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Sorry to Bother You (2018)
March 11, 2019 David DeMoss 1 Comment
[TRANSCRIPT]
Sorry to Bother You is a 2018 dystopian sci-fi satire of the kind we don't see much of anymore, because most of our examples have been embalmed and pinned to butterfly boards. It's a 1984 for 2018, a snapshot of the Brave New World we're all living in. It's the true heir to Terry Gilliam's Brazil, because thirty years of trying to make a Don Quixote movie have officially driven Terry Gilliam insane. (Seriously, some warlock Cervantes fan must've hexed that text and anyone who tries to adapt it. Similar to the curse Alan Moore placed on all his work after the From Hell and League of Extraordinary Gentlemen movies sucked.)
Sorry to Bother You is the one theatrical feature I saw last year that I feel comfortable calling "great," without at least twenty minutes of waffling qualifications. You should see it if you haven't – right now. And if you have, you should join the rest of us in solidarity. We have nothing to lose…not even our chains. We sold them for scrap to pay for gas money so we could get to our crappy jobs on time.
That's the other reason we haven't had as many dystopian sci-fi satires as we once did: the world we're living in is a dystopian sci-fi satire of itself. A demented game show host is president of my country at a time when we're fighting seven wars (that I know of) and steadfastly ignoring the eighth war we should be fighting against the weather itself. Unless we're the 1% of the 1% of the 1%, we haven't seen a real raise in forty years. Our jobs, assuming we have them, universally suck, and the stuff we can buy with the money from our jobs just keeps getting worse. Movies are giant commercials for their own tie-in merchandise. TV shows are filmed on higher quality cameras, but that didn't upgraded the writing, it just made everyone buy new TVs. Video games are delivery systems for their own online casinos, where you use real money to buy fake money to buy a chance to gamble on a sweet paint job for your fake gun. And with your luck, it'll probably turn out to be "Grey" or something. Oo-oo, grey. Our cups runneth over with suckage. And how the hell's a body supposed to satirize all that? Most of it's not even funny, just aggressively, stupidly absurd.
On the other hand, a lot of it's absurd. String enough absurdities along and you create an avalanche and those are always funny. Take job interviews. The lower you go down into the hell that is the "sales industry" the more of a farce they become. Just once I would've like one of my future managers to say, "I don't care if you've got experience for this, I'll hire damn near anyone." The moment that happened in the first scene of this film I knew, "This one's a keeper. Somebody's been there."
Sorry to Bother You is the story of Cassius "Cash" Green – just a dude from Oakland trying to get by in our slow-motion apocalypse. Maybe move out of his uncle's garage so he and his girlfriend, Detroit, can get it on without the automatic door exposing them. He joins the telemarketing firm RegalView and eventually has some success selling encyclopedias to…whoever's dumb enough to buy encyclopedias these days. (Keep 'em for bookshelf ballast, Chief.) He finds this success by discovering his "white voice," (overdubbed by David Cross). As an older coworker, Langston, (played by Danny Glover) explains to him, "It's not really a white voice. It's what they wish they sounded like. What they think they're supposed to sound like." As in, "Hi, this is Dave with SomeBullshitCompanyThatWentBankrupt. Sorry to bother you, but I'm just calling to save you a bundle on long distance phone service…" Ugh.
This gets Cash a promotion to the top floor, where RegalView sells I-can't-believe-it's-not-slave-labor, provided by its number one client, WorryFree. WorryFree is the OmniConsumerProducts of this movie's dimension, if you crossed OCP with Amazon's warehouses. Led (as so many OCPs are these days) by a coked-up, Silicon Valley shithead named Steve Lift (played wonderfully by one time Lone Ranger Armie Hammer), who's like a cross between Steve Job, if Jobs had had an actual personality, and Richard Branson, if Branson hadn't run out of ideas in the mid-80s. Lift has a plan to increase the productivity of his ever-growing, lifetime-contracted workforce by decreasing their humanity. Lift makes the mistake of sharing his grand plan with Cash, so it's up to Cash to stop it…provided he can find anyone who'll believe him. Or who cares.
That's the spoiler-free, elevator-pitch version of the movie, and you should know by now that I care about spoilers as much as most people care about the ants on their countertops. There's a bit in the first ten minutes, where Cash goes into the VIP room of a local, low-rent club. He finds no room to sit, no one to have a conversation with, gets a drink spilled on his shirt…and yet still comes out saying, "That's some baller shit." This is a massive spoiler for the entire rest of the movie. The kind of thing some of us used to call "foreshadowing." So: fair warning and last chance. Go see this movie because it's good. And I'm about to talk about it.
The good thing about dystopian sci-fi satires is, you can indite pretty much every level of your society for all it's bullshit in one go. Most of the bullshit revolves around creating buzz and has fuck-all to do with any other goal. The actual goal is to make more money for people who're already rich, but the rich and their running dogs are still (in spite of everything) squeamish about saying that out loud. Instead, our day-shift managers dress up mundane tasks in the language of warfare and organized crime to try and make stupid bullshit sound cool. We have to "bag and tag" our sales prospects like a squad of telemarketing Chris Kyles, but also pretend our workplaces are all one big, happy family, and asking for a raise is just as gauche as asking for more allowance money when it isn't your birthday. Our managers would argue that social capital is more important, because of course they would. They're managers – they got out of the sales game as soon as possible. At least Erik Prince pays his mercenary army a living wage…as far as I know.
But everything old is new again. That's why mercenary armies and legal slavery have made such big comebacks. Just as bad, but dumber than ever, drenched in twee slogans, like a vampire that sparkles. "Stop worrying and get WorryFree," the commercial for our villain's company says. Because when your only other options are things like "telemarketer" or "sign twirler" or "charge your family members rent so you can pay the inflated mortgage on your over-valued house until the bank takes it from you anyway"…well, the evil voices in your head start to chatter about, "Three hots and a cot," like Cash's uncle says. Like we all used to say…about prison. Take it from someone who was a telemarketer while his girlfriend was a sign twirler. Though mine never asked me to stop talking about the sun exploding. She was all about those zombie apocalypses.
Working front-line sales (see? Even I slip into martial metaphors) is an exercise in constant humiliation. As such, the film's illustration of what it's like, with Cash literally dropping into the lives of total strangers, is spot-on. Cold-calling catches people at their most intimate moments, and either they hang up on you immediately…or they start telling you about the everyday horrors of their lives. Here's a person so obviously and desperately aching for a single moment of true, undiluted human connection that they'll tell you – a total stranger, completely unbidden – about their husband's insanely expensive cancer treatments, say…and you'll have no choice but to "stick to the script." It's disgusting and degrading and you feel like an asshole doing it…because you are. You've been turned into one out of what you tell yourself is necessity. It's no wonder sociopathic bastards rule everything around us, and that we are constantly pressured to become sociopathic bastards in order to get ahead. "I finally feel like I'm good at something," Cash says, once he starts selling. Whether you're good at something worthwhile doesn't even enter into it…until it's too late. Why do you think I quit in 2010 to try and get Internet Famous?
