text:
The Great American Dream Machine was a weekly satirical variety television series, produced in New York City by WNET and broadcast on PBS from 1971 to 1972. The program was hosted by humorist and commentator Marshall Efron. Other notable cast members included Chevy Chase and contributors included Albert Brooks, Paul Jacobs, Studs Terkel, and Andy Rooney. The show centered on skits and satirical political commentary. The show was originally 90 minutes long and usually covered at least seven different current event topics. In the second season, the show was reduced to an hour.

Titles
The show began and ended with patriotic marching music and red, white, and blue GREAT AMERICAN DREAM MACHINE lettering, striped like an American flag. There was an animated "machine" of sorts, with complex moving parts, that had no evident function. The title theme was composed and performed by Steve Katz of Blood, Sweat & Tears fame.

Features
Some of the skits would later be revamped for the movie The Groove Tube.
There were also occasional short films presented on the show, most of them "experimental" or documentaries about artistic endeavours. Some of these were subtitled.

Each week there was a Great American Hero segment.  One week was Evel Knievel; played over Evel's hospital footage was a honky-tonk song about putting body parts back together. The song was written and performed by Martin Mull.

Consumerism
Efron also participated in some skits, especially those taking a critical look at consumerism. One notable skit focused on the different size descriptions on cans of food, that at a time prior to significant government regulation and standardization of labels.  Efron sarcastically compared cans of olives with sizes like "Giant", "Jumbo", "Extra Jumbo", "Super Jumbo", "Colossal", "Super Colossal" and "Gargantuan." While the other sizes were really used in retail, "Gargantuan" was not. The "Gargantuan" can contained one olive that filled the entire can.

Another piece involved Efron attempting to cook a lemon cream pie by using the largely artificial ingredients found listed on a box of Morton frozen lemon cream pie. The final result contained, in his words, "No lemons. No eggs. No cream. Just pie." The skit inspired a  cease and desist letter from the Morton company's lawyers, but the producers of the show aired the skit again after verifying that it was factual. According to Efron, the company subsequently changed the recipe to replace artificial flavorings with concentrated lemon juice.

Another piece had Efron taking the audience on a tour of his apartment, in a "non-event" style that was very much ahead of its time.  He presented his "stuffed cat", which proceeded to wake up and look around.

A memorable segment trumpeted the trash compactor appliance.  Efron's tagline: "The machine that turns 20 pounds of trash into 20 pounds of trash!"

Reception
John Lennon praised the show in a 1972 radio interview, saying "But this Great American Dream Machine that they have on [New York-area public TV station] Channel 13 is as good as, if not better than, anything that's on British TV, including Monty Python's Flying Circus, which is not as heavy as the Dream Machine".

DVD release
A 4-DVD set from S'More Entertainment, featuring most of the episodes of this series (given at a length of 777 minutes, or approximately 13 hours), was released on September 29, 2015.

References

External links
 TV.com: The Great American Dream Machine

PBS original programming
1970s American satirical television series
1970s American variety television series
1971 American television series debuts
1972 American television series endings
Television series by WNET


text:
May 2, 2016 — American / Projects / Truck & 4x4 | 9 Comments
Rare Cameo Carrier: 1957 Chevrolet Task Force Driving Project
This Chevrolet Cameo Carrier is one of just ~10,000 made over a four year production run that ended in 1958. Though based on the standard Task Force line of pick-ups, the Cameo offered a smooth-side, fiberglass skinned bed and a fatter options list, designed as it was to appeal to a new, less work-focused market for light duty trucks. Though ultimately unsuccessful, Chevy deserves credit for predicting the future of pick-ups, if at least 30 years too early. This one runs and drives well, and though all Cameo-specific trim is included, the seller admits to a previous owner performing a so-so restoration. Still, the truck does look to have a lot of potential, and bidding remains under $1k at the time of writing. Find it here on eBay in Sheridan, Wyoming, with reserve not met.
Most light duty pick-ups of the era came standard with flare-side beds, though the Cameo and equivalent GMC Suburban Carrier were fitted with full-length fiberglass outer bed panels instead. Note the cool tailfin treatment and Cameo-specific tailgate, the latter of which was also skinned in fiberglass. The seller says that this truck was sold new in California, later landing with an older owner who gave it a "Walmart makeover." The exterior has worn this coat of primer for at least five years, but the seller notes that all trim–including any seen missing here–is included separately.
Here's a direct shot of the tailgate. The bumper and overriders should be painted body color, though chrome end caps are correct.
The interior is said to have been redone a few years ago, but work doesn't look to have consisted of much more than a rattle can red spray job and new upholstery, the latter of which looks quite decent actually.
Up front, the 350 is described as "beefed-up," though no other specifics are provided. The air cleaner, carb, and Mickey Thompson rocker covers are all clearly aftermarket however, and the seller says that the truck runs and drives well. Power is shuffled through a column-shifted 3-speed manual as seen above.
Properly fixed-up, this truck could be a real stunner. Hopefully it finally gets the attention it deserves.

redpajama_set_name: RedPajamaCommonCrawl


For many years now I've always been using X-Chat whenever I wanted to go on IRC. First under Linux (with some small side-trips to BitchX) and since 2 years now on OSX thanks to the X-Chat Aqua port. Yesterday MacApper ran a story about Linkinus, a relatively new IRC client by Nicolas Lapomarda, that tries to revive the IRC market on Apple's operating system.
Besides X-Chat there is only Colloquy from the open source community, that doesn't have any kind of proxy support, which is simply essential to me … besides: I really don't like its UI ;-) And Limechat is a bit to minimalistic for me. When you look at the commercial front, you have Xirc, which is dead (and remarkably went dead only a year after going commercial, which is exactly what I always fear when I pay for software) among a load of other apps in the < 30 USD price range. macirc has a really great listing in this regard.
The problem is, none of them really convinced me since no one really offered anything new compared to what X-Chat had to offer … except Linkinus. First of all: Linkinus offers a really nice and clean user interface with keyboard navigation for basically everything. But for me the really important thing about it is the split view. Think a light version of what VI has to offer here. You can horizontally split the main window to keep an eye on multiple channels. And all you have to do is how ctrl on the keyboard while selecting the channels from the sidebar. Yes, I know. Quite a few of the terminal based IRC clients have something like that, but this is the first GUI client I've seen so far, that let's you split the main view.


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text:
\section{Introduction}
\label{intro}

Among the many potential applications of agent-based models whose
pattern of interactions is represented by a network, a broad class
is constituted by systems where that pattern is not a static
structure, but evolves in response to the changing state of the
agents. Generally, the evolution of the interaction network and the
dynamics of individual agents  occur over different time scales. For
instance, in  learning processes --such a those implemented in real
and artificial neural networks \cite{learning}--  connections change
adaptively over scales that are large as compared with the internal
dynamics of agents. At the opposite limit, in models of network
growth, the pattern evolves in the absence of any dynamics related
to agents at the network nodes \cite{growth}.

When, on the other hand, the dynamical time scales of a population
of agents and its interaction network are comparable, we can speak
about their {\em coevolution}. Consider, for instance, agents
involved in a cooperation-defection game, such as in the prisoner's
dilemma \cite{zim}, where defected agents are given the opportunity
of breaking the connection with their defectors, in such a way that
no further interaction is possible between them. Or, in a process of
opinion diffusion, that agents which do not succeed at reaching an
agreement may elude mutual contacts in the future
\cite{stau,gil1,gil2,holme}. In such cases, a realistic assumption
would be that the breaking of interaction links occurs just after a
few, or even one of, such events.

In this talk, we explore a model of agent-network coevolution in a
population where an infection is spreading, such that non-infected
agents are given the possibility of avoiding contact with their
infected partners --perhaps in response to risk perception
\cite{risk}. The model is based on an SIS epidemiological process,
where each agent can be susceptible (S) or infected (I). We recall
that in the standard SIS process each infected agent recovers and
becomes susceptible at a fixed rate, say, with probability $\gamma$
per unit time. Susceptible agents, in turn, become infected by
contagion from infected agents, at a rate proportional to the
infection probability per unit time, $\rho$, and to the fraction of
infected agents, $n_{\rm I}$. Within a mean-field description of the
standard SIS model, the fraction of infected agents obeys
\begin{equation} \label{sis0}
\dot n_{\rm I}  = -\gamma n_{\rm I} + \rho n_{\rm I} n_{\rm S},
\end{equation}
where $n_{\rm S}=1-n_{\rm I}$ is the fraction of susceptible agents.
In this description, for asymptotically long times, $n_{\rm I}$
vanishes if $\rho \le \gamma$. Therefore, the infection is
suppressed as time elapses. If, on the other hand, $\rho > \gamma$,
the fraction of infected agents approaches a finite value
$n_I^*=1-\gamma/\rho>0$, and the infection is endemic. The
transition between these two regimes occurs through a transcritical
bifurcation.

We introduce in the following an implementation of the SIS model on
a network, with agents occupying the nodes and contagion taking
place along the links. A susceptible agent can become infected only
if it is connected to an infected agent. Moreover, susceptible
agents have the opportunity, with a certain probability, of breaking
their connection with an infected partner before contagion takes
place, and reconnect the broken link with any other agent in the
population. We show that these reconnection events are able to
control infection spreading, even to the point of completely
suppressing the infection as the reconnection probability grows.
This suppression is achieved with a moderate decrease in the number
of network connections per infected agent.

\section{Model and mean-field formulation}
\label{model}

The present model is a variation of the model introduced by Gross
{\it et al.} \cite{thg}.
 Consider a population of $N$ agents at the nodes of a network
with $M$ links. The average number of neighbours per agent is
$z=2M/N$. At a given time, each agent can be in one of two states:
susceptible (S-agent) or infected (I-agent). Initially, the $M$
links are distributed at random over the population, and there is a
certain fraction of agents in each state.

Each evolution step is divided into two sub-steps. In the first
sub-step, an agent is chosen at random from the whole population. If
it is infected, it recovers with probability $\gamma$, and becomes
susceptible. In the second sub-step, a pair of linked agents is
chosen at random. If both agents are susceptible or infected,
nothing happens. Otherwise, the S-agent is given the chance to break
the link with its infected neighbour and reconnect it with another
agent, taken at random from the remaining of the population. This
rewiring happens with probability $r$. Finally, if the rewiring has
not occurred, the S-agent becomes infected with probability
$\lambda$.

