Agile Spectrum Imaging: Programmable Wavelength Modulation for Cameras and Projectors

We advocate the use of quickly‐adjustable, computer‐controlled color spectra in photography, lighting and displays. We present an optical relay system that allows mechanical or electronic color spectrum control and use it to modify a conventional camera and projector. We use a diffraction grating to disperse the rays into different colors, and introduce a mask (or LCD/DMD) in the optical path to modulate the spectrum. We analyze the trade‐offs and limitations of this design, and demonstrate its use in a camera, projector and light source. We propose applications such as adaptive color primaries, metamer detection, scene contrast enhancement, photographing fluorescent objects, and high dynamic range photography using spectrum modulation.     

Global optimization methods for engineering applications: A review

A review of the methods for global optimization reveals that most methods have been developed for unconstrained problems. They need to be extended to general constrained problems because most of the engineering applications have constraints. Some of the methods can be easily extended while others need further work. It is also possible to transform a constrained problem to an unconstrained one by using penalty or augmented Lagrangian methods and solve the problem that way. Some of the global optimization methods find all the local minimum points while others find only a few of them. In any case, all the methods require a very large number of calculations. Therefore, the computational effort to obtain a global solution is generally substantial. The methods for global optimization can be divided into two broad categories: deterministic and stochastic. Some deterministic methods are based on certain assumptions on the cost function that are not easy to check. These methods are not very useful since they are not applicable to general problems. Other deterministic methods are based on certain heuristics which may not lead to the true global solution. Several stochastic methods have been developed as some variation of the pure random search. Some methods are useful for only discrete optimization problems while others can be used for both discrete and continuous problems. Main characteristics of each method are identified and discussed. The selection of a method for a particular application depends on several attributes, such as types of design variables, whether or not all local minima are desired, and availability of gradients of all the functions.Notation Number of equality constraints - () ^T A transpose of a vector - A A hypercubic cell in clustering methods - Distance between two adjacent mesh points - Probability that a uniform sample of sizeN contains at least one point in a subsetA ofS - A(v, x) Aspiration level function - A The set of points with cost function values less thanf(x _G ^* ) +. Same asA _f () - A _f () A set of points at which the cost function value is within off(x _G ^* ) - A () A set of points x with[f(x)] smaller than - A _N The set ofN random points - A _q The set of sample points with the cost function value f _q - _Q The contraction coefficient; –1 _Q 0 - _R The expansion coefficient; _E > 1 - _R The reflection coefficient; 0 < _R 1 - A _x () A set of points that are within the distance from x _G ^* - D Diagonal form of the Hessian matrix - det() Determinant of a matrix - d _j A monotonic function of the number of failed local minimizations - d _t Infinitesimal change in time - d _x Infinitesimal change in design - A small positive constant - (t) A real function called the noise coefficient - ₀ Initial value for(t) - exp() The exponential function - f ^(c) The record; smallest cost function value over X^(C) - [f(x)] Functional for calculating the volume fraction of a subset - Second-order approximation tof(x) - f(x) The cost function - An estimate of the upper bound of global minimum - f ^E The cost function value at x^E - f ^L The cost function value at x^L - f _opt The current best minimum function value - f ^P The cost function value at x ^P - f ^Q The cost function value at x ^Q - f _q A function value used to reduce the random sample - f ^R The cost function value at x ^R - f ^S The cost function value at x^S - f _{T F min} A common minimum cost function value for several trajectories - f _{TF opt} The best current minimum value found so far forf _{TF min} - f ^W The cost function value at x ^W - G Minimum number of points in a cell (A) to be considered full - The gamma function - A factor used to scale the global optimum cost in the zooming method - Minimum distance assumed to exist between two local minimum points - gi(x) Constraints of the optimization problem - H The size of the tabu list - H(x^*) The Hessian matrix of the cost function at x^* - h _j Half side length of a hypercube - h _m Minimum half side lengths of hypercubes in one row - I The unity matrix - ILIM A limit on the number of trials before the temperature is reduced - J The set of active constraints - K Estimate of total number of local minima - k Iteration counter - The number of times a clustering algorithm is executed - L Lipschitz constant, defined in Section 2 - L The number of local searches performed - _i The corresponding pole strengths - log () The natural logarithm - LS Local search procedure - M Number of local minimum points found inL searches - m Total number of constraints - m(t) Mass of a particle as a function of time - m() TheLebesgue measure of thea set - Average cost value for a number of random sample of points inS - N The number of sample points taken from a uniform random distribution - n Number of design variables - n(t) Nonconservative resistance forces - n _c Number of cells;S is divided inton _c cells - NT Number of trajectories - Pi (3.1415926) - P _i ^(j) Hypersphere approximating thej-th cluster at stagei - p(x ⁽ⁱ⁾⁾ Boltzmann-Gibbs distribution; the probability of finding the system in a particular configuration - pg A parameter corresponding to each reduced sample point, defined in (36) - Q An orthogonal matrix used to diagonalize the Hessian matrix - _i (i = 1, K) The relative size of thei-th region of attraction - r _i ^(j) Radius of thej-th hypersp here at stagei - R _x ^* Region of attraction of a local minimum x^* - r _j Radius of a hypersphere - r A critical distance; determines whether a point is linked to a cluster - R ⁿ A set ofn tuples of real numbers - A hyper rectangle set used to approximateS - S The constraint set - A user supplied parameter used to determiner - s The number of failed local minimizations - T The tabu list - t Time - T(x) The tunneling function - T _c (x) The constrained tunneling function - T _i The temperature of a system at a configurationi - TLIMIT A lower limit for the temperature - TR A factor between 0 and 1 used to reduce the temperature - u(x) A unimodal function - V(x) The set of all feasible moves at the current design - v(x) An oscillating small perturbation. - V(y⁽ⁱ⁾) Voronoi cell of the code point y⁽ⁱ⁾ - v^–1 An inverse move - v _k A move; the change from previous to current designs - w(t) Ann-dimensional standard. Wiener process - x Design variable vector of dimensionn - x^# A movable pole used in the tunneling method - x⁽⁰⁾ A starting point for a local search procedure - X^(c) A sequence of feasible points {x⁽¹⁾, x⁽²⁾,,x^(c)} - x(t) Design vector as a function of time - X^* The set of all local minimum points - x^* A local minimum point forf(x) - x^*(i) Poles used in the tunneling method - x _G ^* A global minimum point forf(x) - Transformed design space - The velocity vector of the particle as a function of time - Acceleration vector of the particle as a function of time - x ^C Centroid of the simplex excluding x ^L - x ^c A pole point used in the tunneling method - x ^E An expansion point of x ^R along the direction x ^C x ^R - x ^L The best point of a simplex - x ^P A new trial point - x ^Q A contraction point - x ^R A reflection point; reflection of x ^W on x ^C - x ^S The second worst point of a simplex - x ^W The worst point of a simplex - The reduced sample point with the smallest function value of a full cell - Y The set of code points - y ⁽ⁱ⁾ A code point; a point that represents all the points of thei-th cell - z A random number uniformly distributed in (0,1) - Z ^(c) The set of points x where [f ^(c) – ] is smaller thanf(x) - []₊ Max (0,) - | | Absolute value - The Euclidean norm - f[x(t)] The gradient of the cost function     

