As the LED Light spectrum continues to evolve and researchers now better understand how lighting has a profound effect on sleep, alertness, performance and health, WalaLight implements costefficient, environmentallyfriendly lighting solutions. In addition to cost savings on utilities, WalaLight can dramatically reduce the need for lighting maintenance and replacement"By using WalaLight, physical and mental wellbeing improves through optimal circadian rhythms," Zuker said. "We can also reset the biological clock for jet lag, as well as circumvent seasonal effect disorder, PTSD, ADHD and many other disorders."
Headquartered in Boca Raton, Florida, WalaLight is designed and manufactured in North America by a special division of uSaveLED, an industry leading supplier of commercial and industrial energyefficient LED lighting products. WalaLight's Healthy Circadian Lighting provides clients across the nation with costefficient, environmentallyfriendly, longlife, highlycertified lighting solutions designed to save them money on utility costs, while also dramatically reducing the need for lighting maintenance and replacement.
"We're able to provide the appropriate spectrum of lighting through our smart Kelvin changing technology. This, in turn, vastly improves behavior and performance," WalaLight Chief Technology Officer, Rodney Smith, said. "We focus on keeping people healthy instead of waiting for health problems to occur, by generating the right amount of light therapy." 
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Inside the waveguide, the electric field, E, and the magnetic field, H, are governed by the 3D Maxwell's equations, where μ, ε, and σ are the permeability, permittivity, and conductivity of the medium. Inside the coaxial cable, under the assumption that only the TEM mode is supported, the potential difference, V, and the current, I, satisfy the 1D transport equation23, where Zc and c are the characteristic impedance and the phase velocity inside the kdirected coaxial CCTV coaxial cable. The terms V???ZcI and V?+?ZcI represent signals traveling inside the coaxial cable in the negative and positive kdirection, respectively. We assume that both the coaxial cable and the waveguide extend to infinity (matched). Moreover, we assume that the only signal source is an incoming energy, Win,wg, associated with the TE10 mode, propagating inside the waveguide towards the negative z axis; see Fig. 1. The incoming energy through the coaxial cable, Win,coax, is assumed to be zero. Under the above assumptions, we can write the following energy balance for the cable–waveguide system, where the right side is the total outgoing energy that consists of the energy existing through the coaxial CCTV coaxial cable Wout,coax, the reflected energy in the waveguide Wout,wg, and the ohmic loss inside the domain Ω. Inspecting expression (4), we note that a natural design objective is to maximize the signal coupled to the coaxial cable (cable A or cable B), Wout,coax, which implicitly implies the minimization of the remaining two terms Wout,wg and . Therefore, given the incoming energy, Win,wg, we formulate the conceptual optimisation problem subject to the set of governing equations and boundary conditions. We numerically solve equations (1), (2), and (3) by the FDTD method30. Let σ be a vector that holds the conductivity components at each Yee edge inside the domain Ω. The goal is to find the σ that maximizes the outgoing energy through the coaxial CCTV coaxial cable, which we accomplish through a gradientbased optimisation method. Let p be a vector of the same dimension as σ storing the design variables that are actually updated by the optimisation algorithm; it holds that 0?≤?pi?≤?1 for each component of p. The design variables should interpolate between the conductivity values representing a good dielectric (pi?=?0) and a good conductor (pi?=?1). However, there is a vast variation in the conductivity value between a good dielectric and a good conductor. For example, the free space has σ?=?0?S/m and the copper has σ?=?5.8?×?107?S/m. The average of these values still represents a good conductor, so the use of a linear interpolation between these values would make the algorithm overly sensitive for small changes of almost vanishing design variables. We therefore use the following exponential interpolation scheme: which gives σmin?=?10?3?S/m and σmax?=?105?S/m for pi?=?0 and pi?=?1, respectively. Numerical experiments show a low sensitivity of the objective function to variations in σ outside the range [σmin, σmax], and the conductivity value for pi?=?1/2 now indeed represents a lossy material that is neither a good dielectric nor a good conductor. Formally, our optimisation problem reads.