A time unit contains $N$ evolution steps. Thus, each I-agent has a
probability $\gamma$ per time unit of becoming susceptible, so that
the mean duration of the infection period is $\gamma^{-1}$.
Moreover, each S-agent in contact with an I-agent becomes in turn
infected with probability $2 (1-r) \lambda$ per time unit.

\subsection{Mean-field equations}

Although, clearly, the model is defined bearing in mind its
implementation as a numerical simulation, a formulation in terms of
differential equations, from mean-field arguments, turns out to give
an essentially correct description of the system. To define our
mean-field formulation, we first introduce a suitable set of
variables. We call $N_{\rm I}$ and $N_{\rm S}$ the number of
infected and susceptible agents, respectively. They satisfy $N_{\rm
I}+N_{\rm S}=N$. Moreover, we  denote by $M_{\rm II}$, $M_{\rm IS}$,
and $M_{\rm SS}$, respectively, the number of network links joining
two infected agents (II), an infected agent and a susceptible agent
(IS), and two susceptible agents (SS). Since the total number of
links is preserved by the dynamical rules, we have $M_{\rm
II}+M_{\rm IS}+M_{\rm SS}=M$ constant at all times. Differential
equations will be formulated for the fractions $n_{\rm I} = N_{\rm
I}/N$, $m_{\rm II}=M_{\rm II}/M$, and $m_{\rm IS}=M_{\rm IS}/M$. The
conservation of the number of agents and links implies $n_{\rm
S}=N_{\rm S}/N = 1-n_{\rm I}$ and $m_{\rm SS}=M_{\rm SS} /M
=1-m_{\rm II}-m_{\rm IS}$.

The evolution of the above defined quantities is given by the events
of infection and recovery, and by the reconnection of links. When,
for instance, an I-agent becomes susceptible, there is not only a
decay in the fraction of I-agents, but also a change in the
fractions $m_{\rm II}$ and $m_{\rm IS}$. In fact,  the links joining
the recovered agent with I and S-agents pass, respectively, from the
II-type to the IS-type, and from the IS-type to the SS-type. A
symmetric situation occurs when an S-agent becomes infected. The
number of links of each type associated to a given agent is
calculated using mean-field-like averages. For instance, the number
of II-links associated to an I-agent is estimated as $2M_{\rm II} /
N_{\rm I} = z m_{\rm II}/n_{\rm I} $, where $z=2M/N$ is the overall
average number of links per agent. Similarly, the number of IS-links
associated to an I-agent is taken to be $M_{\rm IS} /  N_{\rm I} = z
m_{\rm IS}/2n_{\rm I}$. Reconnection events, in turn, can change an
IS-link into an SS-link. The probability for this change is
proportional to the fraction of S-agents in the whole population and
to the reconnection probability $r$. Finally, it has to be taken
into account that both infection and reconnection only occur when an
IS-link is selected, so that their probabilities are proportional to
$m_{\rm IS}$.

Putting all these considerations together, the evolution equations
for $n_{\rm I}$, $m_{\rm II}$, and $m_{\rm IS}$ read
\begin{equation} \label{sisn}
\begin{array}{ll}
n_{\rm I}' = &-n_{\rm I}+ \tilde \lambda m_{\rm IS} ,\\
m_{\rm II}' =& -2 m_{\rm II} +\tilde \lambda m_{\rm IS}^2/(1-n_{\rm I}), \\
m_{\rm IS}' =& 2m_{\rm II}-m_{\rm IS}- \tilde r (1-n_{\rm I}) m_{\rm IS} \\
& +\tilde \lambda m_{\rm IS}(2-2m_{\rm II}-3m_{\rm IS})/(1-n_{\rm
I}),
\end{array}
\end{equation}
with $\tilde \lambda = (1-r) \lambda /\gamma$ and $\tilde r =2r/ z
\gamma$. Primes indicate differentiation with respect to the
rescaled time $t'=\gamma t$. In this formulation, thus, the inverse
recovery probability $\gamma^{-1}$ fixes an overall time scale, and
the infection and reconnection probabilities are accordingly
redefined as $\tilde \lambda$ and $\tilde r$, which are the only two
parameters left. Note that $\tilde \lambda$ depends on both
$\lambda$ and $r$, and that $\tilde r$ incorporates the only
network-specific parameter, namely, the average connectivity per
agent $z=2M/N$.

In the absence of reconnection events, $r=0$, and provided that we
put $m_{\rm II}=n_{\rm I}^2$ and $m_{\rm IS}=2n_{\rm I}n_{\rm
S}=2n_{\rm I}(1-n_{\rm I})$, the three lines in Eq. (\ref{sisn})
collapse into
\begin{equation}
n_{\rm I} ' = -n_{\rm I} +2 \tilde \lambda n_{\rm I} (1-n_{\rm I}).
\end{equation}
Rewriting this equation in terms of the non-normalized parameters,
we reobtain the mean-field equation (\ref{sis0})  for the SIS model,
with $\rho=2\lambda$. The factor of $2$ relating the infection
frequencies $\rho$ and $\lambda$ originates in the fact that, in our
implementation of the SIS model on a network, each agent is (on the
average) chosen twice per unit time to possibly become infected.

\subsection{Infection level at equilibrium}

We focus the attention on the equilibrium solutions of Eqs.
(\ref{sisn}), which are the candidates to represent the infection
level and network structure at asymptotically long times. First, we
consider the stationary values of the fraction of infected agents.
The analysis is restricted to the case of $\tilde \lambda>1/2$
which, in the absence of reconnection events, corresponds an endemic
infection where a finite fraction of the population is infected at
all times, $n_{\rm I} > 0$ for $t \to \infty$.

At the fixed points of the dynamical equations (\ref{sisn}), the
equilibrium fraction of links $m_{\rm II}^*$ and $m_{\rm IS}^*$ are
related to the equilibrium fraction of infected agents $n^*_{\rm I}$
as
\begin{equation} \label{ms}
m_{\rm II}^*=\frac{n^{*2}_{\rm I}}{2\tilde \lambda (1-n^*_{\rm I})},
\ \ \ \ \ \ \ \ m_{\rm IS}^*= \frac{n^*_{\rm I}}{\tilde \lambda}.
\end{equation}
In turn, $n^*_{\rm I}$ satisfies
\begin{equation} \label{ni0}
0= n_{\rm I}^* \left[ 2\tilde \lambda -1-\tilde r +(3\tilde
r-2\tilde \lambda) n_{\rm I}^* -3\tilde r n_{\rm I}^{*2} +\tilde r
n_{\rm I}^{*3} \right].
\end{equation}
This polynomial equation has four solutions. One of them tends to
infinity for $\tilde r \to 0$, and remains real and larger than one
for any positive $\tilde r$. Since meaningful solutions to our
problem must verify $n_{\rm I}^*\le 1$, we disregard this solution
from now on.

The trivial solution $n_{\rm I}^{(0)}=0$ exists for any value of the
normalized infectivity $\tilde \lambda$ and of the normalized
reconnection probability $\tilde r$. For a given $\tilde \lambda$,
its stability depends on $\tilde r$. As discussed in more detail
below, $n_{\rm I}^{(0)}=0$ is unstable for small $\tilde r$ and
becomes stable as $\tilde r$ grows. The other two solutions read
\begin{equation} \label{n12}
n_{\rm I}^{(1,2)} = 1-\sqrt{\frac{2\tilde \lambda}{3\tilde r}}
\left[ \cos \frac{\alpha}{3} \mp \sqrt{3} \sin \frac{\alpha}{3}
\right]
\end{equation}
with
\begin{equation}
\alpha = \arctan \sqrt{\frac{32 \tilde \lambda^3}{27 \tilde r}-1}
\end{equation}
($0\le \alpha \le \pi/2$). These two solutions are real for $32
\tilde \lambda^3 \ge 27 \tilde r$. Otherwise, they are complex
conjugate numbers. The solution $n_{\rm I}^{(1)}$, with the minus
sign in the right-hand side of Eq. (\ref{n12}), approaches
$1-(2\tilde \lambda)^{-1}$ for $\tilde r \to 0$. Thus, it represents
the expected fraction of infected agents in the absence of
reconnection. When it is real, it satisfies $n_{\rm I}^{(1)}<1$, and
it is stable as long as it remains positive. Consequently, along
with the trivial solution, $n_{\rm I}^{(1)}$ is another meaningful
equilibrium solution to our problem. Finally, $n_{\rm I}^{(2)}$ is
negative and stable for small $\tilde r$. Depending on  $\tilde
\lambda$, it can become positive as $\tilde r$ grows but, at the
same time, it becomes unstable. Therefore, it does not represent a
meaningful solution.

\begin{figure}
\resizebox{\columnwidth}{!}{\includegraphics*{fig1.eps}} \vspace*{15
pt}
 \caption{ Bifurcation diagram for the equilibrium fraction
of infected agents $n_{\rm I}^*$ as a function of the normalized
reconnection probability $\tilde r$, for three normalized
infectivities $\tilde \lambda$. Although only positive values of
$n_{\rm I}^*$ are meaningful, an interval in the negative domain is
also shown for completeness.  Full and dotted lines represent,
respectively, stable and unstable branches. For clarity, the
solution $n_{\rm I}^{(0)}=0$ is plotted in the vicinity of the
transcritical bifurcation only.} \label{fig1}
\end{figure}

Figure \ref{fig1} summarizes, in a bifurcation diagram, the
behaviour of $n_{\rm I}^{(0)}$, $n_{\rm I}^{(1)}$, and $n_{\rm
I}^{(2)}$ as functions of the normalized reconnection probability
$\tilde r$, for three representative values of the normalized
infectivity $\tilde \lambda$. In the three cases, we have $\tilde
\lambda>1/2$, so that --as discussed above-- a non-trivial
meaningful solution does exist. Full and dotted lines represent,
respectively, stable and unstable branches. For small infectivity
($\tilde \lambda = 0.6$), the stable solution $n_{\rm I}^{(1)}$
crosses $n_{\rm I}^{(0)}$ and becomes negative and unstable, while
$n_{\rm I}^{(0)}$ becomes stable. This transcritical bifurcation
takes place at $\tilde r = 2\tilde \lambda -1$. As $\tilde r$ grows
further,  $n_{\rm I}^{(1)}$ and the negative stable solution $n_{\rm
I}^{(2)}$ approach each other, and collide when $n_{\rm I}^{(1)} =
n_{\rm I}^{(2)}= 1-3/4\tilde \lambda$. Beyond this tangent
bifurcation, which takes place at $\tilde r = 32 \tilde \lambda^3 /
27$, the two solutions are complex numbers.