Hpcfolder: a simple tool used to parallelize algorithms using the message passing interface (MPI)

The Journal of Supercomputing - Hpcfolder is a user-friendly high-performance computing tool that can be used to analyze the performance of algorithms parallelized using MPI. It is possible to view...     

Antineoplastic and antioxidant potential of phycofabricated silver nanoparticles using microalgae Chlorella minutissima

This study for the first time reports on fresh water microalgae Chlorella minutissima aqueous extract (CmAe) which was utilized for the biogenic synthesis of silver nanoparticles and tested their antineoplastic potential against Liver Hepatocellular Carcinoma (HepG2) cell line. The characteristic colour change of the reaction mixture from greenish yellow to yellowish brown confirmed the synthesis of Chlorella minutissima silver nanoparticles (CmAgNPs). Microscopic analysis revealed CmAgNPs to be spherical‐shaped with particle size ranging from 10 to 30 nm. The carbohydrates and proteins distinctive peaks were observed in Fourier transform infrared spectroscopy (FTIR) spectra which suggested these biomolecules acted as reducing and capping agents. Further, the crystalline nature of CmAgNPs was confirmed by X‐ray diffraction (XRD) analysis. CmAgNPs showed maximum free radical scavenging proving it to be more potent antioxidant agent as compared to CmAe. The mortality rate of HepG2 cells treated with CmAgNPs was found to be 91.8 % at 120 μg/ml with IC₅₀ value 12.42 ± 1.096 μg/ml after 48 h whereas no effect was observed on normal Human Embryonic Kidney (HEK 293) cells. Fluorescent images of the treated HepG2 cells revealed the formation of apoptotic bodies, condensed nuclei and cell shrinkage indicating their effectiveness against the cancer cells.Inspec keywords: silver, nanoparticles, nanomedicine, microorganisms, cellular biophysics, nanofabrication, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, proteins, Fourier transform infrared spectra, molecular biophysics, X‐ray chemical analysis, X‐ray diffraction, kidney, cancer, biomedical materialsOther keywords: antineoplastic potential, antioxidant potential, phycofabricated silver nanoparticle, Chlorella minutissima, freshwater microalgae, aqueous extract, liver hepatocellular carcinoma cell line, CmAgNP synthesis, field emission scanning electron microscopy, high‐resolution transmission electron microscopy, atomic force microscopy, dynamic light scattering, carbohydrate, protein, Fourier transform infrared spectroscopy, biomolecule, energy‐dispersive X‐ray spectroscopy, elemental silver signal, CmAgNP crystalline, X‐ray diffraction analysis, antioxidant agent, HepG2 cell mortality rate, human embryonic kidney, HEK 293 cell, fluorescent image, apoptotic body formation, condensed nuclei, cell shrinkage, cancer cell, antineoplastic agent, Ag     

