FE3 EPR investigation of PLZT 1/65/35 and 8/65/35

X-band EPR spectra of PLZT 1/65/35 and PLZT 8/65/35 doped with 1% FE³⁺ were recorded at temperature range -175°C to 200°C. Three types of paramagnetic centers were found. Two of them are in strong axial and rhombic crystal field due to neighboring oxygen and lead vacancies. The other center has symmetry determined by polarization and oxygen octahedra tilt. EPR spectra of PLZT 8/65/35 are in agreement with its glassy behavior.     

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.     

A molecular level mechanism ofn-butane oxidation to maleic anhydride over vanadyl pyrophosphate

A molecular level mechanism is proposed for the highly selective 14-e^– oxidative transformation ofn-butane to maleic anhydride on the surface of vanadyl pyrophosphate. The mechanism suggests that the dimeric active sites assume at any given time, one of four possible interconvertible states which differ from each other in the number of available oxygen atoms and the formal oxidation states of the individual vanadium atoms. The relative ratios of active sites in each of the four possible states are dictated by the reaction conditions, the redox properties of the reacting gases and the structure of the vanadyl pyrophosphate active surface. A crucial feature of the mechanism is a pseudo-ozonide surface species formed by the interaction of a chemisorbed dioxygen molecule and an adjacent metal-oxo group. This unusual species is responsible for the initial activation of then-butane, which occurs when the chemisorbed dioxygen abstracts an H-atom from the alkane and the adjacent metal-oxo group reacts with the incipient alkyl radical to form an alkoxy group. The proposed mechanism is entirely consistent with literature reports describing the behaviour of (VO)₂P₂O₇ in flow, pulse and TAP reactors.     

Early detection of heart diseases using a low-cost compact ECG sensor

Multimedia Tools and Applications - Heart disease patients are continuously increasing. The patients face the problem of a delayed diagnosis as the subjects do not undergo routine tests and consult...     

Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning

Robotic Path planning is one of the most studied problems in the field of robotics. The problem has been solved using numerous statistical, soft computing and other approaches. In this paper we solve the problem of robotic path planning using a combination of A* algorithm and Fuzzy Inference. The A* algorithm does the higher level planning by working on a lower detail map. The algorithm finds the shortest path at the same time generating the result in a finite time. The A* algorithm is used on a probability based map. The lower level planning is done by the Fuzzy Inference System (FIS). The FIS works on the detailed graph where the occurrence of obstacles is precisely known. The FIS generates smoother paths catering to the non-holonomic constraints. The results of A* algorithm serve as a guide for FIS planner. The FIS system was initially generated using heuristic rules. Once this model was ready, the fuzzy parameters were optimized using a Genetic Algorithm. Three sample problems were created and the quality of solutions generated by FIS was used as the fitness function of the GA. The GA tried to optimize the distance from the closest obstacle, total path length and the sharpest turn at any time in the journey of the robot. The resulting FIS was easily able to plan the path of the robot. We tested the algorithm on various complex and simple paths. All paths generated were optimal in terms of path length and smoothness. The robot was easily able to escape a variety of obstacles and reach the goal in an optimal manner.     

Rapidly exploring random graphs: motion planning of multiple mobile robots

Rapidly exploring random trees (RRT) and probabilistic roadmaps (PRM) are sampling-based techniques being extensively used for robot path planning. In this paper, the tree structure of the RRT is generalized to a graph structure which enables a greater exploration. Exploration takes place simultaneously from multiple points in the map, all explorations fusing at multiple points producing well-connected graph architecture. Initially, in a typical RRT manner, the search algorithm attempts to reach the goal by expansions, and thereafter furtherer areas are explored. With some additional computation cost, as compared to RRT with a single robot, the results can be significantly improved. The so-formed graph is similar to roadmap produced by PRM. However as compared to PRM, the proposed algorithm has a more judicious search strategy and is adaptable to the number of nodes as a parameter. Experimental results are shown with multiple robots planned using prioritization scheme. Results show the betterment of the proposed algorithm as compared to RRT and PRM techniques.     