The situation is different for larger infection probabilities, as
illustrated by Fig. \ref{fig1} for $\tilde \lambda=1$. Now, for
$\tilde r=0$,  $n_{\rm I}^{(1)}$ is large and, as $\tilde r$ grows,
it is the stable negative solution $n_{\rm I}^{(2)}$ which first
reaches $n_{\rm I}^{(0)}$. At the transcritical bifurcation at
$\tilde r = 2\tilde \lambda -1$, $n_{\rm I}^{(2)}$ becomes positive
and unstable, and $n_{\rm I}^{(0)}$ becomes stable. The tangent
bifurcation where $n_{\rm I}^{(1)}$ and $n_{\rm I}^{(2)}$ collide
and become complex, at $\tilde r = 32 \tilde \lambda^3 / 27$, takes
now place when these two solutions are positive. As a consequence,
there is an interval of normalized reconnection probabilities,
between the two bifurcations, where the system is bistable: both
$n_{\rm I}^{(0)}$ and $n_{\rm I}^{(1)}$ are stable meaningful
solutions to the problem. The asymptotic state is selected by the
initial condition for $n_{\rm I}$, and $n_{\rm I}^{(2)}$ stands at
the boundary between the two attraction basins.

The regimes of small and large infectivity are separated by the
critical value $\tilde \lambda =3/4=0.75$, also shown in Fig.
\ref{fig1}. At this critical point, the transcritical and the
tangent bifurcation collapse into a  pitchfork bifurcation at
$\tilde r = 1/2$. Here, the three equilibria collide simultaneously,
and $n_{\rm I}^{(0)}$ becomes stable, while the other two solutions
become complex.

\begin{figure}
\resizebox{\columnwidth}{!}{\includegraphics*{fig2.eps}} \vspace*{15
pt} \caption{Phase diagram in the $(\tilde r, \tilde
\lambda)$-plane, showing the regions of infection suppression
($n_{\rm I} \to 0$) and persistence ($n_{\rm I} \to n_{\rm
I}^{(1)}$), and the intermediate bistability zone. Their boundaries
are given by the transcritical (TC) and the tangent (Tg) bifurcation
lines, which collapse into a pitchfork bifurcation (P) at
$(1/2,3/4)$. The dotted line is the continuation of the tangent
bifurcation line in the zone where $n_{\rm I}^{(1)}$ is negative.
The inset shows the same phase diagram in terms of the
non-normalized parameters $r$ and $\lambda$, for $\gamma=0.01$ and
$z=10$. } \label{fig2}
\end{figure}

A phase diagram of our system over the parameter plane ($\tilde
r,\tilde \lambda$) is shown in Fig. \ref{fig2}. The zones of endemic
infection, where the fraction of infected agents at asymptotically
long times is positive ($n_{\rm I}\to n_{\rm I}^{(1)}$), and of
infection suppression ($n_{\rm I}\to 0$) are separated, for large
$\tilde \lambda$ and $\tilde r$, by the bistability region, where
both asymptotic behaviours can be obtained, depending on the initial
condition. The three zones are limited by the lines of the
transcritical bifurcation [$\tilde \lambda = (1+\tilde r)/2$, TC],
where $n_{\rm I}^{(0)}=0$ changes its stability, and of the tangent
bifurcation [$\tilde \lambda = (27 \tilde r/32)^{1/3}$, Tg] where
$n_{\rm I}^{(1)}$ and $n_{\rm I}^{(2)}$ collide and become complex.
These two lines are tangent to each other at the ``triple point''
$(1/2,3/4)$, where the bistability region disappears, and the system
undergoes a pitchfork bifurcation [P]. For smaller $\tilde \lambda$
and $\tilde r$ bistability is no more possible, and the zones of
infection persistence and suppression are separated by the
transcritical line. The tangent bifurcation takes now place at
negative values of $n_{\rm I}^{(1)}$ and $n_{\rm I}^{(2)}$ (dotted
line).

The inset of Fig. \ref{fig2} shows the same phase diagram in terms
of the original, non-normalized reconnection and infection
probabilities, $r$ and $\lambda$, for a recovery probability
$\gamma=0.01$ over a network with an average of $z=10$ neighbours
per site.  Note that the relation between non-normalized and
normalized parameters is not a mere change of scale, because both
$r$ and $\lambda$ enter the definition of $\tilde \lambda$.

Let us summarize our results on the persistence or suppression of
the infection in terms of the non-normalized parameters. First, for
small infectivity, $\lambda \le \gamma/2(1-r)$, the infection is
always suppressed. In this situation, the infectivity is just too
small to sustain a finite infected population. For larger
infectivities, on the other hand, the infection can become
established, depending on the reconnection probability $r$. In the
range $\gamma/2(1-r) <\lambda <3\gamma/4(1-r)$, the infection is
endemic if reconnections are infrequent, $r<z(\lambda-\gamma/2)/(1
+z \lambda)$. Otherwise, for sufficiently frequent reconnections,
the infection dies out. The transition between both situations is
continuous in the fraction of infected agents, and occurs through a
transcritical bifurcation. For even larger infection probabilities,
$\lambda >3\gamma/4(1-r)$, the regimes of persistence (low $r$) and
suppression (large $r$) are separated by a bistability zone, where
the infection persists or dies out depending on the initial fraction
of infected agents. The bistability zone is limited by the
transcritical bifurcation quoted above and a tangent bifurcation at
a reconnection probability given by the solution to $27 \gamma^2 r=
16 (1-r)^3 \lambda^3$. The discontinuous nature of the tangent
bifurcation implies that the endemic state present in the
bistability zone disappears abruptly at the boundary, with a finite
jump in the asymptotic fraction of infected agents, from $n_{\rm I}
= 1-\sqrt{z(1-r)\lambda/3r}>0$ to zero.

\begin{figure}
\resizebox{\columnwidth}{!}{\includegraphics*{fig3.eps}}\vspace*{15
pt} \caption{ Connectivity of infected and susceptible agents,
$z_{\rm I}$ and $z_{\rm S}$, relative to the overall connectivity
$z=2M/N$, for three values of the normalized infectivity $\tilde
\lambda$, as functions of the normalized reconnection probability
$\tilde r$.  Only the values corresponding to meaningful stable
solutions for the fraction of infected agents at plotted. The
connectivity of infected agents is not plotted beyond the threshold
of infection suppression. The vertical dashed line represents the
finite jump in $z_{\rm S}$ at the tangent bifurcation where the
solution $n_{\rm I}^{(1)}$ disappears.} \label{fig3}
\end{figure}

\subsection{Number of neighbours of infected and susceptible agents}

The variables $m_{\rm II}$ and $m_{\rm IS}$ characterize how the
structure of the network is related to the state of the agents.
Reconnection events favor the growth of the number of SS-links at
the expense of IS-links. Thus, for $r>0$, S-agents should
asymptotically posses relatively large numbers of neighbours. The
equilibrium values  $m_{\rm II}^*$ and $m_{\rm IS}^*$ as functions
of the equilibrium fraction $n_{\rm I}^*$ of I-agents are given by
Eqs. (\ref{ms}). These equations show, as expected, that the
fraction of links connecting I-agents with any other agent is
proportional to the fraction of I-agents itself.

In order to introduce quantities that define the connectivity of
I-agents and S-agents independently of their respective fractions,
we consider the average number of neighbours per agent of each type.
For I-agents, for instance, the average numbers of infected and
susceptible neighbours are $2M_{\rm II}/N_{\rm I}$ and $M_{\rm
IS}/N_{\rm I}$, respectively. The average connectivity of I-agents,
$z_{\rm I}$, is the sum of these two quantities or, equivalently,
\begin{equation}\label{zi}
\frac{z_{\rm I}}{z} = \frac{1}{2\tilde \lambda (1-n_{\rm I}^*)},
\end{equation}
which gives the ratio between $z_{\rm I}$ and the overall average
connectivity per agent at equilibrium. With analogous arguments for
S-agents, their average connectivity reads
\begin{equation} \label{zs}
\frac{z_{\rm S}}{z} = \frac{1}{1-n_{\rm I}^*}-\frac{n_{\rm
I}^*}{2\tilde \lambda (1-n_{\rm I}^*)^2} .
\end{equation}
Due to the conservation of the total number of links, $z_{\rm I}$
and $z_{\rm S}$ are univocally related. This relation can be
obtained from Eqs. (\ref{zi}) and (\ref{zs}) by eliminating $n_I^*$,
which yields
\begin{equation}
z_{\rm S} = z_{\rm I}[1+2\tilde \lambda (1-z_{\rm I}/z)].
\end{equation}
In order to describe the correlation between the structure and the
state of the population it is however useful to analyze both $z_{\rm
I}$ and $z_{\rm S}$ as functions of the relevant parameters. Figure
\ref{fig3} illustrates the behaviour of $z_{\rm I}$ and $z_{\rm S}$,
as described in the following, for the infection probabilities
$\tilde \lambda$ already considered in Fig. \ref{fig1}.

For $n_{\rm I}^* = n_{\rm I}^{(1)}$, which stands for the stable
equilibrium solution for low reconnection probabilities, both
$z_{\rm I}$ and $z_{\rm S}$ approach $z$ as $\tilde r \to 0$. As
expected, in the absence of reconnection events, there is no
difference in the number of neighbours of infected and susceptible
agents. Also, as $\tilde r$ grows from zero, we have $z_{\rm
I}<z<z_{\rm S}$. We verify that reconnection tends to increase the
connectivity of S-agents at the expense of I-agents.

The other solution relevant to the epidemiological process, $n_{\rm
I}^*=n_{\rm I}^{(0)}=0$, corresponds to a purely susceptible
population. Accordingly, we find $z_{\rm S}=z$. Note also that Eq.
(\ref{zi}) predicts $z_{\rm I} = z/2\tilde \lambda$, but this value
is never realized due to the total absence of I-agents in this
state.