In the sales trenches, Cash meets union organizer Squeeze, and that's the most science fictional thing in this film, hands down. During my ten-plus years doing Regalview-level work, union organizing existed in a limbo, somewhere between a fondly hoped-for dream and a literal joke. "Gee, this sucks," we'd say, as we huddled around the smoker's ghetto, complaining about the latest dumb thing we'd be forced to do, "we should form a union, ha-ha." The fact everyone is not summarily fired the moment they do their first protest is the second most sci-fi thing in this film.
Instead, Cash is promoted. That's the "meritocracy" people talk about – kick the talented upstairs before they give the rest of us any bright ideas. Sure, you'll abandon all your friends to drudgery and miserable toil…but hey, at least you'll get to drink on the job. There's a lot of drinking up on the top floor, with the other Power Callers. Granted, the extra money will help you pay off the family debt and get a space that's all your own…but even that, relatively miniscule, once-taken-for-granted amount of power will alienate you from your friends. And significant others. "I'm about to get paid," Cash says, the first time he crosses the picket line. "We're all trying to be paid," Squeeze retorts, and if we don't all hang together, we'll most assuredly hang separately.
Contrast Cash with Winston from 1984, Sam from Brazil, and Guy Protagonist from Fahrenheit 451. (Bernard, from Brave New World is a coward and a narc, so fuck him.) All four of them begin as low-level drones of the systems their trapped in. Guy is a loyal enforcer…at first…while Winston and Sam know how fucked they are thanks to their positions as shit government employees. All can only impotently rail against their systems in the utmost privacy. Cash begins as a survivor, just trying to get along, but his total lack of ideology allows Sorry to Bother You to dramatize how his system (our current system) turns even the most well-meaning into Winstons, Sams and Guys. All three of them began their radicalization out of what they mistook for love, because they lived in fascist bureaucracies that legislated love out of existence long before their stories began, leaving them nothing to fall back on but their own hormones. Cash begins things in a stable relationship, but his lack of awareness of how the system's changing him strains that past the breaking point. He becomes a bourgeois bastard, the most annoying person to live with, because all they truly care about is "trying to get paid."
Cash's love-interest, Detroit, is a parable of the modern arts and how we artists (and yes, I'm still pretensions enough to count myself and all my colleagues among them) interact with the bourgy bastards of the world. We've been trying to shock them out of their drone-like complacency for over 200 years. It's been loads of laughs, but all it really seems to do is make them more reactionary (as long as reaction comes with the correct, local brand signifiers). This in turn makes us try to shock them even harder with increasingly self-defeating, and occasionally self-destructive, pieces. Usually riffing on Marina Abramovic's "Rhythm 0," only you recite excerpts from The Last Dragon while people throw shit at you. That's what separates your performance art from the sadistic game show that everyone in this movie's world watches every night – "I Got the Shit Kicked Out of Me." That, and the size of your audience. Even the so-called avant garde is drowning in ruinous nostalgia for the 1970s. What is this, the 1990s? Still?
Even if you get big, what's the point? The top of the socio-economic heap is overrun with narcissistic dipshits, so bored with their world-traveling, orgy-filled lives that their fondest wish (apart from making more money) appears to be getting away with saying the N-word in public. And they have the gall to call themselves "rational." "This isn't irrational," they'll say, about their latest dumb-ass plan, whether its cars with auto-pilots that can't stay between two straight lines, blood-testing machines that don't take blood samples, turning people into horses so they can lift more boxes per minute, or turning your best salesman into a horse-person so he can be your controlled opposition. The Matrix, which built-in it's own controlled opposition to patch over an original, systemic flaw it never adequately addressed, was immanently rational in its own solipsistic way. That's the problem with rationalism: these days, most people use it as a synonym for what they already believe.
There's a book about this, called Voltaire's Bastards, by John Ralston Saul, and if more people had spent the 90s reading him than Christopher Hitchens bullshit, the world would be a much better place. Here's a not-at-all-random quote: "Almost without exception they are bullies. Primarily this appears to be intellectual intimidation. Combined with the use of secrecy and systems manipulation, it is used to frighten people on the practical level of their incomes, pensions, and careers." And here's another, from a little later: "The technocrats are hedonists of power. Their obsession with structures and their inability or unwillingness to link these to the public good make this power an abstract force — a force that works, more often than not, at cross-purposes to the real needs of a painfully real world." But please, feel free to write me a novel-length comment about how you just know Elon Musk is going to save us all because he watches the same cartoons you do. Sounds imminently rational.
That's the other side of all the pointless conspiracy theorizing these days: the waiting around for a savior. Most of the creep-tastic shit in our world occurs right out in the open and you can find it without going down any rabbit holes that lead to Anime Nazi message boards. There will be no more Woodwards (the one we have has gone way down hill in his old age), no more Bernsteins. The rich stopped caring a long time ago, secure that their money can and will let them get away with…whatever. You can catch them committing their various crimes against humanity on video and all your exposé will do is make their stock rise faster. The one thing – the only thing – that'll even begin to make a difference is if we all unite into an overwhelming, revolutionary force and overthrow this goddamn, shit-sucking, vampire capitalist system.
It won't be easy. The cops will shoot us and beat us down, or let their fascist friends do it while they look the other way…but guess what? They're already doing that, even in my own Fair City of roses and water. Our current Chief of Police is from Oakland, just like this film's writer/director, Boots Riley. She got the job because her predecessor got caught skipping out on training exercises and having subordinates sign in for him. And he only got the job because his predecessor straight-up Dick Chenney'd a friend while they were drunkenly bird hunting. Like I said, we're ruled over by total dumbasses and don't have much left to loose.
Except our illusions that we live in a normal, functional society. Those are the hardest to give up (both in our reality, and this film's) because most of our society is designed to keep them intact. Which is why artists keep feeling the need to couch their societal critiques in sci-fi dystopias. They've always been more about the year they were made in, and that's been true since way before Orwell transposed those last two numbers in his title. The punchline here being Boots Riley finished this script in 2012, and we're only seeing the movie now.
It took this long because the independent movie funding scene – insofar as it ever existed – has been massively hollowed out by corporate conglomeration, and the fact everyone wants to try and be Netflix now. That's obviously bad…but it's hard to see the universe where this came in 2012 being any better. I remember 2012, and we were all so dumb back then.
Had this movie come out in 2012, it would've been either willfully misinterpreted, or worse: Ignored to Death. In fact, it kind of was. Once Boots finished the script, he made an album of the same name…and I didn't hear about it until last year, when the film came out. Again you fail me, internet, so I'm giving Riley props myself. Don't let this one slide into the memory hole. See Sorry to Bother You. It's good. Because it's true. "Maybe the artist is being literal."
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text:
package org.apache.shardingsphere.shardingscaling.core.controller;