MULTIROBOT MOTION PLANNING USING HYBRID MNHS AND GENETIC ALGORITHMS

Planning the motion of multiple robots deals with computing the motion of all robots avoiding any collision. This article focuses on the use of hybrid Multi Neuron Heuristic Search (MNHS) and Genetic Algorithm (GA). The MNHS is an advancement over the conventional A* algorithm and is better suited for maze-like conditions where there is a high degree of uncertainty. The MNHS contributes toward optimality of the solution, and the GA gives it an iterative nature and enables the approach to be used on high-resolution maps. MNHS works over the set of points returned by the GA in its fitness function evaluation. A priority-based approach is used, in which the priorities are decided by the GA. Path feasibility is speeded up by using the concept of coarser-to-finer lookup called momentum. Experimental results show that the combined approach is able to easily solve the problem for a variety of scenarios.

[Supplementary materials are available for this article. Go to the publisher's online edition of Applied Artificial Intelligence for the following free supplemental resource(s): Videos 1-4]     

Sulphated polysaccharides from Indian samples of Enteromorpha compressa (Ulvales,Chlorophyta): Isolation and structural features

Heteroglycan and xyloglucan rich fractions were extracted from Indian samples of Enteromorpha compressa in 25% yield by sequential extractions with water and alkali. This heteroglycan is sulfated and has an apparent molecular mass of 55 kDa. Chemical structural analysis of this polysaccharide revealed a branched structure having 1,4- and 1,2,4-linked rhamnose 3-sulphate, 1,4-linked glucose, 1,3- and 1,6- linked galactose, 1,4- and terminally linked glucuronic acid and 1,4-linked xylose partially sulfated on O-2. Chemical and spectroscopic analysis showed that the 4-M KOH extracted hemicellulosic fraction contained an unusual β-(1,4)-linked linear xyloglucan. Enzyme hydrolysis and analysis of the resulting fragments by matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) showed that this linear polymer contained partially sulfated Glc₃Xyl₂ or Glc₄Xyl₂ as oligomeric building subunits.     

Nanostructures from Single Amino Acid‐Based Molecules: Stability,Fibrillation, Encapsulation,and Fabrication of Silver Nanoparticles

The small‐sized molecules that have been developed from single hydrophobic amino acids (Phe, Trp, Tyr and Leu) by suitably protecting the –NH₂ and –CO₂H groups generate diverse nanoscopic structures – such as nanorods, nanofibrils, nanotubes, and nanovesicles – depending upon the protection parameters and solvent polarity. The vesicular structures get disrupted in the presence of various salts, such as KCl, CaCl₂, (NH₄)₂SO₄ and N(n‐Bu)₄Br. Insertion of unnatural (o/m/p)‐aminobenzoic acids as a protecting group and the lack of conventional peptide bonds in the molecules give the nanostructures proteolytic stability. The nanostructures also show significant thermal stability along with a morphological transformation upon heat treatment. Our in vitro studies reveal that the addition of micromolar concentration “curcumin” significantly reduces the formation of amyloid‐like fibrils. These diverse nanostructures are used as a template for fabricating silver nanoparticles on their outer surfaces as well as in the inner part, followed by calcination in air which helps to obtain a 1D silver nanostructure. Furthermore, the nanovesicles are observed to encapsulate a potent drug (curcumin) and other biologically important molecules, which could be released through salt‐triggered disruption of vesicles.     

Multiuser Detection in SDMA–OFDM Wireless Communication System Using Complex Multilayer Perceptron Neural Network

The space division multiple access–orthogonal frequency division multiplexing (SDMA–OFDM) wireless system has become very popular owing high spectral efficiency and high load capability. The optimal maximum likelihood multiuser detection (MUD) technique suffers from high computational complexity. On the other hand the linear minimum mean square error (MMSE) MUD techniques yields poor performance and also fails to detect users in overload scenario, where the number of users are more than that of number of receiving antennas. By contrast, the differential evolution algorithm (DEA) aided minimum symbol error rate (MSER) MUD can sustain in overload scenario as it can directly minimizes probability of error rather than mean square error. However, all these classical techniques are still complex as these do channel estimation and multiuser detection sequentially. In this paper, complex multi layer perceptron (CMLP) neural network model is suggested for MUD in SDMA–OFDM system as it do both channel approximation and MUD simultaneously. Simulation results prove that the CMLP aided MUD performs better than the MMSE and MSER techniques in terms of enhanced bit error rate performance with low computational complexity.