Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

A capacitance based proximity sensor, the 'Capaciflector' (Vranish 92), has been developed at the Goddard Space Flight Center of NASA. We had investigated the use of this sensor for avoiding and maneuvering around unexpected objects (Mahalingam 92). The approach developed there would help in executing collision-free gross motions. Another important aspect of robot motion planning is fine motion planning. Let us classify manipulator robot motion planning into two groups at the task level: gross motion planning and fine motion planning. We use the term 'gross planning' where the major degrees of freedom of the robot execute large motions, for example, the motion of a robot in a pick and place type operation. We use the term 'fine motion' to indicate motions of the robot where the large dofs do not move much, and move far less than the mirror dofs, such as in inserting a peg in a hole. In this report we describe our experiments and experiences in this area

Modeling Vacuum Arcs

We are developing a model of vacuum arcs. This model assumes that arcs develop as a result of mechanical failure of the surface due to Coulomb explosions, followed by ionization of fragments by field emission and the development of a small, dense plasma that interacts with the surface primarily through self sputtering and terminates as a unipolar arc capable of producing breakdown sites with high enhancement factors. We have attempted to produce a self consistent picture of triggering, arc evolution and surface damage. We are modeling these mechanisms using Molecular Dynamics (mechanical failure, Coulomb explosions, self sputtering), Particle-In-Cell (PIC) codes (plasma evolution), mesoscale surface thermodynamics (surface evolution), and finite element electrostatic modeling (field enhancements). We can present a variety of numerical results. We identify where our model differs from other descriptions of this phenomenon.Comment: 4 pages, 5 figure

Bioinspired electrohydrodynamic ceramic patterning of curved metallic substrates

Template-assisted electrohydrodynamic atomisation (TAEA) has been used for the first time to pattern curved metallic surfaces. Parallel lines of ceramic titania (TiO2) were produced on titanium substrates, convex and concave with diameters of ~25 mm, at the ambient temperature. Optimal results were obtained with 4 wt% TiO2 in ethanol suspension deposited over 300 s during stable cone-jetting at 20 µl/min, 10kV and collection distance 80 mm. A high degree of control over pattern line width, interline spacing and thickness were achieved. Nanoindentation load-displacement curves were continuous for the full loading and unloading cycle, indicating good adhesion between pattern and substrate. At a loading rate of 1 μN/s and a hold time of 1 s, pattern hardness decreased as load increased up to 7 μN and remained at 0·1 GPa up to higher loads. Elastic modulus behaved similarly, and both were not sensitive to loading rate. The effect of heat treatment to further consolidate the patterned deposits was also investigated. Hardness of the patterns was not markedly affected by heating. This work shows that TAEA is highly controllable and compatible on a range of substrate geometries. Extending TAEA capabilities from flat to curved surfaces, enabling the bioactive patterning of different surface geometries, takes this technology closer to orthopaedic engineering applications

Political economy of independent regulation in India's natural gas industry

Based on a case study of India's downstream hydrocarbon regulator, this article argues that the success or failure of independent regulation in industries supplying basic goods and services is determined by the politico-economic context in which the regulator functions. In a developing country with a large number of poor people without access to basic necessities such as water, energy, or roads, independent economic regulation by itself can deliver little, unless backed by a strong political will

Predicting Financial Savings Decisions Using Sigmoid Function and Information Gain Ratio

AbstractPlanning for savings remains one of the most critical decisions for any user. The most important factor in this process is decision making. Most of the time, we can take decisions on how much money to save at a time based on our spending pattern. But automating this process is not easy, since it involves a number of parameters. Here, we attempt to incorporate intelligence into this decision making. The algorithm will attempt to predict the maximum amount to save based on the current account balance, clubbed with the entire database of available transactions on that account / user. Every transaction will be assigned an impact factor based on the time of occurrence, relative to the current date. Every month is divided into four quarters to track recurring expenses like EMIs. These impacts have to be taken by a machine learning algorithm to predict the maximum possible savings in that quarter. The impact factor will also depend upon the fraction of balance being spent on that quarter. If there is a goal set for savings, it will also be taken into consideration. If a considerable expense is predicted for that month, the savings will be kept low so that the account won’t go into overdraft. Recurring expenses are kept in check and accounted for to the maximum extent using information gain ratio from the transaction list

Candida tropicalis spondylodiskitis in a patient with carcinoma of sigmoid colon: a case report

Fungal spondylodiskitis is being increasingly reported in immunocompromised patients. A patient who presented with severe back pain three months following laparoscopic resection of Carcinoma of Sigmoid colon is presented here. Magnetic Resonance Imaging of the spine showed evidence of multilevel lumbar spondylodiskitis. Biopsy done via the posterior approach showed Candida tropicalis sensitive to fluconazole and resistant to Amphotericin B. Patient was treated with fluconazole and had good relief. Posterior pedicle screw stabilization was done to provide mechanical stability

Physio-chemical and antibacterial characteristics of pressure spun nylon nanofibres embedded with functional silver nanoparticles

© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Date of Acceptance: 05/06/2015A novel and facile approach to prepare hybrid nanoparticle embedded polymer nanofibers using pressurised gyration is presented. Silver nanoparticles and nylon polymer were used in this work. The polymer solution's physical properties, rotating speed and the working pressure had a significant influence on the fibre diameter and the morphology. Fibres in the range of 60–500 nm were spun using 10 wt.%, 15 wt.% and 20 wt.% nylon solutions and these bead-free fibres were processed under 0.2 MPa and 0.3 MPa working pressure and a rotational speed of 36,000 rpm. 1–4 wt.% of Ag was added to these nylon solutions and in the case of wt.% fibres in the range 50–150 nm were prepared using the same conditions of pressurised gyration. Successful incorporation of the Ag nanoparticles in nylon nanofibres was confirmed by using a combination of advanced microscopical techniques and Raman spectrometry was used to study the bonding characteristics of nylon and the Ag nanoparticles. Inductively coupled plasma mass spectroscopy showed a substantial concentration of Ag ions in the nylon fibre matrix which is essential for producing effective antibacterial properties. Antibacterial activity of the Ag-loaded nanofibres shows higher efficacy than nylon nanofibres for Gram-negative Escherichia coli and Pseudomonas aeruginosa microorganisms, and both Ag nanoparticles and the Ag ions were found to be the reason for enhanced cell death in the bacterial solutionPeer reviewe

Analysis of homogeneous turbulent reacting flows

Full turbulence simulations at low Reynolds numbers were made for the single-step, irreversible, bimolecular reaction between non-premixed reactants in isochoric, decaying homogeneous turbulence. Various initial conditions for the scalar field were used in the simulations to control the initial scalar dissipation length scale, and simulations were also made for temperature-dependent reaction rates and for non-stoichiometric and unequal diffusivity conditions. Joint probability density functions (pdf's), conditional pdf's, and various statistical quantities appearing in the moment equations were computed. Preliminary analysis of the results indicates that compressive strain-rate correlates better than other dynamical quantities with local reaction rate, and the locations of peak reaction rates seem to be insensitive to the scalar field initial conditions