import java.util.List;

/**
 * Sync process group.
 */
public interface SyncProgressGroup extends SyncProgress {

    /**
     * Get all sync progress in group.
     *
     * @return all sync progress
     */
    List<SyncProgress> getSyncProgresses();

    /**
     * Add sync progress to group.
     *
     * @param syncProgress sync progress
     */
    void addSyncProgress(SyncProgress syncProgress);
}

redpajama_set_name: RedPajamaGithub


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Bord Pleanala have failed to meet their current deadline of 22 March for a decision on the Ringaskiddy incinerator application and are to defer for a fourth time in order to request further information from the applicant, Indaver Ireland. No new date has been set.
CHASE is infuriated by this latest extension and questions the credibility of a process that minimises time given to the community to thoroughly examine an application while granting extra time to the developer first to prepare the application and then to correct it.
Following the 2011 refusal, Indaver opened pre-consultation talks with Bord Pleanala on 30 August 2012 and lodged the application on 13 Jan, 2016.
CHASE spokesperson Mary O'Leary said "We have been fighting this proposal in one form or other since 2001. It is a torturous process and this is a real kick in the teeth. Indaver have been engaged with Bord Pleanala on this application since 30 August 2012, that's over 4 and a half years ago. We are livid. Indaver have had every chance to get their homework right, they have failed to do so and they are still being spoonfed instead of being sent home. But the real question on everybodys lips is WHY?
Why are Bord Pleanala giving Indaver the opportunity to add further information at this stage, over a year after the application was submitted, 10 months after the oral hearing closed and 8 months after the statutory decision deadline of 12 July.
Why have Bord Pleanala not returned a decision when the Department of Defence stated categorically at the Oral Hearing that the facility would have strategic implications for the Irish State, that it would "create a flight safety hazard to Irish Air Corps helicopter operations" and that risk control measures would need to be implemented which would "impact on the Irish Air Corps' ability to operate helicopters into Haulbowline".
Why have Bord Pleanala not returned a decision when the final day exposed false dioxin figures in Indavers application so serious that the Inspector was forced to break and take legal advice.
CHASE steering committee will be meeting later this week to discuss the implications of this latest delay.


SAC administers a comprehensive insurance program that provides both aircraft (towplanes & gliders) and airfield insurance to clubs and individuals. The insurance is arranged through Jones Brown, an insurance broker located in Calgary.
Pilots insured through the SAC Insurance Plan must be members of the Soaring Association of Canada.
Pilots that fly with PowerFlarm in their gliders are also eligible for a 5% discount on their insurance through the SAC Insurance Plan.


text:
Q: Drawing Image on Android I need to draw an image on android, but I want to draw it row by row how can I do that with good performance.
Also, if I need to draw a random region in an image how could i get it in android....
I'm totally new to the android programming.

A: This is all explained in the Canvas and Drawables developer guide.
Basically the Canvas API "provides a set of 2D-drawing APIs that allow you to render your own custom graphics onto a canvas".

A: https://developer.android.com/guide/topics/graphics/2d-graphics.html
http://androidcodesnippetsblog.blogspot.in/2013/01/drawing-image-using-canvas-in-android.html
try this this will help you.

redpajama_set_name: RedPajamaStackExchange


text:
\section{Introduction}

The galaxy population we see today has some very distinctive features.  One of the most fundamental is the separation of galaxies into a bimodal distribution according to colour (e.g. \citealt{strateva01,baldry06}).  The colour largely relates to the age of the stars, with galaxies on the tight red sequence being mostly passive systems containing old stars. In contrast, the galaxies in the blue cloud generally show a younger stellar population (e.g. Taylor et al. in prep).  However, it is still unclear what drives this separation.

Recent research has focussed on how blue star-forming galaxies can have their star formation quenched, moving them onto the red sequence.  Red-sequence galaxies are preferentially found in denser environments (e.g. \citealt{blanton05, cooper08, thomas10, smith12}) and star formation is also clearly suppressed in those high density environments (e.g. \citealt{lewis02,gomez03,kauffmann04}).  This immediately suggests environmental factors play an important role.