where is the outgoing energy through the coaxial CCTV
coaxial cable computed by the FDTD method, and N is the number of Yee edges
inside the design domain Ω. The spectral density of the incoming energy, , will
implicitly determine the frequencies for which the structure will be optimised.
To address the wideband objective function in optimisation problem (7), we use a
timedomain sinc signal to impose the incoming energy, , inside the waveguide. A
sinc signal with infinite duration has a flat energy spectral density over a
specific bounded frequency interval31. To realise a reasonable simulation time,
we truncate the sinc signal after 8 lobes. The truncated sinc signal is
modulated to the center of the frequency band of interest and its bandwidth is
set to cover this frequency band. The objective function gradient is computed
using the solution to an adjointfield problem, which is also a FDTD
discretization of Maxwell’s equations, but is fed with a time reversed version
of the observed signal at the coaxial cable32. For any number of design
variables, the gradient of the objective function can be computed with only two
FDTD simulations, one to the originalfield problem and one to the adjointfield
problem.
Optimisation problem (7) is strongly selfpenalised towards the lossless
design cases. More precisely, solving problem (7) by gradientbased optimisation
methods leads, after only a few iterations, to designs consisting mainly of a
good conductor (σmax) or a good dielectric (σmin). The reason for the strong
selfpenalisation can be explained by energy balance (4) as follows. To maximize
CCTV
coaxial cable the outgoing energy, Wout,coax, for a given incoming energy,
Win,wg, the energy losses, , inside the design domain should by minimized. The
intermediate conductivities contribute to higher energy losses than the extreme
conductivities, as pointed out in the introduction. Thus, any gradientbased
optimisation method will attempt to minimize the energy losses, , by moving the
edge conductivities towards the lossless cases (σmin and σmax). Unfortunately,
the resulting optimised designs often consist of scattered metallic parts and
exhibit bad performance24.
To relax the strong selfpenalisation, we use a filtering approach that
imposes some intermediate conductivities inside the design domain during the
initial phase of the optimisation. To do so, we replace pi by qi in expression
(6), where the vector q?=?Kp, in which the filter matrix K is a discrete
approximation of an integral operator with support over a disc with radius R.
The filter replaces each component in the vector p by a CCTV
coaxial cable weighted average of the neighbouring components, where the
weights vary linearly from a maximum value at the center of the disc to zero at
the perimeter. To avoid lossy final designs, we solve optimisation problem (7)
through a series of subproblems, where after the solution of subproblem n, the
filter radius is reduced by setting Rn+1?=?0.8?Rn. We start with a filter radius
R1?=?40Δ, where Δ denotes the FDTD spatial discretization step. Each subproblem
is iteratively solved until a stopping criterion for optimisation, based on the
firstorder necessary condition, is satisfied. To update the design variables,
we use the globally convergent method of moving asymptotes (GCMMA)33.
We investigate the design of transitions between a 50?Ohm coaxial CCTV
coaxial cable (probe diameter 1.26?mm, outer shield diameter 4.44?mm) and
and two standard waveguides; the WR90 (a?=?22.86?mm and b?=?10.16?mm) and the
WR430 waveguides (a?=?109.22?mm and b?=?54.61?mm). The first cutoff frequency of
the WR90 waveguide is f10?=?6.56?GHz and the second is f20?=?13.12?GHz, while
the WR430 waveguide has f10?=?1.37?GHz and f20?=?2.75?GHz. The frequency band of
interest in both cases is the band between the first and the second cutoff
frequencies, where only the TE10 mode can propagate (below, we refer to this
bandwidth as the bandwidth objective). These frequency bands correspond to a
relative bandwidth of 66.7% for the WR90 waveguide and 67.0% for the WR430
waveguide. In our numerical experiments, we use uniform FDTD grids. For the WR90
waveguide we use a spatial step size Δ?=?0.127?mm, and for the WR430 waveguide
Δ?=?0.607?mm. In both cases, a 16 cell perfectly matched layer (PML) is used to
terminate the waveguide and 15 cells of free space separate the end of the
design domain and the beginning of the PML. We use an inhouse FDTD code
implemented to run on graphics processing units (GPU) using the parallel
computing platform CUDA (https://developer.nvidia.com/whatcuda). One solution
to Maxwell’s equations takes around 5?minutes and around 4?GB of memory is
required for computing the objective function gradient. The waveguide walls and
the coaxial probe are assigned a conductivity value of σ?=?5.8?×?107?S/m.