For $\tilde \lambda \le 3/4$, the fraction of I-agents decreases
monotonically with $\tilde r$ and vanishes continuously at the
transcritical bifurcation --or, for $\tilde \lambda = 3/4$, at the
pitchfork bifurcation. The connectivity of S-agents is $z_{\rm S}
=z$ both at $\tilde r=0$ and at the bifurcation. For intermediate
values of the reconnection probability $z_{\rm S}$ is larger than
$z$ and attains a maximum. This maximum, which at first sight may
result to be surprising, can be easily explained. In fact, to
sustain a value of $z_{\rm S}$ larger than the overall average $z$,
it is necessary to have I-agents with a relatively low number of
neighbours. As the infection is progressively suppressed by
reconnection, the number of I-agents decreases and, accordingly,
their contribution to the average number of neighbours per agent
becomes less significant. At the bifurcation and beyond, S-agents
must account for the whole average, so that $z_{\rm S}$  returns to
its value for $\tilde r=0$, i.e. $z_{\rm S}=z$.

The connectivity of I-agents, in turn, is a monotonically decreasing
function of $\tilde r$, and reaches $z_{\rm I}=z/2\tilde \lambda <z$
at the bifurcation. This implies that, even at the threshold of
infection suppression, I-agents maintain a finite number of
neighbours within the population.

For $\tilde \lambda > 3/4$, again, the connectivity $z_{\rm S}$
associated with the solution $n_{\rm I}^{(1)}$ initially increases
with $\tilde r$, and attains a maximum. In the subsequent decay,
however, it does not reach $z_{\rm S}=z$. In fact, $n_{\rm I}^{(1)}$
disappears through a tangent bifurcation when it is still positive,
so that the jump in the infection level is discontinuous. At the
bifurcation, we find  $z_{\rm S}= 2z(2\tilde \lambda +3)/9>z$. The
connectivity of I-agents decreases with $\tilde r$ and, at the
bifurcation, its value is independent of $\tilde \lambda$: $z_{\rm
I}=2/3$.

From the viewpoint of the interplay of the epidemiological dynamics
and the structure of the underlying network, the most interesting
result of this section is the fact that the infection dies out even
when infected agents keep a substantial connectivity with the rest
of the population. In the cases illustrated in Fig. \ref{fig3}, for
instance, infected agents preserve more than $60$ \% of their
connections at the threshold where the infection level vanishes. In
other words, reconnection needs not to completely isolate infected
agents to suppress the infection. A moderate, partial isolation of
the infected population is enough to asymptotically inhibit the
endemic state.

\section{Discussion and conclusion}

What mechanisms are at work when the infection is suppressed by
reconnection, even when the connectivity of infected agents remains
fairly high? To advance an answer to this question, it helps to
consider a simpler dynamical system for the fraction of I-agents:
\begin{equation} \label{eff}
n_{\rm I}'=-n_{\rm I} +[2 \tilde \lambda - \tilde r (1-n_{\rm I})^2
]n_{\rm I} (1-n_{\rm I}).
\end{equation}
The right-hand side of this equation is just a rearrangement of that
of Eq. (\ref{ni0}). The equilibria of Eq. (\ref{eff}) are thus
identical to the equilibria for $n_{\rm I}$ in Eqs. (\ref{sisn}).
Moreover, their stability properties are also the same as in our
original system. It is important to understand, however, that
(\ref{eff}) and (\ref{sisn}) are not equivalent: they merely share
the same equilibrium behaviour in which regards the fraction of
I-agents.

We immediately see that Eq. (\ref{eff}) can be put in the form of
the standard mean-field equation (\ref{sis0}) for a SIS process if
we introduce the effective infection probability
\begin{equation}
\rho_{\rm eff} = \gamma [2 \tilde \lambda - \tilde r (1-n_{\rm I})^2
]= 2 (1-r)\lambda -\frac{2r}{z} (1-n_{\rm I})^2.
\end{equation}
In Eq. (\ref{sis0}) the threshold of infection suppression, where
the trivial equilibrium  changes its stability, is given by
$\rho=\gamma$. Imposing this same condition to $\rho_{\rm eff}$, we
find $\tilde r = 2\tilde \lambda-1$. But this is precisely the
suppression threshold in the system with reconnections. Therefore,
with respect to the stabilization of the trivial equilibrium, the
system (\ref{sisn}) is effectively equivalent to the standard SIS
model with infectivity $\rho_{\rm eff}$. The transcritical
bifurcation of Eqs. (\ref{sisn}), where $n_{\rm I}^{(0)}=0$ becomes
stable, can be interpreted as a kind of continuation for $r \neq 0$
of the transcritical bifurcation of the SIS model without
reconnection events.

The interpretation of the tangent bifurcation where the endemic
state disappears at a positive value of $n_{\rm I}^{(1)}$, for
$\tilde \lambda >3/4$, is less direct. It can however be argued that
the presence of such a tangent bifurcation, together with the
transcritical bifurcation which stabilizes the trivial equilibrium,
constitute the generic critical behaviour expected for a SIS model
like Eq. (\ref{eff}), with an infection probability which depends on
the density of I-agents:
\begin{equation} \label{eff0}
n_{\rm I}'=-n_{\rm I} + \rho (n_{\rm I}) n_{\rm I} (1-n_{\rm I}).
\end{equation}
Besides the trivial equilibrium, this equation has fixed points at
the solutions of
\begin{equation} \label{eff1}
\rho (n_{\rm I}^*) = (1-n_{\rm I}^*)^{-1}.
\end{equation}
Figure \ref{fig4} illustrates graphically two representative
situations. The dotted curve is the graph of the right-hand side of
Eq. (\ref{eff1}) as a function of $n_{\rm I}^*$. If the graph of
$\rho (n_{\rm I}^*)$ has a single intersection with the dotted curve
(A) and if, upon variation of parameters in the infection
probability, the graph varies as indicated by the arrow, the
intersection crosses $n_{\rm I}^*=0$ and a transcritical bifurcation
takes place. The standard SIS model, for which $\rho$ is constant,
is a special case within this situation. More generally, the graph
of $\rho (n_{\rm I}^*)$ may have two (B) or more intersections with
the dotted curve. When parameters change, it is still possible than
one of the intersections becomes involved in a transcritical
bifurcation crossing $n_{\rm I}^*=0$, exactly as in situation A.
Now, however, it may well be the case that two intersections
approach each other, and eventually collapse and disappear, as in B.
In this case, Eq. (\ref{eff0}) undergoes a tangent bifurcation, as
found to happen in our system (\ref{sisn}).

\begin{figure}
\resizebox{\columnwidth}{!}{\includegraphics*{fig4.eps}}\vspace*{15
pt} \caption{Graphical solution of Eq. (\ref{eff1}). The dotted
curve represents the right-hand side of the equation, and full
curves are possible graphs of the left-hand side. Dots stand at
their intersections. The arrows illustrate how the graphs may change
upon the variation of parameters, in the cases of a transcritical
bifurcation (A) and of a tangent bifurcation (B).} \label{fig4}
\end{figure}

In summary, the above discussion shows that the suppression of the
endemic state as a result of reconnection events can be reasonably
understood in terms of the critical behaviour of a standard SIS
model with an effective infectivity, which depends on both the
reconnection probability and on the fraction of infected agents. The
transcritical bifurcation which stabilizes the state where the
infection is completely inhibited is interpreted as a continuation
of a similar transition in the absence of reconnection. In turn, the
tangent bifurcation --which, for large infectivities, suppresses the
infection as the reconnection probability grows-- is a generic
phenomenon in SIS models with density-dependent infectivity
\cite{tangent}.

\centerline{ } \centerline{***} \centerline{ }

We have studied a model for an epidemiological process in a
population of agents on a network, where contagion can occur along
the network links. The network coevolves with the population as the
infection progresses: a susceptible agent can decide to break a link
with an infected partner, and reconnect it with another agent. Our
main result is that this reconnection mechanism, implemented with
moderate frequency, can completely suppress the endemic state where
an infected portion of the population persists at arbitrary long
times. Suppression of the endemic state does not require full
isolation of the infected population. On the contrary, it can be
achieved while each infected agent preserves a substantial part of
the links with the rest of the population.

Whether these results are relevant to real epidemiological processes
is a question beyond the present study. Our analysis should be
regarded as an illustration of the kind of collective effects that
may emerge from the coevolution of populations of dynamical elements
and their interaction network.

redpajama_set_name: RedPajamaArXiv


George Mason Hillel hosted "Expressions of the Holocaust" partnered with The Jewish Federation of Greater Washington and the JCRC of Greater Washington. It was an event to honor the International Day of Holocaust Commemoration on January 28th. The event consisted of two parts, a general plenary where movies and clips from a once Nazi-occupied Germany were shown, then Holocaust survivor testimonies. I was lucky enough to have the chance to listen to one of those survivors.
The idea behind "Expressions of the Holocaust" was so we, as a Mason community, could remember the tragic things that millions of people went through because of the actions of one man, and his hateful ideas.
Ruth Kohn, a holocaust survivor came to Mason to share her story. Kohn, born in a small town in 1927 Germany, moved to Berlin on the last train for Jews in 1941. There, she went to school but was kicked out two years later for being Jewish.
She continued telling her story, "I couldn't tell you everything because I would be here until tomorrow." We tend to think of history as one period that happened between X year and Y year. We tend to forget that there are people who lived through these times day to day.
One of the biggest struggles her family faced was finding food. Her father had to trade in anything they had, silverware, furniture... for pork meat, even though pork is not kosher. Her father described the experience as "eating poison" but he was not going to let his children starve. So they ate pork and potato skins and to this day, Kohn cannot stand the taste of potato skins. There are endless triggers that remind her of her trauma and the horrible experiences she went through as a child. She said that she envies people like us, college kids who had childhoods, who got to be teenagers, who did not have to worry about being sent to concentration camps.
On September 1,1939, WWII officially began. Kohn and her family had to move to an air raid shelter every night that was specifically for Jews. She said that two air raids happened every night. One at midnight by the British, and one at 3 in the morning by the Russians. She also mentioned the United States' unwillingness to let in Jewish refugees into the country saying "we do not have enough space" which was troubling because every opportunity to escape the living hell of Germany was slowly being shut in her face.
Kohn also shared another story during that time, the one of many moments she thought she was going to die. Her family moved to a one room apartment and they were only allowed one room for four people. One morning, two policemen barged into her room.
"They just stood at the door like statues", she said. They did not ask questions and did not take anything. To this day Kohn still does not know what these policemen wanted. However, she is thankful they did not see the radio on top of the shelf or else her entire family would have been shot. "I think God was with us", Kohn said.
In the Dominican, Kohn learned Spanish and got a job at a mental health clinic where she worked with PTSD patients, she then became a nurse, got married and started a family.
Today she is traumatized. There are things that still remind her of Berlin. Yellow benches remind her of the benches that were made specifically for the Jews. Potato peels remind her of the only food that was available to them. She escaped and the war ended, but her personal war never stopped.
She now works for the Holocaust Museum and also shares her story with different schools in association with The Jewish Federation of Greater Washington.
When I talked to her after the event, she told me one thing that stuck with me. I thanked her for sharing her story and she said "don't forget it".
People like Ruth Kohn are reminders of why community events like "Expressions of the Holocaust" are important, to remind us of the terrible things that humans are capable of and why we must never let them happen again.