There is uncertainty, however, in how the change in star-forming properties as a function of environment manifests itself. \cite{balogh04} found that, once luminosity is taken into account, the observed environmental difference is only due to the {\it fraction} of blue galaxies changing in each environment, rather than due to any change in the properties of the galaxy population. Star formation rates measured from single-fibre observations of the H$\alpha$ emission line give similar conclusions: \cite{peng10} observed that the relationship between star formation rate and stellar mass was the same in the highest and lowest density environments. Recent results from the Galaxy And Mass Assembly (GAMA; \citealt{driver11}) survey also show that the fraction of star-forming galaxies falls with increasing environmental density \citep{wijesinghe12,robotham13}, but the star formation rate of the star-forming galaxies depends solely on their stellar mass, showing no change with their environment \citep{wijesinghe12}.  These observations would imply that any mechanism that transforms galaxies in dense environments must be rapid or have happened a long time ago.

In contrast, research examining the strength of the $4000\rm{\AA}$ break and the Balmer absorption lines \citep{vonderlinden10} and ultraviolet imaging from the \emph{GALaxy Evolution EXplorer} (GALEX) space telescope \citep{rasmussen12} suggests that both the star-forming fraction \emph{and} the star formation rate in star-forming galaxies changes as a function of environment, allowing for a longer timescale for any transformation.

The different conclusions drawn by these observations may have a number of causes, including the different ways that star formation and environment are measured, varying definition for star-forming galaxies and the inability of single-fibre observations to specify where that star formation is happening.  This last point is crucial given that the proposed mechanisms for any modulation of star formation with environment can have very different spatial effects:

{\it Ram-pressure stripping} \citep{gunn72,nichols11}, which can expel the gas from the disk, and {\it strangulation} \citep{larson80}, which results when the gas is removed from the halo, should both preferentially remove gas in the outer parts of galaxies (e.g. \citealt{bekki09,kapferer09}).  These processes may be efficient at removing halo gas, which is observed in galaxy clusters (e.g. \citealt{sun07,randall08}).  Ram-pressure stripping may also act in small and/or compact groups \citep{mccarthy08,rasmussen08} or on the outskirts of clusters (e.g. \citealt{merluzzi12}).   The timescale of $>2$ Gyrs for strangulation \citep{mccarthy08}, however, seems to contradict the short timeframe implied by observations. Although \cite{prescott11} find this to be the likely mechanism for the quenching of star formation in satellites hosted by isolated galaxies. Direct galaxy--galaxy interactions may also play a critical role in either triggering star formation (e.g. \citealt{moss93,ellison08,patton13}) or suppressing it, as seen in the less-massive galaxies of pairs when the pair mass ratio is large \citep{robotham13}.

Feedback from star formation in low-mass galaxies provides an internal mechanism for transformation.  This provides a solution to the mismatch of the theoretical dark matter halo mass function and the observed stellar mass function (e.g. \citealt{baldry08}) by heating and/or expelling gas in halos.  Extreme outbursts of star formation may be triggered by mergers or interactions (e.g. \citealt{hopkins09}) even with very low luminosity galaxies or tidal debris (e.g. \citealt{angel10,cluver13}), and frequently seen in isolated compact groups (e.g. \citealt{angel04,iraklis10,scudder12}).  This makes a link between internal and environmental effects.  There is observational evidence of feedback from star formation (e.g. \citealt{veilleux05,strickland09,angel12}).

At present it is still not clear which of these processes dominate in which situations.  In one of the first attempts to study spatially-resolved star formation in a very large sample as a function of a broad range of environment, \cite{welikala08, welikala09} used galaxy colours to demonstrate that star formation is suppressed in the central parts of galaxies in high-density environments, apparently ruling out ram-pressure stripping as a significant influence in the general galaxy population.

While galaxy colours are a coarse measure of the integrated star formation history of a galaxy, the well-understood H$\alpha$ emission line at 6563\AA\   probes near-instantaneous star formation ($< 10$~Myr, e.g. \citealt{kennicutt98}). Spatially-resolved H$\alpha$ measurements have only been made for samples of local galaxies either in the field or nearby clusters (e.g. \citealt{moss93,vogt04,koopmann04a,meurer06,fumagalli08,rose10,sanchez12}), often with narrow-band imaging, but have not been possible for a data set that covers a wide range in environment.

We present here observations of the spatially-resolved H$\alpha$ emission of galaxies over a wide range of environment from optical integral field unit (IFU) observations of galaxies selected from the GAMA survey.  The primary goal of this paper is to measure the radial distribution of star formation and examine how that varies as a function of environment.  We know that the star formation rates of galaxies are strongly dependent on their stellar mass, but their dependence on environment is less clear.  We therefore use GAMA to select a carefully controlled sample of galaxies with a narrow range of stellar masses ($M_{*}\sim10^{10}M_{\odot}$) in a range of environments.  GAMA is highly spectroscopically complete (97 per cent; \citealt{driver11}), even in the densest regions.  This is achieved by returning to each target area an average of $10$ times, as described in \cite{robotham10}.  This enables accurate environment measurements including 5th nearest neighbour surface densities (e.g. \citealt{wijesinghe12}) and friends-of-friends group determination \citep{robotham11}.

We describe the selection of our sample in Section \ref{sect:sample} and the observations in Section \ref{sect:observations}.  In Section \ref{sect:emissionlines} we describe the method for measuring the emission line properties and then present the total star formation rates and H$\alpha$ surface brightness profiles of the sample in Sections~\ref{Sect:SFR} and \ref{sect:profiles}. We discuss our findings in Section \ref{sect:discussion} before summarising our conclusions in Section~\ref{sect:conclusions}.  Throughout this paper we assume a Hubble constant of $H_0=70$ km s$^{-1}$ Mpc$^{-1}$ and $\Omega_M=0.3$, $\Omega_\Lambda=0.7$.  Equivalent widths for features in emission are quoted as positive numbers.

