuzzy programming. Three models of expected value, chance-constrained programming and dependent-chance programming and two hybrid intelligent algorithms are then presented. At the end, efficiency of algorithms for solving fuzzy models of dynamic facilities layout is shown through some numerical examples.     

Effect of particle dimension on biocompatibility of carbon nanomaterials

With various emerging applications ranging from medicine to materials and electronics, the risk of exposure to nanomaterials is rapidly increasing. Several routes of exposure to nanomaterials exist; the most important being dermal contact and inhalation. In this dermal toxicity study, the cellular effects of carbon-based materials with diameters ranging from micro- to nano-dimension were investigated using mouse keratinocytes (HEL-30). The carbon materials tested included carbon fibers (CF; 10 μm diameter), carbon nanofibers (CNF; 100 nm diameter), multi-walled carbon nanotubes (MWCNT; 10 nm diameter), and single-walled carbon nanotubes (SWCNT; 1 nm diameter). CF and CNF did not significantly affect cell viability; however, MWCNT and SWCNT reduced cell viability in a time-dependent manner up to 48 h, with full recovery of mitochondrial function by the 72 h time point. After a 24 h exposure, cells exposed to MWCNT produced up to 3-fold higher increase in reactive oxygen species than those exposed to SWCNT. The results of this study suggest that high-aspect ratio carbon material toxicity is dependent on dimension and composition.     

Radiation crosslinking of linear polyethyleneimine-based nanoparticles grafted to poly(glycidyl methacrylate) via trimethylolpropane triacrylate as potential electronic packaging material

Linear polyethyleneimine (L-PEI)-based nanoparticles were synthesized via hydrolysis of poly-2-methyl-2-oxazoline (PMeOx), which was prepared by cationic ring-opening polymerization of the oxazoline five-membered ring. Herein, a kinetic study of the ring-opening polymerization reaction is discussed. The nuclear magnetic resonance spectrum of PMeOx verified the presence of repeating units and terminal groups in the polymer's structure. Molar ratios of PEI and PMeOx were characterized using size exclusion chromatography with low-polydispersity polymer chains as the controlled polymerization reaction. PEI and PMeOx exhibited narrow particle size distribution with hydrodynamic radii of 89 and 67 nm, respectively, as determined via dynamic light scattering analysis. In addition, atomic forces and scanning electron microscopy were used to investigate the topography of the PEI thin films. Poly(glycidyl methacrylate) P(GMA) was grafted onto a PEI chain in the presence of trimethylolpropane triacrylate (TMPTA) as the crosslinking agent to synthesize the P(GMA–PEI–TMPTA) tripolymer via free radical polymerization using gamma irradiation. The thermal characterization of the P(GMA–PEI–TMPTA) tripolymer was conducted using thermogravimetric analysis and differential scanning calorimeter. Generally, the thermal stability of the P(GMA–PEI–TMPTA) tripolymer was improved at low-glycidyl methacrylate concentrations. The prepared tripolymer could be used as effective packaging materials for electronics industries.