text:
Asset 30reza2 Contilio
Posted on September 23, 2018 October 1, 2018 by Contilio
McKinsey highlights the significance of Contilio's 3D vision approach for increasing construction productivity
"This article is written by McKinsey"
A new analysis of the construction technology ecosystem finds emerging trends, constellations of solutions, and an ever-increasing universe of technology use cases that are disrupting the way we plan, design, and execute projects.
After decades of under-digitization, the engineering and construction (E&C) sector is making bold moves in a new era. Last year, we mapped the industry's technology ecosystem with a focus on the solutions that are proliferating in the construction phase of the project life cycle. The research shed light on the emergence of technology clusters, industry-wide technology investment of more than $10 billion in less than a decade, and the lack of integrated solutions that span three identified use case clusters: on-site execution ("field"), digital collaboration ("team"), and back-office and adjacencies ("office").
This year, we expanded the study to include the entire asset life cycle—concept and feasibility, design and engineering, preconstruction, construction, and operations and maintenance—across more than 2,400 technology solutions companies, creating the most comprehensive database of the construction ecosystem worldwide. In this article, we explore three key topics based on our latest research:
What are the emerging trends from this year's research? We explore how the landscape has changed over the past year in terms of constellations of technology, accelerated investment, and an expansion in the number of use cases.
How will the market evolve in the coming years? We discuss the changes we expect over the next few years, including continued fragmentation of the industry, which will lead to consolidation, as well as an intensifying fight for talent.
How can the industry accelerate its transition to a digital future? We outline recommendations for AEC firms, technology providers, and owners to accelerate the impact of technology.
1. What are the emerging trends from this year's research?
Three key trends are shaping the industry: emerging constellations of solutions around established use cases, accelerating technology investment, and an expanding set of promising use cases.
'Constellations' of solutions emerging around established use cases
In our continuous mapping of the construction technology landscape, we see the concept of different "constellations" of connected solutions emerging around established use cases, which serve as indicators of what technologies are gaining the most traction and where their impact can be expected to rapidly increase in the near future. Today, the most prominent constellations include 3-D printing, modularization, and robotics; digital twin technology; artificial intelligence (AI) and analytics; and supply chain optimization and marketplaces (Exhibit 1).
Within each constellation are three or more use cases that span the three use case clusters we identified last year: on-site execution ("field"), digital collaboration ("team"), and back-office and adjacencies ("office"). For example, the digital twin technology constellation includes drone-enabled yard inspection, which is an on-site execution use case, as well as several digital collaboration use cases: laser scanning, virtual learning, and design simulation. In Exhibit 1, the thickness of the lines connecting various use cases indicates use cases that are often addressed together; in the digital twin technologies constellation, design simulation and virtual learning are strongly linked given the increasing amount of solutions offering these two uses cases in combination.
In particular, three of the constellations—3-D printing, modularization, and robotics; twin models; and artificial intelligence and analytics—are poised to be transformational for the industry. A fourth constellation, supply chain optimization and marketplaces, is notable due to its quick rise as dozens of smaller players have entered into this market over the past year.
Artificial intelligence and analytics. In the long-term, AI and analytics have boundless potential use cases in E&C. Machine learning is gaining some momentum as an overarching use case (that is, one applicable to the entire construction life cycle, from preconstruction through O&M), particularly in reality capture (for example, in conjunction with computer vision) as well as for comparison of in situ field conditions with plans (for example, supporting twin models). Indeed, by applying machine learning to an ongoing project, schedules could be optimized to sequence tasks and hit target deadlines, and divergences from blueprints could be caught closer to real time and corrected using a variety of predetermined potential scenarios.
In the immediate future, we expect AI's proliferation in the E&C sector to be modest. Few leaders have the processes, resources, and existing data strategies in place to power the necessary algorithms and meaningfully implement this technology. However, the potential impact is so large that the industry can no longer afford to ignore it. AI methods are increasingly able to work across industries, elevating the threat of competition from nontraditional market entrants. And a narrow set of start-ups are already gaining market traction using AI-focused approaches.1
3-D printing, modularization, and robotics. Parts of the construction industry are moving toward a manufacturing-like system of mass production, relying on prefabricated, standardized components that are produced off-site. Our research finds that consistent use of these techniques, on projects where they are economically feasible, could boost the sector's productivity by five- to tenfold. Such a system would include applications such as fully automated prefabrication processes that turn a 2-D drawing or 3-D model into a prefabricated building component, or fabrication directly off a 3-D model or shop drawings; construction robotics such as bricklaying or welding robots; self-driving heavy machinery to make construction safer, faster, and more affordable; exoskeletons and wearable robotics to improve the mobility of workers with injuries or to harness the strength of robotic arms; and metal 3-D printing of long-lead components such as joints, enabling the production of high-performing components and, ultimately, more efficient, cost-effective parts.
On the robotics side, the E&C industry is at the beginning of its journey to embrace the hardware innovations that enable field augmentation with exoskeletons and drone-enabled yard inspection. These advances are particularly important given a labor shortage in many geographies as well as the natural ceiling of human physical productivity. Pairing humans with robots can assist in tasks that would take a human worker more effort (for example, lifting heavy objects and placing them in exact coordinates).
Digital twin technology. In E&C, productivity gains are directly driven by transparency and proactive problem resolution. Digital twin platforms and reality-capture solutions enable stakeholders to minimize rework in the field by allowing a dynamic view of the project and real-time comparison of progress to design blueprints—and the ability to adapt those blueprints as the work progresses and inevitably results in changes. Drones and satellite imagery, as well as LiDAR and photosphere based-solutions, are key components of many reality-capture efforts.
The most exciting applications of twin models can be found in the seamless integration of 3-D models generated by drone imagery, turbocharged by live key performance indicators that are monitored using Internet of Things sensors. This approach creates an exact digital replica of a project's physical reality, allowing us to rapidly advance data accuracy and incorporate as-built data into 3-D models for automated, real-time progress updates. It also enables users to virtually interact with "mixed reality" models that combine 3-D design and as-built configurations. What is truly exciting about these applications is the ability to reduce decision-making cycles in a construction project from a monthly basis to a daily basis through full automation of the project's scheduling and budgeting updates.
Supply chain optimization and marketplaces: Currently, procurement of materials, equipment, and labor is a largely manual and cumbersome process. However, start-ups that offer marketplace platforms for the buying and selling of goods as well as hiring have begun to gain traction in certain regions. Some of these start-ups have been acquired by large suppliers, which have quickly deployed these platforms at scale. By enabling players to match supply with demand, these marketplaces have huge potential to optimize the supply chain—much the way such marketplaces have revolutionized industries such as retail—improving productivity and profitability. In construction, these marketplaces can also enhance competitive bidding by improving transparency on costs and availability of materials, labor, and equipment for both future and ongoing projects. They will also become increasingly important given the rising use of prefabricated components that are manufactured off-site. Despite the progress, this constellation is nascent and limited to North America.
Increasing and evolving technology investment
Through the mapping of the investment flows we found two critical insights:
Investment has doubled in the past decade: Last year, we found that construction technology companies had garnered $10 billion in investment between 2011 and early 2017. Our updated research has pointed not only to a greater volume of outside investment but also an acceleration in investment. Between 2008 and 2012, construction technology received $9 billion in cumulative investment. Between 2013 and February 2018, that number doubled to $18 billion, largely driven by mergers and acquisitions (Exhibit 2).
Early technologies are delivering on their promise: Our research reveals that by count of transactions, early-stage venture capital (VC) is on the rise. Of the 908 transactions from 2013 through February 2018, three in four were early-stage VC. Indeed, since 2015—a peak year for VC investments—the construction technology space has sustained a relatively high level of investment from VCs, suggesting that more solutions will be ready for scaling and that high levels of merger and acquisition (M&A) activity will continue unabated. M&A activity tends to occur one to two years after late-stage VC.
Furthermore, late-stage VC has been trending upward in the market (Exhibit 3). From 2010 onward, late-stage VC has almost steadily increased (except a small dip in 2016). Such a steady rise indicates that certain use cases are market-backed and ready for growth financing,2 delivering on the promised impact.
An expanding set of use cases
Last year, our research focused on technology in one phase of the asset life cycle: construction and commissioning. As we expanded our taxonomy to look at the entire asset life cycle, we found that two phases are attracting the most growth: construction and commissioning and operations and maintenance (Exhibit 4). Other phases tend to be already established—for instance, preconstruction and back-office—while others are small or still maturing.
Construction remains the highest invested phase of the asset life cycle.Construction leads the ecosystem in garnering the most overall capital from 2013 to February 2018, with both the highest number of use cases and the highest number of transactions. It is also relatively mature; only one-third of companies in this phase are newcomers. Over time, we expect to see M&A investments related to consolidation as well as incremental late-stage VC investments (for example, for scaling sales operations).
Preconstruction and construction back-office phases are both garnering large investments. Investment in the preconstruction phase is primarily driven by labor and equipment marketplaces, a relatively fragmented solution space where regionally focused players will eventually face consolidation. Construction back-office, on the other hand, is a very mature solution space. Investment in this phase is driven primarily by mature companies through M&A or private equity transactions with high average values.
Cross-cutting technologies are gaining the most momentum. We classified 3-D printing, virtual learning, design simulation, machine learning, and deep learning as "overarching," given their applicability across different stages of the life cycle. While we found relatively few transactions in this category compared with construction and commissioning, the number of companies founded in this space over the past five years exceeds any other category, and the dollar value of transactions is quickly catching up with the rest of the categories. The average transaction amount is particularly high in capital-intensive use cases in this category such as 3-D printing.
There are two untapped markets: design/engineering and concept/feasibility.This may be because entrepreneurs have focused on life cycle stages that hold the majority of project value. Alternatively, the office-based nature of these phases also means their relevant solutions (such as CAD or BIM) may already be relatively mature and sophisticated. We foresee less disruption in these stages and more continuous improvement (for example, new features for existing software).
2. How will the market evolve in the next 2–3 years?
Mapping the number of transactions in each of the 38 use cases against the number of new companies in the past five years in that space reveals a detailed picture of the current construction market (Exhibit 5). Four archetypes emerge:
Talent acquisition. In the upper right quadrant, we find both a high concentration of new companies and a high number of transactions in machine learning, among several other use cases. This quadrant can be described as "talent grab," which means that companies are using acquisitions to onboard new talent and skills.
Emerging. In the lower right quadrant, we find use cases, such as deep learning, where there are a lot of new companies but not a lot of transactions, suggesting these use cases are primed to emerge into the tech investment space in the next few years.
Maturing. In the upper left quadrant, we find use cases, such as document management, with a lot of transactions but relatively fewer new companies, suggesting that these use cases are dominated by relatively established companies operating in a fragmented market. These areas may thus be facing consolidation in the near future.
Established or unproven. Finally, in the lower left quadrant we find established or unproven use cases, such as enterprise resource planning, where few new companies and few transactions are underway. These markets may be saturated—but for the exception of some use cases, such as laser scanning, that have simply not yet realized momentum.
Increasing consolidation against a backdrop of continued fragmentation
The fragmentation of technology offerings will continue to be an issue. In last year's analysis, just 13 percent of the companies we studied had engaged a technology solution that addressed more than one of the three clusters (on-site execution, digital collaboration, and back-office and adjacencies)—meaning that most companies are engaging solutions that address a very specific, narrow application rather than more integrated solutions.
Our new research confirms that more than half of companies are still engaging a solution that addresses just 1 or 2 use cases out of the 38 (Exhibit 6).
This fragmentation is one of the biggest challenges we've heard from companies that want to engage with technology solutions. Many are older, venerable companies using legacy systems and various information-collection methods. For these companies, integration may sound more like it's yet another solution to layer in on the top of all the other processes and solutions on hand—when in fact, technology can be used to cut down on the number of solutions and methods being used.
Integration plays
The lack of use case integration is one of the drags on technology adoption at scale. As such, more companies are exploring the potential to consolidate solutions that address multiple use cases. While integration won't "grease the wheels" of every aspect of technology adoption, it certainly represents a viable path forward to bring more layers up to speed. (See sidebar, "Integration plays.")
The struggle to find talent
Finding digital talent is a prominent concern for executives across the industry, and it will be critical to digitization: according to research by McKinsey's Digital Academy, investing in talent increases the odds of digitization success by 2.5 times. Investing in talent requires balancing the entrepreneurship DNA, industry knowledge, and business acumen to build business unit from scratch—but the talent pool is small when it comes to balancing these three skill sets.
3. How can the industry accelerate its transition to a digital future?
While technology has dramatically advanced in the E&C sector, there is much room for improvement. There are several actions that AEC firms, technology providers, and project owners can take to accelerate construction technology in the coming years.
AEC firms:
Invest in talent and skill building: AEC leaders must begin to expand skill sets among existing employees as well as hire new candidates with technical expertise. To start, AEC firms can explore talent pools in digital native companies, even those outside the E&C industry; a particular focus should be given to candidates in other industries that have undergone a digital transition. These individuals can be paired with the right industry leaders and reach in the organization to integrate new and existing expertise. To upskill current employees, firms should bring in training programs in new technologies—for instance, to train employees in 3-D printing—or set aside funds for capability building.
Actively engage with the start-up ecosystem: This action can take a variety of forms, one of which is investing directly in start-ups through a corporate VC arm. Here, AEC firms may be challenged by entrepreneurs who are hesitant to accept capital from large players, as it compromises their ability to work with a funder's competitor. AEC firms can manage this caution by exploring other, less risky forms of engaging with start-ups: for instance, investing indirectly through a VC fund or partnering selectively for piloting or codeveloping solutions.
Establish conditions of success for piloting and scaling: AEC firms can prime themselves to be early adopters of promising technology by setting aside funding for the purpose of experimentation. As pilot solutions prove their value, AEC firms can use a helpful acid test for evaluating the longer-term use of a technology: whether a project manager is willing to accommodate its cost in their project budget. AEC firms can also bring in outside start-up expertise as needed, as building an in-house development team is often labor intensive and time consuming. Partnering with start-ups that can bring specific capabilities (for example, product development through rapid iteration) can be particularly valuable.
Tech providers:
Listen to the end user and adapt: Solutions in the ecosystem are often developed by looking for a problem. Indeed, we find passionate start-up founders looking for an application of their novel solution in the industry, instead of truly understanding the industry's needs. To that end, start-ups—especially if teams are from outside the AEC industry—must listen closely to the needs of AEC firms and adapt product offerings. This effort will consist of focusing on validated customer needs; in this fragmented landscape, it is imperative to validate the real need (versus a "nice-to-have" application).
Plan for the journey to integration and consolidation: As described above, unlocking real value from the technology ecosystem will require integration across multiple use cases and clusters. As the industry evolves, start-ups must therefore forge a "co-opetition" strategy—that is, how to simultaneously collaborate and compete. This is especially true given the multiple pivots that start-ups undergo (for example, starting with one use case and shifting to a new one). Start-ups in the early stage will need to plan on an evolving go-to-market strategy.
Enforce a strong and sharable data foundation: All project participants need to work with one shared data backbone in one system, known as a common data environment (CDE). This data will need to be made available to all project participants, with up-front agreement from all.
Align on supportive contract strategies: Digital participation needs to be part of the bidding contracts for all project participants. Indeed, a digital project should emulate an integrated project delivery (IPD) setup, which can not only improve outcomes and accountability but also circumvent the hostility of an adversarial contractual environment.
Identify and focus on critical use cases: Owners need to focus on understanding their organization's unique economic case for technology. While it may be appealing to pursue the most cutting-edge tools and applications, owners must identify and prioritize the use cases that will have both a long-term impact and a medium- to short-term impact to generate momentum. Only by developing a concrete and customized understanding of the return on investment, as well as the risk and disruption to existing functions, can they ensure that new technology adoption is optimized and sequenced according to pressing needs and their distinct circumstances.
Gone are the days when the construction industry can ignore the burgeoning set of technology solutions across the asset life cycle. We expect investment, competition, and consolidation to continue to accelerate as use cases and start-ups serving the industry proliferate. As predictions come to life and new capabilities infiltrate the field, team, and office, the winners will be the ones that adapt—sooner rather than later.
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We provide gentle periodontal treatment that is designed to fit your needs and protect your oral health.
We'll Help Get Your Oral Health Back on Track!
You may not hear much about it, but one out of every two American adults has periodontal disease. Periodontal (gum) disease is a bacterial infection that damages gum tissue and the bone supporting your teeth. If it's not caught and treated in its early stages, periodontal disease can eventually lead to tooth loss and other serious health issues.
At Temple Dental Trails, we understand the serious risk that gum disease poses to both your dental and general health. Fortunately, in most cases, gum disease can be prevented and treated with professional dental cleanings and proper oral hygiene. We have always been strong advocates of prevention as the most effective way to reduce the possibility of developing gum disease.
Gum disease may start in your mouth, but it is not just an oral health problem. Numerous studies exist that indicate a connection between what happens in your mouth and in your body. Research indicates that severe periodontal disease can enter the bloodstream and lead to serious health complications like heart disease, respiratory disease, diabetes, and stroke.
As gum disease progresses, spaces open up between the tooth and gums; these are called periodontal pockets. These spaces provide the perfect environment for bacteria to continue to grow and, without treatment, gum disease continues to do its damage.
When gum disease reaches this point, it will begin to destroy the gum tissue and bone that supports your teeth. Unfortunately, in cases of severe gum disease, tooth loss becomes a real possibility. Our goal is to provide you with the treatments and education you need so you never have to worry about compromising your smile with gum disease.
The earliest stage of periodontal disease is referred to as gingivitis and, in most cases, it can be treated with a routine dental cleaning. Without treatment, gingivitis advances to the most serious stage of gum disease, which is periodontitis.
If we find evidence of periodontitis, we will recommend a deep cleaning procedure that will eliminate bacteria and infected tissue. Depending on the extent of infection, we may also need to prescribe antibiotics as well as a follow-up deep cleaning. In severe cases, we will refer you to a periodontist for treatment that will prevent tooth loss.
During a deep cleaning, your hygienist gently scrapes away plaque, tartar, and harmful bacteria above and below the gum line. This is a process where the surface of the tooth is smoothed (planed) to allow affected gum tissue to heal and reattach to the tooth. In certain cases, we will prescribe antibiotics to ensure that the infection is completely eliminated.
Our team at Temple Dental Trails is here to provide the treatments you need to protect your oral health. We are pleased to provide you with the most updated, state-of-the-art care available and will do everything possible to make you feel like part of our extended family and ensure that you feel welcome whenever you visit our office.
Quality dental care should not be complicated, and we offer convenient office hours to accommodate your schedule. We respect that you are busy, and we book your appointments efficiently so you don't have to spend valuable time waiting for treatment.
Please call our Temple dental office to arrange your next exam and cleaning. Together we will work toward your goal of excellent oral health.
It is certainly not normal for your teeth to bleed when you brush. In fact, bleeding gums is a common sign of periodontal disease.
If you have gum disease, you're not alone. The Centers for Disease Control estimate that half of Americans over the age of 30 have some form of periodontal disease.
The most common cause of periodontal disease is improper oral hygiene. This doesn't necessarily mean that you don't take care of your teeth. But you may not be brushing properly, meaning that you don't get the most out of your daily routine.
For this reason, it is critical that you schedule regular professional cleanings with a qualified dental hygienist. A trained hygienist can spot gum disease long before you notice any symptoms.
On top of cleaning, we also educate!
During a cleaning, your hygienist can also show you the proper way to brush and floss your teeth. An effective at-home hygiene routine can go a long way toward preventing periodontal disease from developing in the first place.
If you're due for a dental cleaning, please contact our Temple dental office. We will be happy to arrange an appointment with one of our Registered Dental Hygienists.
Researchers in the dental field are continuously working to gain a better understanding of oral disease to provide methods for integrating those findings in clinical settings.
Are Cavities Caused by Sugar? Or Bacteria?
Since you were a little kid, you have been told that sugar is bad for your teeth. But did anybody ever actually explain why?
Is it the sugar itself that causes the damage, or is something else going on?
It's easy to take good oral health for granted. Unfortunately, dental health isn't a priority for most people until something goes wrong.