A mathematical model for wave propagation in a composite solid matrix containing two immiscible fluids

Constitutive relations and field equations have been extended for a porous medium composed of two solids and containing two chemically non-reactive immiscible fluids. By generalizing the closure relation of porosity change and employing this into the mass balance equations, the stress–strain relations have been developed. The idea of generalized compressibility tests is invoked to find the value of dimensionless parameters appearing in the closure relation of porosity change. By generalizing momentum balance equations of Lo et al. (Water Resour Res 41:1–20, 2005), the propagation of dilatational and rotational waves is explored. It is found that four dilatational and two rotational waves exist in the porous medium. In contrast to Biot’s theory, the presence of the second fluid and second solid in the porous medium gives rise to additional P- and S-waves. Variation of phase speeds and corresponding attenuation coefficients of existing waves versus frequency, saturation of the fluid phases and solid fraction are computed numerically and depicted graphically.     

Charge transport and structural morphology of HCl-doped polyaniline

The d.c. and a.c. (100 Hz–1 MHz) conductivities of HCl-doped polyaniline have been measured in the temperature range 77–300 K. At 77 K, the a.c. conductivity data, (), can be described by the relation ()=As, where the parameter s lies close to unity and decreases with increase in the doping level. The ratio of measured a.c. to d.c. conductivity shows dispersion at 77 K, which decreases with increase in the doping level. This decrease is found to be sharp around pH3.0. In the temperature range 77–150 K, the observed d.c. conductivity data can be described by Mott's three dimensional variable range hopping (VRH) model. Scanning electron microscopy studies reveal a sharp change in structural morphology of HCl-doped polyaniline at a pH3.0. A strikingly remarkable structural morphology has been observed in the formc of a channel at this pH value. This change is accompanied by a rapid increase in d.c. conductivity, dielectric constant, along with sharp changes in structural morphology, which indicates the existence of a doping-induced structural conductivity correlation in this system. © 1998 Chapman & Hall     

Optimal structural design with indirect use of Transferred Forces

An optimal design method based on the concepts of Transferred Forces is introduced. The method uses these forces in an indirect way. The concept of reaction functional based on transferred forces is introduced. The functional approximates the structural behaviour in terms of the properties of a selected region. Using the reaction functionals, a nonlinear programming formulation and a computational method that perform sizing and topology optimization are developed. The procedure does not need structural analyses during optimization iterations. Example problems are solved with the method and the similar solutions are obtained for a refined mesh model and a different starting design. Thus, it is concluded that the new concept presented here is applicable to structural optimization problems. Received June 28, 2000     

Study of variational inequality and equality formulations for elastostatic frictional contact problems

Summary An overview ofvariational inequality andvariational equality formulations for frictionless contact and frictional contact problems is provided. The aim is to discuss the state-of-the-art in these two formulations and clearly point out their advantages and disadvantages in terms of mathematical completeness and practicality. Various terms required to describe the contact configuration are defined.Unilateral contact law and classical Coulomb’s friction law are given.Elastostatic frictional contact boundary value problem is defined. General two-dimensional frictionless and frictional contact formulations for elastostatic problems are investigated. An example problem of a two bar truss-rigid wall frictionless contact system is formulated as an optimization problem based on the variational inequality approach. The problem is solved in a closed form using the Karush-Kuhn-Tucker (KKT) optimality conditions. The example problem is also formulated as a frictional contact system. It is solved in the closed form using a new two-phase analytical procedure. The procedure avoids use of the incremental/iterative techniques and user defined parameters required in a typical implementation based on the variational equality formulation. Numerical solutions for the frictionless and frictional contact problems are compared with the results obtained by using a general-purpose finite element program ANSYS (that uses variational equality formulation). ANSYS results match reasonably well with the solutions of KKT optimality conditions for the frictionless contact problem and the two-phase procedure for the frictional contact problem. The validity of the analytical formulation for frictional contact problems (with one contacting node) is verified. Thevariational equality formulation for frictionless and frictional, contact problems is also studied in detail. The incremental/iterative Newton-Raphson scheme incorporating the penalty approach is utilized. Studies are conducted to provide insights for the numerical solution techniques. Based on the present study it is concluded that alternate formulations and computational procedures need to be developed for analysis of frictional contact problems.     

Sterile keratitis after corneal collagen crosslinking in a child

Corneal collagen crosslinking (CXL) is a non invasive technique used in halting the progression of keratoconus. Complications with this modality are rare. We report a case of an 8-year-old child who developed sterile infiltrates in the immediate postoperative period after uneventful corneal collagen crosslinking for keratoconus. The infiltrates resolved with topical steroid therapy. There was also present coexisting vernal keratoconjunctivitis (VKC) which was controlled with topical 2% cyclosporine A eye drops prior to crosslinking treatment. This case highlights importance of controlling VKC prior to CXL in keratoconus as it adds to the risk of developing post operative sterile keratitis.