where is the outgoing energy through the coaxial CCTV
coaxial cable computed by the FDTD method, and N is the number of Yee edges
inside the design domain Ω. The spectral density of the incoming energy, , will
implicitly determine the frequencies for which the structure will be optimised.
To address the wideband objective function in optimisation problem (7), we use a
timedomain sinc signal to impose the incoming energy, , inside the waveguide. A
sinc signal with infinite duration has a flat energy spectral density over a
specific bounded frequency interval31. To realise a reasonable simulation time,
we truncate the sinc signal after 8 lobes. The truncated sinc signal is
modulated to the center of the frequency band of interest and its bandwidth is
set to cover this frequency band. The objective function gradient is computed
using the solution to an adjointfield problem, which is also a FDTD
discretization of Maxwell’s equations, but is fed with a time reversed version
of the observed signal at the coaxial cable32. For any number of design
variables, the gradient of the objective function can be computed with only two
FDTD simulations, one to the originalfield problem and one to the adjointfield
problem.
Optimisation problem (7) is strongly selfpenalised towards the lossless
design cases. More precisely, solving problem (7) by gradientbased optimisation
methods leads, after only a few iterations, to designs consisting mainly of a
good conductor (σmax) or a good dielectric (σmin). The reason for the strong
selfpenalisation can be explained by energy balance (4) as follows. To maximize
CCTV
coaxial cable the outgoing energy, Wout,coax, for a given incoming energy,
Win,wg, the energy losses, , inside the design domain should by minimized. The
intermediate conductivities contribute to higher energy losses than the extreme
conductivities, as pointed out in the introduction. Thus, any gradientbased
optimisation method will attempt to minimize the energy losses, , by moving the
edge conductivities towards the lossless cases (σmin and σmax). Unfortunately,
the resulting optimised designs often consist of scattered metallic parts and
exhibit bad performance24.
To relax the strong selfpenalisation, we use a filtering approach that
imposes some intermediate conductivities inside the design domain during the
initial phase of the optimisation. To do so, we replace pi by qi in expression
(6), where the vector q?=?Kp, in which the filter matrix K is a discrete
approximation of an integral operator with support over a disc with radius R.
The filter replaces each component in the vector p by a CCTV
coaxial cable weighted average of the neighbouring components, where the
weights vary linearly from a maximum value at the center of the disc to zero at
the perimeter. To avoid lossy final designs, we solve optimisation problem (7)
through a series of subproblems, where after the solution of subproblem n, the
filter radius is reduced by setting Rn+1?=?0.8?Rn. We start with a filter radius
R1?=?40Δ, where Δ denotes the FDTD spatial discretization step. Each subproblem
is iteratively solved until a stopping criterion for optimisation, based on the
firstorder necessary condition, is satisfied. To update the design variables,
we use the globally convergent method of moving asymptotes (GCMMA)33.
We investigate the design of transitions between a 50?Ohm coaxial CCTV
coaxial cable (probe diameter 1.26?mm, outer shield diameter 4.44?mm) and
and two standard waveguides; the WR90 (a?=?22.86?mm and b?=?10.16?mm) and the
WR430 waveguides (a?=?109.22?mm and b?=?54.61?mm). The first cutoff frequency of
the WR90 waveguide is f10?=?6.56?GHz and the second is f20?=?13.12?GHz, while
the WR430 waveguide has f10?=?1.37?GHz and f20?=?2.75?GHz. The frequency band of
interest in both cases is the band between the first and the second cutoff
frequencies, where only the TE10 mode can propagate (below, we refer to this
bandwidth as the bandwidth objective). These frequency bands correspond to a
relative bandwidth of 66.7% for the WR90 waveguide and 67.0% for the WR430
waveguide. In our numerical experiments, we use uniform FDTD grids. For the WR90
waveguide we use a spatial step size Δ?=?0.127?mm, and for the WR430 waveguide
Δ?=?0.607?mm. In both cases, a 16 cell perfectly matched layer (PML) is used to
terminate the waveguide and 15 cells of free space separate the end of the
design domain and the beginning of the PML. We use an inhouse FDTD code
implemented to run on graphics processing units (GPU) using the parallel
computing platform CUDA (https://developer.nvidia.com/whatcuda). One solution
to Maxwell’s equations takes around 5?minutes and around 4?GB of memory is
required for computing the objective function gradient. The waveguide walls and
the coaxial probe are assigned a conductivity value of σ?=?5.8?×?107?S/m.




http://blog.51.ca/u709670/2017/05/27/americanshujinakamurashownhereinanundatedphoto/




Things You Might Not Know About Charles Darwin This Sunday, Feb. 12, is , an
international day of celebration LED Canopy Light
commemorating the birth of Charles Darwin and his contributions to
science. It's also an excuse for science and evolutionthemed around the
globe, and for all of us to take a moment to appreciate the value of science and
the wonders of the natural world. As you prepare to celebrate, here are a few
things you might want to know about Darwin — some insights new and old to
impress your friends and family. 1. Darwin developed the Theory of Evolution
by Natural Selection. Studies consistently find that many Americans — including
college students and even preservice teachers — critical features of how the
process works. You can read through common misconceptions , or review the key
ingredients for natural selection — heritable variation that leads to
differential reproduction — in this easy created for 13.7. 2. Darwin wasn't
only a meticulous observer of the natural world, he was also a careful reader
and a diligent recordkeeper when it came to his own habits. Beginning in 1838,
Darwin kept a notebook in which he recorded the books he was reading. From 1837
to 1860, he reported reading 687 distinct works of English nonfiction. These
years span an important period in the development LED Canopy Light
of his thinking, from his return to England from the Galapagos Islands to
the publication of .




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