\section{Sample}
\label{sect:sample}
We selected our sample from the Galaxy And Mass Assembly (GAMA; \citealt{driver11}\footnote{http://www.gama-survey.org}) survey which combines single-fibre spectroscopy \citep{hopkins13} with a diverse set of supporting imaging data.  We specifically selected galaxies from the first phase of the GAMA survey, referred to as GAMA I.  There are $\sim170,000$ galaxies in the GAMA I sample down to $r=19.4$ mag in two regions, each of 48 sq deg, and $r=19.8$ mag in a third region, also of 48 sq deg.  While the majority of the GAMA spectra have been obtained from the Anglo-Australian Telescope (AAT), the spectra and redshifts for brighter galaxies in these regions, like those targeted here, are obtained from the Sloan Digital Sky Survey (SDSS; \citealt{york00}).

In order to focus specifically on the effects of environment rather than stellar mass we targeted galaxies with stellar masses $6\times10^9M_{\odot}<M_{*}<2\times10^{10}M_{\odot}$.   The stellar mass measurements are from spectral energy distribution fits to optical broad-band photometry \citep{taylor11} and have random uncertainties of $\sim0.3$ dex. Given the size of the uncertainties, no narrower window in stellar mass would be appropriate.  We corrected the redshifts for the effects of peculiar velocity using the \cite{tonry00} multi-attractor flow model ($z_{\rm{TONRY}}$; \citealt{baldry12}) and limited the sample to low redshifts, $0.02<z_{\rm{TONRY}}<0.06$, so that targets are close enough that we can spatially resolve them.  This reduces the available sample to 688 galaxies.  We are complete in stellar mass over the redshift range considered.

The nearest neighbour surface density, $\Sigma_5$, is calculated for all galaxies with reliable redshifts (nQ$>2$; \citealt{driver11}) .  The 5th nearest neighbour metric is similar to the $\Sigma_1$ metric used in \cite{brough11}. The surface density is defined using the projected co-moving distance to the 5th nearest neighbour ($d_5$) with $\pm 1000$km s$^{-1}$ within a pseudo-volume limited density-defining population: $\Sigma_5=5/\pi d^2_5$.  The density-defining population has absolute SDSS petrosian magnitudes M$_r<$M$_{r,\rm{limit}}$-Q$z$, k-corrected to $z=0$ following \cite{loveday12}, where M$_{r,\rm{limit}}$= -20.0 mag and Q defines the expected evolution of M$_r$ as a function of redshift (Q=0.87; \citealt{loveday12}).  Densities are then corrected for the survey $r-$band redshift completeness as $\Sigma_5=\Sigma_{5,\rm{raw}}\times1/$completeness.  Galaxies where the nearest survey edge is closer than the 5th nearest neighbour have upper limits calculated and flags assigned.  More details on this and other environment metrics available for GAMA will be provided in Brough et al. (in prep).

There are 424 galaxies with stellar masses $6\times10^9M_{\odot}<M_{*}<2\times10^{10}M_{\odot}$ and $0.02<z_{\rm{TONRY}}<0.06$ that are not flagged as having been affected by a survey edge.  These 424 galaxies have environmental densities $0.02 < \Sigma_5 (\rm{Mpc}^{-2})<78$, with a median $\Sigma_5=0.77~\rm{Mpc}^{-2}$.  We randomly selected 18 galaxies across 2 density bins around the median density ($<0.77$ Mpc$^{-2}$; 11 galaxies and $>0.77$ Mpc$^{-2}$; 7 galaxies).  The surface density distribution of the 424 possible targets and the 18 selected are illustrated in Figure~\ref{dens_histo}.  The 18 targets selected have apparent SDSS petrosian magnitudes m$_r<17.6$ mag and a mean effective semi-major axis radius, from 2D Sersic surface brightness fits to re-processed SDSS r-band imaging \citep{kelvin12}, of R$_{e,r}=3.4^{\prime\prime}$.  The properties of the 18 observed galaxies from the GAMA survey are described in Table~\ref{sample}.

We determined the effect the number of the nearest neighbour used has on the sample selected and the results presented here.  We also calculated $\Sigma_ {N=10}$ for the parent sample considered here (galaxies with stellar masses $6\times10^9M_{\odot}<M_{*}<2\times10^{10}M_{\odot}$ and $0.02<z_{\rm{TONRY}}<0.06$). The mean difference $\Sigma_{N=5}-\Sigma_{N=10}=2.0$ Mpc$^{-1} \pm6.8$ Mpc$^{-1}$.  The median $\Sigma_ {N=10}=0.95$ Mpc$^{-1}$, which does not move galaxies between the high and low density bins defined here.  However, using N=10 a large fraction of this sample (12 out of 18) are affected by survey edges, we therefore present all of our results using N=5.

The GAMA groups catalogue \citep{robotham11} is not volume limited so we cannot draw strong conclusions from the group properties of these galaxies.  However, we do note that all galaxies in high-density environments are found in groups and that these generally have higher total dynamical masses ($7\times10^{12}M_{\odot}<M_{dyn}<4\times10^{14}M_{\odot}$) than the 3/11 galaxies in low-density environments that are found in pairs and groups ($7\times10^{11}M_{\odot}<M_{dyn}<7\times10^{12}M_{\odot}$).  For information we also indicate in Table~\ref{sample} whether the galaxies in groups are the central galaxy in their group (C), a satellite (S) or one of a pair of galaxies (P), where the group centre is defined following an iterative centre-of-light analysis \citep{robotham11}.  None of these galaxies are at the centre of a group.

\begin{figure}
\begin{center}
\resizebox{20pc}{!}{\includegraphics{dens_histo.pdf} }
\end{center}
\caption{Histogram showing the surface density distributions of the 424 possible targets (dashed line) and the 18 observed galaxies (solid line).  The dotted line indicates the median surface density of $0.77$ Mpc$^{-2}$ that divides the low and high density samples analysed here.  The observed galaxies sample the possible density distribution well and the low and high-density subsamples can be seen to be well separated.}
\label{dens_histo}
\end{figure}

\begin{table*}
 \centering
  \caption{Properties of the observed sample of galaxies from GAMA (described in the text).  The galaxies are divided into the two environmental density bins: high density (top of table) and low density (bottom of table).}
  \label{sample}
  \begin{tabular}{llllllllll}
  \hline
GAMA ID&RA&Dec.&Stellar Mass& z$_{\rm{TONRY}}$ &$\Sigma_5$  &Group Mass&   Central? &     R$_{e,r}$  &Sersic n$_r$\\
&J2000&J2000&Log(M$_\odot$)&&Mpc$^{-2}$ & Log(M$_\odot$)&&$^{\prime\prime}$ & \\
\hline