Pattillo, Kelsie E.. "The Typology of Uyghur Harmony and Consonants." Rice Working Papers in Linguistics, 4, (2013) Rice University: https://hdl.handle.net/1911/75166.
Descriptions of Uyghur phonology are unclear as to whether or not the front and back consonant assimilation of velar and uvular stops is a harmonic process (Comrie 1997; De Jong 2007; Engesæth et al. 2010; Friedrich 2002; Hahn 1991, 1998). Data from Uyghur reference materials demonstrate front and back consonant assimilation processes in Uyghur which differ from cross-linguistic consonant harmony as it has been defined and described in the literature (Hansson 2001; Rose and Walker 2004). The data demonstrate that Uyghur consonant assimilation is triggered by vowel harmony, thus it should not be referred to as consonant harmony in future descriptions of Uyghur.


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At A Point In My Life I Had Only One Shoe And It Was A Fake Designers – Joeboy Recounts Struggles
24-year-old singer and songwriter, Joeboy has recounted how he got through life while growing up.
In a chat with media personality and Journalist, Chude Jideonwo, Joeboy gave details of some of the challenges he had to pass through as a young boy.
The music star narrated how he got embarrassed for owning school fees in his secondary school days and how that affected his self-esteem.
He also narrated how he worked under the heat of the sun promoting products for a company in Ogun State with a weekly pay of N5,000.
He added that there was a time in his life that he had only one shoe, which was a fake designer shoe, and that was what made him vow to always buy shoes whenever he becomes successful.
"Sometimes I felt everything should just end because it was difficult.
"I remember after secondary school, I didn't have money, I was looking for a job. I remember going for a full month looking for a job.
"I would prepare my CV. There was a time I trekked from Ilaje to Sabo in search of a job with my friend. We submitted our CVs but didn't get the jobs eventually.
"I eventually got a job to promote products for a company under the sun. They took us to redeem camp in Ogun state, it was difficult. We were paid N5000 a week.
At that point, life was hard, I remember I only had one Nike shoe and it was fake. So, one promise I made to myself was that when I finally blow, I'll always buy shoes.
"So, these days, when I'm down, I just step out to buy shoes. Life was more difficult than failing an exam or owing school fees.
"There was a particular time this happened to me. I'll just say when a child is owing school fees, don't call the child out. Just tell the child not to go to school.
"Don't flog kids for owing school fees, the child doesn't have money. School owners should not embarrass a child for owing school fees.
It was really embarrassing for me at the time because it affected my esteem at that point."
Related: "I am scared of this my new life"
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Barriers to HCV treatment access from the drug user's point of view: stigma, complex lives and damaged veins
Keith Alcorn
Despite access to hepatitis C treatment, many people who inject drugs still perceive numerous barriers to starting treatment, including the attitudes of healthcare workers, the difficulty of juggling treatment with competing demands, a lack of support to navigate the healthcare system and problems with blood tests due to damaged veins, an Australian study published in PLOS One reports.
Australia has one of the most extensive hepatitis C treatment programmes in the world. It also has a hepatitis C virus (HCV) epidemic that is highly concentrated in current and former injecting drug users. Recent reports on treatment uptake suggest that after an early rush to access treatment, the number of people starting treatment has plateaued, suggesting that barriers to treatment may exist for people who inject drugs.
A qualitative study designed by the University of New South Wales's Centre for Social Research in Health set out to identify barriers other than non-availability of treatment to the uptake of direct-acting antivirals (DAAs) by people who inject drugs in the Australian state of Victoria. To achieve elimination of HCV in Australia and other countries where the majority of people living with HCV are current or former injecting drug users, what psychosocial and structural issues need to be addressed?
The study is based on interviews conducted by a peer researcher with experience of injecting drug use and hepatitis C with 24 people who had injected drugs in the past six months. Participants were recruited through community networks by Harm Reduction Victoria at four sites in Melbourne. The study recruited a cross-section of people who declined treatment or deferred treatment, people contemplating starting, people currently on DAA treatment and those who had completed a course of DAA treatment. Interviews took place in 2016 and 2017 and were analysed for themes relating to barriers to treatment.
Being asymptomatic led people to ignore their diagnosis and not to engage with medical care for hepatitis C, and interviewees said that they received little information about the impact of hepatitis C on their health or the likely progression of liver disease.
People deferred treatment for a long time due to lack of symptoms, but other commitments also kept people from engaging with the idea of treatment. Work, pregnancy and childrearing claimed the attention of interviewees, as did less specific anxieties about the time not being right to undertake a course of treatment.
Interviewees were also put off seeking treatment by advice from healthcare providers to wait for new drugs or confused about whether they were eligible for treatment if they continued injecting drugs.
Long-term injectors with many damaged veins saw difficulties in undergoing a course of treatment that might entail numerous blood samples.
"The big barrier for me is that no one can get blood out of me, I've just got no veins and I mean this has been problem for the last 10 or so years," said a 64-year-old woman.
Several interviewees commented unfavourably on the competence of healthcare workers who drew blood. "It's just quicker too and less painful if I can do it," said another woman, aged 42 years. Self-sampling and the use of dried blood spots to collect samples were seen by some interviewees as important tools for achieving higher rates of diagnosis and treatment uptake among long-term injectors. (Taking blood for diagnosis and HCV viral load testing at the same visit needs more attention, say the study investigators.)
Despite a push for treatment of hepatitis C through primary care in Australia, some primary care physicians caring for people who use drugs had told interviewees to seek specialist hepatitis care if they wanted DAA treatment. Primary care physicians had shown little inclination to carry out regular monitoring in their patients with hepatitis C and interviewees reported that few primary care physicians were taking the opportunity to prescribe DAAs.
For some, the numerous competing demands of managing opioid substitution therapy, co-morbid conditions, childcare and mental health conditions made it difficult to access DAA treatment or to travel to healthcare facilities where it was available. Intermediary services that can help to connect people to treatment – for example, by providing transport – are needed, the study investigators recommend.
Finding non-stigmatising and accepting healthcare workers also represented a barrier to care. Many interviewees had internalised stigmatising messages from healthcare workers and others. They felt that physicians considered treating people who inject drugs "a waste of time" and that they would be denied re-treatment if they became reinfected.
Interviewees agreed that information on where to access non-stigmatising services that provide DAA treatment would encourage people to seek treatment.
The researchers say that to increase treatment uptake, countries like Australia need to look simultaneously at patient and provider barriers to treatment, as well as systemic obstacles, and need to acknowledge past deficits in care to address distrust of the health system and healthcare providers. Community and primary care barriers need attention alongside barriers in specialist liver care.
"Efforts to increase DAA treatment uptake must reduce stigma and discrimination as a central precept to any effective response," they conclude.
Madden A et al. Beyond interferon side effects: what residual barriers exist to DAA hepatitis C treatment for people who inject drugs. PLOS One 13 (11): e0207226, https://doi.org/10.1371/journalpone.0207226
Hepatitis information
For more information on hepatitis visit infohep.org.
Infohep is a project we're working on with the World Hepatitis Alliance and the European Liver Patients Association.
Visit infohep.org >
People and personal stories
People who inject drugs
Naltrexone implants provide better HIV treatment outcomes for those with HIV and opioid addiction in Russia19 April 2019
Hepatitis C drugs for all genotypes curing almost everyone who completes treatment, real-world studies show16 April 2019
Hepatitis C drops among HIV-positive London gay men after direct-acting antiviral scale-up07 March 2019
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Related news selected from other sources
Hepatitis C deaths fall by 16 per cent between 2015 and 2017Public Health England - 09 April 2019
Armenia gets license to produce drugs for hepatitis C treatment Public Radio of Armenia - 03 April 2019
Louisiana picks drug company for hepatitis C treatment plan San Francisco Chronicle - 27 March 2019
Pilot study finds HCV treatment safe in pregnancyHealio - 11 March 2019
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In unique case, Australian man appears to have cleared his HIV infection11 June 2019
Hepatitis C more stigmatising than HIV: gay men's attitudes towards hepatitis C reinfection 04 June 2019
Open the e-atlas for more news from Australia >
Starting ART at a high CD4 cell count has clear benefits for people with a low viral load10 July 2019


