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.     

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.     

Structural Properties of Boron-Doped Germanium-Tin Alloys Grown by Molecular Beam Epitaxy

Boron-doped Ge_1?x Sn _x alloys with atomic fractions of tin up to x = 0.08 were grown on n-Ge(001) substrates using solid-source molecular beam epitaxy, in order to study their structural properties. The total boron concentration in the alloys was ~ 10¹⁸ cm^?3 as measured by secondary-ion mass spectroscopy, which also indicated low amounts of impurities such as carbon and oxygen. More than 90% of the Sn atoms occupied substitutional lattice sites in the alloy as determined by Rutherford backscattering spectrometry. High-resolution x-ray diffraction showed that the boron-doped Ge_1?x Sn _x alloys were single crystals that were completely strained with low defect densities and coherent interfaces for thickness up to 90 nm, and for Sn composition of 8%. The boron-doped Ge_1?x Sn _x /n-Ge formed p–n junctions with conventional rectifying characteristics, indicating that the boron produced electrically active acceptor states.     

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]     

Experimental Studies on the Self-Shielding Effect in Fissile Fuel Breeding Measurement in Thorium Oxide Pellets Irradiated with 14 MeV Neutrons

The 14 MeV neutrons produced in the D-T fusion reactions have the potential of breeding Uranium-233 fissile fuel from fertile material Thorium-232. In order to estimate the amount of U-233 produced, experiments are carried out by irradiating thorium dioxide pellets with neutrons produced from a 14 MeV neutron generator. The objective of the present work is to measure the reaction rates of 232 Th + 1 n → 233 Th → 233 Pa → 233 U in different pellet thicknesses to study the self-shielding effects and adopt a procedure for correction. An appropriate assembly consisting of high-density polyethylene is designed and fabricated to slow down the high-energy neutrons, in which Thorium pellets are irradiated. The amount of fissile fuel ( 233 U) produced is estimated by measuring the 312 keV gammas emitted by Protactinium-233 (half-life of 27 days). A calibrated High Purity Germanium (HPGe) detector is used to measure the gamma ray spectrum. The amount of 233 U produced by Th 232 (n, γ) is calculated using MCNP code. The self-shielding effect is evaluated by calculating the reaction rates for different foil thickness. MCNP calculation results are compared with the experimental values and appropriate correction factors are estimated for self-shielding of neutrons and absorption of gamma rays.     

Effect of N-Vinyl-2-Pyrrolidone (NVP), a Bromodomain-Binding Small Chemical,on Osteoblast and Osteoclast Differentiation and Its Potential Application for Bone Regeneration

The human skeleton is a dynamic and remarkably organized organ system that provides mechanical support and performs a variety of additional functions. Bone tissue undergoes constant remodeling; an essential process to adapt architecture/resistance to growth and mechanical needs, but also to repair fractures and micro-damages. Despite bone’s ability to heal spontaneously, certain situations require an additional stimulation of bone regeneration, such as non-union fractures or after tumor resection. Among the growth factors used to increase bone regeneration, bone morphogenetic protein-2 (BMP2) is certainly the best described and studied. If clinically used in high quantities, BMP2 is associated with various adverse events, including fibrosis, overshooting bone formation, induction of inflammation and swelling. In previous studies, we have shown that it was possible to reduce BMP2 doses significantly, by increasing the response and sensitivity to it with small molecules called “BMP2 enhancers”. In the present study, we investigated the effect of N-Vinyl-2-pyrrolidone (NVP) on osteoblast and osteoclast differentiation in vitro and guided bone regeneration in vivo. We showed that NVP increases BMP2-induced osteoblast differentiation and decreases RANKL-induced osteoclast differentiation in a dose-dependent manner. Moreover, in a rabbit calvarial defect model, the histomorphometric analysis revealed that bony bridging and bony regenerated area achieved with NVP-loaded poly (lactic-co-glycolic acid (PLGA) membranes were significantly higher compared to unloaded membranes. Taken together, our results suggest that NVP sensitizes BMP2-dependent pathways, enhances BMP2 effect, and inhibits osteoclast differentiation. Thus, NVP could prove useful as “osteopromotive substance” in situations where a high rate of bone regeneration is required, and in the management of bone diseases associated with excessive bone resorption, like osteoporosis.     

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.