  136624&  11:43:17.06& -01:38:39.0 & 10.30  & 0.0463   &   16.33    &      13.8  & S &	2.24   & 	2.4    \\
  220328& 12:04:16.65& +01:32:46.5 &  9.83   & 0.0221    &  9.91         &  13.8 	& S	 & 5.20 & 	 	2.5 \\
  618152&  14:18:05.49& +00:13:38.6&  10.03  & 0.0543     & 8.25          & 14.6  & S& 	3.56 	 & 	0.9    \\
  227278&  14:11:19.16& +01:18:34.3&  10.13  & 0.0259     & 8.06       &    12.8   & S&	2.05 	  & 	2.6   \\
  600916&  09:12:06.92& +00:20:12.7& 10.05  & 0.0549     & 7.71     &      12.9  & S&	5.50 	 & 	1.1  \\
  136880&  11:45:20.90& -01:48:46.1 &  9.78    &  0.028     &  6.04    &       13.8   & S&	3.79 	 & 	1.6   \\
  600978&  09:12:45.34& +00:20:24.9 &  9.91   & 0.0549     & 4.89       &     12.9       & S&   	5.08 	 & 	0.8  \\
   \hline
  422359&   08:42:13.17& +02:37:28.6&  10.10  & 0.051     &  0.71    &       -            &    &  	2.47 	 & 	1.6  \\
  106252&   14:21:05.39& +00:51:54.3&  9.83  & 0.0550     &  0.65    &       -            &      &	2.34 	 & 	0.6 \\
  227962&  14:22:01.09& +01:11:50.3&  9.88   & 0.0558     & 0.42       &    12.8 	 & S	& 2.02	  & 	0.9  \\
  92770&     14:30:14.98& +00:37:17.0&   9.87    & 0.0271     & 0.31      &     -             &   &  	3.28   & 	1.2  \\
  418448&   09:04:50.24& +02:30:23.3&  10.02   & 0.0557    &  0.26    &       -          &      & 2.03 	 & 	2.5 \\
  375909&   08:45:32.05& +01:17:36.0&  9.96  & 0.0450      & 0.14       &    12.9 	 &  P	&4.23 	 & 	0.8     \\
  536005&   12:00:00.48& -01:01:40.7& 10.09 &  0.0483     & 0.12     &      -            &     & 2.62 	 & 	1.4 \\
  535319&  11:49:15.69& -00:58:36.9&   9.89   & 0.0606     & 0.09        &    11.9  & P	&4.08 	 & 	0.8     \\
  55150&    12:03:01.01& -00:17:28.2&  10.09  & 0.0417     & 0.06        &   -             &     &	4.47  &  	0.7  \\
  371177&  08:41:39.24& +00:58:26.7&   10.03 &  0.0608     & 0.06       &     -          &      &  2.63 	 & 	1.7  \\
  583637&  11:43:17.98& -00:10:53.8&   10.01 &  0.0577     & 0.03       &    -          &     &	 3.28  & 	1.2  \\
 \hline
\end{tabular}
\end{table*}

\section{Observations}
\label{sect:observations}
The data were taken in 2011 April,  2012 February and 2012 May with the SPIRAL IFU. SPIRAL is a $32\times16$ element rectangular microlens array coupled via an optical fibre feed to the dual-beam AAOmega spectrograph \citep{saunders04, sharp06}.  It has a spatial sampling of $0^{\prime\prime}.7$/spaxel with no gaps, giving a field of view of  $22^{\prime\prime}.4 \times 11^{\prime\prime}.2$.  We observed with the low-resolution 580V grating in the blue and the higher resolution 1000R grating in the red.  These settings correspond to wavelength ranges of $3700-5700\rm{\AA}$ and $6200-7300\rm{\AA}$ and spectral resolutions of 1900 and 5000 respectively. Accounting for the sample redshift range, this targets the emission lines H$\beta$ in the blue and H$\alpha$ in the red.  Observations were made during dark time, with an average seeing of $1.5^{\prime\prime}$ (FWHM). Each galaxy was observed for $3\times2400$s with individual observations dithered by 1-2 spaxels in Right Ascension and Declination in order to avoid four isolated dead elements in SPIRAL.  Spectrophotometric standard stars were also observed each night, in order to prepare a sensitivity function.

Initial data reduction, from raw detector output to dark-subtracted, bias-subtracted, wavelength-calibrated, sky-subtracted, 1D-extracted spectra, was achieved using the \texttt{2dfdr} pipeline \citep{croom04}.  The root mean square dispersion around the wavelength solution is $0.12\rm{\AA}$ in the blue and $0.03\rm{\AA}$ in the red spectra.  The dispersion around the $5577\rm{\AA}$ sky line is $0.09\rm{\AA}$.  Twilight flat-field frames were also observed in order to account for relative fibre-to-fibre transmission variations.  As none of our targets completely fill the SPIRAL field-of-view a sky background spectrum was calculated by taking the median over pixels without galaxy light.  The final data analysis was carried out using custom IDL routines.  The sensitivity function determined from comparing the total observed flux from spectrophotometric standard stars to that predicted as a function of wavelength was applied.  The final flux calibration was done by applying SDSS $g$- and $i$-band fiber magnitudes (measured in the $3^{\prime\prime}$ SDSS fibre) to the blue and red SPIRAL spectra integrated over a $3^{\prime\prime}$ aperture respectively for each galaxy.  The calculated offset was then applied to the individual SPIRAL spectra.  Comparison with the flux-calibrated SDSS spectra indicates a 6 per cent uncertainty in the flux calibration level of the blue spectra (covering the H$\beta$ line) and 10 per cent in the red spectra  (covering the H$\alpha$ line).  Following flux calibration individual frames were aligned and mosaiced using telescope offset information. Frames are scaled based on a comparison of overlap regions in the mosaic, to account for minor variations in transparency and seeing.