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Home > sand and gravel production
The nation's top 25 construction aggregates producers
Jun 16, 2014· The 10 leading states, in descending order of production, were Texas, California, Minnesota, Arizona, Michigan, Ohio, North Dakota, New York, Washington, and Colorado Their combined output of construction sand and gravel accounted for approximately one-half of the US construction sand and gravel production...
11191 Sand And Gravel Processing - US EPA
11/95 Sand And Gravel Processing 11191-1 11191 Sand And Gravel Processing 111911 Process Description1-6 Deposits of sand and gravel, the unconsolidated granular materials resulting from the natural disintegration of rock or stone, are generally found in near-surface alluvial deposits and in subterranean and subaqueous beds...
Sand | Rock | Gravel | Production | Kearney, NE
Start your commercial or residential landscaping project on the right foot by having the sand, gravel, and rock supplied by the committed and knowledgeable team at Broadfoot's Sand & Gravel Corp , Stone and Gravel Production Cobblestone, South Dakota boulders, and Colorado decorative rocks and boulders are available as well as a wide ....
5 Aggregate Production - INgov
for aggregate production come from bedrock or unconsolidated deposits The vast majority of materials used in the mineral aggregate industry are obtained from surface-mined stone quarries or from sand and gravel pits How materials are extracted influences their quality...
ANNUAL PRODUCTION REPORT - ROCK, SAND AND ,
ANNUAL PRODUCTION REPORT - ROCK, SAND AND GRAVEL PLANT NORTH DAKOTA DEPARTMENT OF HEALTH DIVISION OF AIR QUALITY SFN 51113 (11-10) GENERAL INFORMATION Name of Company Year of Emissions Mailing Address City State Zip Code Permit to Operate Number Plant ID Number Actual Hours of Operation ROCK, SAND AND GRAVEL PLANT ,...
USGS reports 2016 crushed stone, sand and gravel production
Jun 13, 2017· The USGS issued its Construction Sand and Gravel Statistics and Information report stating that construction sand and gravel production increased nearly 8 percent in 2016, from 937 billion tons in 2015 to 1,010 billion tons valued at $89 billion in 2016 It was produced by an estimated 6,300 operations owned by 4,100 companies and government ....
Construction Sand | Gravel
Washed Concrete Sand/C-33 Coarse sand mainly used in the production of redi-mix concrete Other uses include beach repair sand, filtration material for bio-retention ponds, admix product for topsoil, volleyball pits, bedding sand, and used place on top of ice or snow for traction...
How Does a Gravel Industry Work? | Chron
Production Process Gravel, sand and crushed rock are quarried out of rocky areas of land Depending on the nature of the land, certain quarries are more suited to gravel, while others are more ....
Sand control - petrowikiorg
The consequences of sand production are always detrimental to the short-long-term productivity of the well Although some wells routinely experience manageable sand production, these are the exception rather than the rule In most cases, attempting to manage sand production over the life of the well is not an attractive or prudent operating ....
Air PBR 106143: Wet Sand and Gravel Production - TCEQ ,
Wet sand and gravel production facilities are permitted by rule if they meet the conditions stated in 30 TAC Sections 1064 and 106143 No registration or fee ,...
2016 aggregate production statistics : Pit & Quarry
May 29, 2017· 2016 aggregate production statistics By PQ Staff | May 29, 2017 Crushed stone , Construction sand and gravel production was about 101 billion tons in 2016, an increase of 7 percent compared with that of 2015 Apparent consumption also increased to about 101 billion tons Consumption of construction sand and gravel was higher in 2016 ....
US SAND AND GRAVEL - ERATH COUNTY, TEXAS
A family owned business with customer service as our number one priority We utilize our own pits to make sure we have top of the line sand and gravel materials...
Division of Geology and Mineral Resources - Sand and Gravel
Sand and Gravel Mining operations in ia produced 93 million short tons of sand and gravel in 2016 with an estimated market value of $111 million Sand and gravel natural aggregate resources in ia are relatively plentiful and have long been utilized in the ,...
Construction aggregate - Wikipedia
Construction aggregate, or simply "aggregate", is a broad category of coarse to medium grained particulate material used in construction, including sand, gravel, crushed stone, slag, recycled concrete and geosynthetic aggregat Aggregates are the most mined materials in the world...
Gravel - Wikipedia
Bank gravel: naturally deposited gravel intermixed with sand or clay found in and next to rivers and streams Also known as "bank run" or "river run" Bench gravel: a bed of gravel located on the side of a valley above the present stream bottom, indicating the former location of the stream bed when it ,...
Loader Operator Sand Gravel Production Jobs, Employment ,
94 Loader Operator Sand Gravel Production jobs available on Indeed Apply to Plant Operator, Loader Operator, Equipment Operator and more!...
Sand, gravel properties key to optimum designs - Oil & Gas ,
Successful gravel packed and screen well completions require a knowledge of sand as well as gravel textural properti These completion methods keep sand and fines from entering the well bore, so ....
Production Plus Sand and Gravel Buckets - Dymax Inc
Dymax Production Plus Sand and Gravel Buckets: Experience in Action Sand and Gravel Buckets for Wheel Loaders and Track Loaders are designed for use in abrasive materials or extreme wear applications, such as loading sand and gravel or charging asphalt plants...
Sand and Gravel Operations Flowchart - Burgex Inc
Sand and gravel operations lay the foundation (literally) that world economies are built upon Chances are, wherever you are, there is an active sand and gravel pit nearby Sand and gravel products lay the groundwork for virtually all construction, landscaping, and transportation applications...
Sand and Gravel | The Delaware Geological Survey
Sand and gravel are essential for supporting and maintaining economic development throughout Delaware These natural resources are used primarily for aggregate in the productions of concrete for residential, commercial, and industrial buildings, bridge and highway construction, fill for road beds and foundations, water and wastewater treatment facilities, and for replenishment of our Atlantic ....
Sand and Gravel - Products | Lehigh Hanson, Inc
Natural sand and gravel is usually dug or dredged from a pit, bank, river, lake or seabedIn most cases, minimal processing is needed beyond washing and screening the material to separate it by particle size While they share common uses and applications, crushed stone and sand and gravel differ in their physical properties and production...
Sand and gravel aggregate production line,quarry plant ,
Oct 08, 2013· Zhengzhou Machinery Co, Ltd specializes gravel aggregate production systems, including sand and gravel aggregate crusher, sand making machine, a set of gravel aggregate gravel ,...
Construction Sand and Gravel Statistics and Information
Construction sand and gravel, one of the most accessible natural resources and a major basic raw material, is used mostly by the construction industry Despite the low unit value of its basic products, the construction sand and gravel industry is a major contributor to and an indicator of the economic well-being of the NationAnnual PublicationsMineral Commodity Summaries...
2017 aggregate production analysis : Pit & Quarry
May 18, 2018· Production totaled 890 million metric tons, which were valued at more than $77 billion In 2016, sand and gravel production reached 892 million metric tons Despite a slight dip in production of sand and gravel in 2017, the average value per metric ton has steadily increased in ,...
Sand and Gravel | Premier Aggregates | Idaho
Premier Aggregates was founded in 2011 as a transportation and logistics company serving the heavy industrial market Since then, our focus has evolved to include the natural resource sector, specifically rock, sand, and gravel production and supply...
Cement, sand and gravel production - Mega Production
The company leases quarries close to the town of Kaspi in order to obtain supplementary materials for the production of concrete These natural materials are processed in crushing machines manufactured by global leader , which in itself ensures that the sand and gravel we produce meets the highest European standards...
Predicting sand production - petrowikiorg
Therefore, gravel packing cannot be applied indiscriminately when the possibility for sand production from a well is unknown Making the decision whether to gravel pack is fairly easy if the formation material is either hard (no sand production) or weak (sand production) The difficulty arises when the strength of the formation material is ....
Fisher Sand & Gravel Co, Inc: Private Company ,
May 13, 2019· Fisher Sand & Gravel Co, Inc offers production of sand and gravel products The company also offers aggregate, quarry, recycle materials, crushed gravel and sand,...
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What is Theosophy?
Directions to Krotona
We Are Grateful
School of Theosophy
Our Grounds
Sanctuary of Connections
Labyrinth at Krotona
In the map above, the red marker indicates the parking lot of the Bookshop and Library.
Directions to Krotona by air, train or car.
Visitors arriving by air may fly into Los Angeles (LAX), Burbank (BUR), or Santa Barbara (SAB) airports. Generally speaking, flights to LAX will be more frequent and less expensive.
Unless you arrange for a rental car, you will need to take a shuttle, taxi or train from the airport. Please note that shuttle and train service is available only from LAX.
Trains operated by Amtrak serve the Ventura train station and have service from LAX. Just as with the shuttle service, you will need to arrange a ride from the train station to Krotona.
Currently, the only shuttle service coming directly to Ojai is the Roadrunner (1-800-247-7919), which offers service to and from LAX. Roadrunner shuttle fares can be shared with other incoming students.
An alternative service is the Ventura County Airporter (1-805-650-6600). You can book a round trip ticket online when you have booked your flight.
For students registered for classes, Rochelle is available for assistance with ground travel plans. Please let her know as soon as your travel plans are confirmed.
From Ventura
From Santa Barbara
From LAX via Hwy 1 (PCH)
From LAX via I-405 and I-101
From Ventura/Santa Barbara
Take the Ojai/Hwy 33 exit from Hwy 101 North or South.
Drive north-bound 12 miles through the small towns of Casitas Springs, Oak View, and Mira Monte.
After passing Villanova School, take the next left (Krotona St on the left, Hermosa Rd on the right). Two stone pillars mark the entrance.
From within Ojai
Krotona is on Ventura Ave/Hwy 150 at the intersection of Krotona Hill / Hermosa Rd., 0.6 miles south of the "Y" (Vons shopping center).
Read our Guest Policies
Ojai, California
Ojai is a rural community of 8,000 cradled in an inland valley in the coastal mountains of Southern California. We are located about a 90-minute drive north of Los Angeles, and 30-minutes inland from Ventura. Private taxi and shuttle services are available directly to Ojai or to Ventura where we can arrange to meet you.


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Q: primefaces schedule repeat day with different values I want to know if there is anything I can use with primefaces schedule or anything similiar preferably from primefaces, to be able to set diferent events for the same day, I explain my situation a little better:
I have multiple boardrooms and I have a filter that loads the schedule with the information for each boardroom and the events that it has scheduled, but I want to be able to see multiple boardrooms at the same time.
My idea is to have multiple schedules and each one load a boardroom event, I don't want to have a single schedule show with different colors each boardroom. I want them to be separated, is it posible?
example

A: It can be to late .... Hope this idea can help someone in the futur !
If I understand, you need to cut the day with different columns depend on your boardrooms number.
Perhaps you can do that with css style. When you create event, you can affect a css style.
Exemple for 3 boardroom :
.firstBoardRoom { left :0% !important; right : 67% !important }
.middleBoardRoom { left :34% !important; right : 34% !important }
.lastBoardRoom { left :67% !important; right : 0% !important }

Or something like this

redpajama_set_name: RedPajamaStackExchange


There are not many sights that can compare to Longwood Gardens dressed in its Christmas finery. Acres of plants and trees shine brightly with all the colors of Christmas. Additionally, we'll tour the QVC Studio (and shop). We will travel to Amish country to see the Christmas Show at the American Music Theatre and visit the Kitchen Kettle Shops. On the way home, we stop at the Christkindl Market in Bethlehem, Pennsylvania, to see thousands of crafts and gifts to start your Christmas shopping. Your travel hosts for this trip -- Eric Sargent and Norma Jeanne Pinney.