\section{Emission-Line Measures}
\label{sect:emissionlines}

In order to examine the radial distribution of star formation, high signal-to-noise spectra were produced by combining spectra within annuli for each galaxy. Each annulus is defined as a radial de-projection of the galaxy, based on position angle and inclination information derived from GAMA analysis of SDSS imaging data \citep{kelvin12}. Prior to stacking, each spectrum from individual spaxels is velocity matched based on a velocity fields derived from emission and absorption fits to a block-averaged (3x3 spaxel) data-cube. The [N\textsc{ii}], H$\alpha$, [N\textsc{ii}] region is fitted with a four component model, three emission lines and H$\alpha$ absorption, assuming common velocities and widths for the emission components and with the ratio of the flux of the nitrogen lines fixed at 3.28. The emission redshift is allowed to float with respect to that of the absorption line. Errors are estimated from a quadrature summation of the statistic values returned for the best-fit model and the parameter distribution from a bootstrap re-sampling of each composite spectrum.

Individual Gaussian fits to the H$\alpha$ and H$\beta$ emission lines in each spaxel of each SPIRAL data-cube were also made for examination purposes. The resulting H$\alpha$ flux and velocity maps as well as SDSS thumbnail images for the same field-of-view are shown for each galaxy in Appendix~\ref{maps}.  The maps are presented in order of environmental density (highest density environment first).  There are some interesting features in the H$\alpha$ flux maps including off-centre (600978, 92770, 371177) and clumpy emission (618152, 535319, 55150, 583637).  \cite{gerssen12} also observe clumpy emission in their VIMOS IFU observations of SDSS galaxies.  Two of the off-centre and clumpy emission features are in galaxies in high-density environments (618152 and 600978; $29^{+20}_{-11}$ per cent), while the remaining 5 are in galaxies in the low-density environments ($45^{+15}_{-13}$ per cent).  We conclude that off-centre and clumpy H$\alpha$ emission does not significantly depend on environment in our data.

The H$\alpha$ velocity maps (Appendix~\ref{maps}) show that all galaxies with strong H$\alpha$ emission show ordered rotation in that emission line, even when the emission is clumpy or off-centre.  This is consistent with observations at higher redshifts showing that clumpy galaxies are well fit by ordered disk models (e.g. \citealt{wisnioski11}).

\section{Star Formation Rates}
\label{Sect:SFR}

We first examine the total star formation rates (SFR) of the galaxies.  The total SFR measurements are made by summing the obscuration-corrected H$\alpha$ flux ($f_{H\alpha}$ [ergs s$^{-1}$ cm$^{-2}$]) over the observed extent of the galaxy.  The flux is obscuration corrected using the Balmer decrement (BD; H$\alpha$ flux/H$\beta$ flux) measured in individual spaxels . The H$\alpha$ luminosity is then:
\begin{equation}
\rm{L}_{H\alpha} \rm{(W)}=4\pi d_L^2 ~f_{H\alpha} (BD/2.86)^{2.36},
\end{equation}
where $d_L$ is the luminosity distance in centimetres.  The Balmer decrement is a unitless obscuration sensitive parameter and its departure from the Case B recombination value of 2.86 indicates dust attenuation along the line of sight. While dust geometries are complex, this approach implicitly models the dust as a foreground screen averaged over the galaxy \citep{calzetti01}.  The exponent in the dust obscuration correction factor is equal to $k(\lambda_{H\alpha})/[k(\lambda_{H\beta}) - k(\lambda_{H\alpha})$], and $k(\lambda)$ at a given $\lambda$ is determined from the \cite{cardelli89} Galactic dust extinction curve (derived from observations of the UV extinction of stars). This is found to well describe the obscuration of the ionised gas in star-forming galaxies \citep{calzetti01,gunawardhana11}.  The SFRs are then calculated using the relationship given by \cite{kennicutt98} assuming a \cite{salpeter55} initial mass function (IMF), i.e. SFR $= \rm{L}_{H\alpha} \rm{(W)}/1.27\times10^{34}$.  These values are given in Table~\ref{SFRtable}.

\begin{table*}
 \centering
  \caption{Spectral measurements from IFU observations and the GAMA survey.  Total H$\alpha$ fluxes and obscuration-corrected star formation rates (SFR) are given for the IFU observations. The GAMA measurements (described in the text) are made from SDSS stellar absorption-corrected single-fibre spectra.  The column `Class' details whether a galaxy is classified as an AGN by GAMA and whether it would be classified as Star Forming (SF) or Non-Star Forming (NSF) by Wijesinghe et al. (2012). The galaxies are divided into the two environmental density bins: high density (top of table) and low density (bottom of table). Galaxy 220328 only shows H$\alpha$ in absorption and Galaxies 136880 and 227278 are active galactic nuclei (AGN).}
  \label{SFRtable}
  \begin{tabular}{lllllll}
  \hline
GAMA ID&f$_{H\alpha,\rm{IFU}}$ & SFR$_{\rm{IFU}}$&H$\beta$ EW$_{\rm{SDSS}}$ &BD$_{\rm{GAMA}}$ & SFR$_{\rm{GAMA}}$ & Class\\
&$10^{-17}$ergs s$^{-1}$ cm$^{-2}$ & $M_{\odot}$yr$^{-1}$& $\rm{\AA}$ &  & $M_{\odot}$yr$^{-1}$\\
\hline
      136624   &   266 &   0.02&      0.10	  & 1.50     &   0.01 &  NSF\\
      220328     & -  &-&-0.08   &  2.42      &    0.01 & NSF\\
      618152      &618 &    0.79&  4.21    &  4.57    &      1.58 &    SF\\
      227278      &85    &-&       0.66   & 3.37    &      -   &  AGN\\
      600916      &276    & 0.35&         1.46  &   5.09         &   0.79  &   NSF\\
      136880      &44    &-&      0.10  &  5.22 &         -  &   AGN \\
      600978      &1608  &    1.92&        6.92  &   3.96  &        2.14 &     SF\\
      \hline
      422359 &     1328      &1.62&         6.10  &   4.32  &        2.13  &    SF\\
      106252   &   165     &0.19&   3.23   &   5.13  &        0.64  &   SF\\
      227962     & 1930    &  2.36&  8.38   &   3.61   &       1.87   &   SF  \\
      92770     &366    &0.07   &  0.69   &  3.07      &     0.04  &  NSF     \\
      418448     & 793   &   1.03&   4.19  &    3.62     &     0.88    & SF    \\
      375909     & 2976   &   4.04&   8.43   &   4.85  &        5.09   &   SF\\
      536005      &2140     & 1.68&   8.76   &   4.57      &    4.11   &    SF\\
      535319      &1425     & 2.04& 6.42  &    3.75    &     1.72   &   SF\\
      55150     & 5630      &5.89&     5.91  &   4.27     &     4.26   &   SF \\
       371177     & 730      &1.37&  3.00  &    3.41    &      0.56   &  SF\\
      583637      &958      &1.42&   2.18   &   4.04   &       0.65   &  NSF\\
 \hline
\end{tabular}
\end{table*}

\subsection{Dependence on Environment}

We compare the total SFRs of the star-forming galaxies (SFR$_{\rm{IFU}}$) with their environmental density in the top panel of Figure~\ref{SFR}.  We note that the only absorption-dominated galaxy (galaxy 220328) in this sample is found in the highest density environment.  The observed mean SFR$_{\rm{IFU}}$ (low density)$=1.97\pm0.51$ is more than a factor of two higher than that at high density ($=0.77\pm0.42$). To determine the significance of an environmental dependence we apply a Kolmogorov-Smirnov two sample test to the SFRs in the low and high-density environments.  This gives a probability of 19.6 per cent that the two samples are drawn from the same parent population.  A Spearman rank correlation of the relationship between log10($\Sigma_5$) and log10(SFR), shows that the correlation between these parameters is only significant at the $1.8\sigma$ level.

Given the small size of our sample and the scatter observed we examine whether we can detect a significant relationship with environment.  We tested this by adjusting the mean SFRs of the galaxies in the high-density environments while maintaining their standard deviation and re-ran our statistical tests.  A weakly significant correlation between environment and SFR is observed (at a $2.3\sigma$ level) if the mean SFRs in high-density environments are a factor of 5 lower than those in the low-density environments (a factor of 2 lower than observed).

We observe a weak but not significant relationship of SFR with environment in this sample.  Due to the small sample size and observed scatter we cannot draw a strong conclusion about a universal SFR dependence, or lack of, on environment.

\begin{figure}
\begin{center}

\resizebox{18pc}{!}{\includegraphics{halpha_SFR_dens.pdf} }

\end{center}
\caption{Total star formation rates of the star-forming galaxies as a function of environmental density.  The dashed line indicates the median surface density of 0.77 Mpc$^{-2}$ that divides the low and high-density subsamples analysed here.  There is a weak correlation between log10(SFR$_{\rm{IFU}}$) and log10($\Sigma_5$), significant only at the $1.8\sigma$ level.  We indicate which galaxies would have been classified by Wijesinghe et al. (2012) as star forming (squares) and non-star forming (triangles); some of those classified as non-star forming are still forming stars.  }
\label{SFR}
\end{figure}

\subsection{Comparison with Wijesinghe et al. (2012)}

We use the total SFR measurements made from our IFU observations to analyse the \cite{wijesinghe12} star-forming galaxy classification.  They define star-forming galaxies as those not classified as active galactic nuclei (AGN) using the \cite{kewley01} definition with non-absorption corrected H$\beta$ equivalent widths (EW) $> 1.5\rm{\AA}$, BD $< 15$ and SFR $> 10^{-3}M_{\odot}$yr$^{-1}$.  We use the single-fibre GAMA measurements to determine whether our sample would meet their star-forming classification.

GAMA utilises the MPA/JHU emission-line catalogue\footnote{http://www.mpa-garching.mpg.de/SDSS/DR7/} to obtain absorption-corrected line fluxes and equivalent widths (EW) for these bright galaxies.  These line measurements are made from stellar absorption-corrected SDSS spectra.  The GAMA SFRs are calculated as described in \cite{hopkins13} and \cite{gunawardhana13} and are given in Table~\ref{SFRtable}.  In summary, the H$\alpha$ luminosity is calculated from the H$\alpha$ EW, which is aperture corrected and extinction corrected using the Balmer decrement as per the IFU measurements.  The GAMA SFRs are then calculated using the \cite{kennicutt98} relationship.  We note that dust obscuration is not excessive in any of the galaxies in this sample: their mean Balmer decrements are $3.9\pm0.9$ (Table~\ref{SFRtable}) which translates to a dust obscuration factor of $\sim2$.

\cite{wijesinghe12} do not correct H$\beta$ equivalent widths for stellar absorption for the definition of their star-forming sample, however, they do correct H$\alpha$ equivalent widths by adding a constant correction of $0.7\rm{\AA}$.  We therefore use that addition here, i.e. stellar absorption corrected H$\beta$ EW$>2.2\rm{\AA}$, to determine whether our sample would meet their star-forming classification.  Table~\ref{SFRtable} shows that 2 of the galaxies in this sample are classified as AGN from the single-fibre analysis and 5 do not make the \cite{wijesinghe12} star-forming classification, based on their H$\beta$ EW.  Figure~\ref{SFR} shows that 4 of these `non-star forming' galaxies are still forming stars at some level.  These galaxies are a clear indication of the need to take care when separating galaxies into distinct star-forming and non-star-forming populations.

\subsection{Aperture Corrections}

\begin{figure}
\begin{center}

\resizebox{18pc}{!}{\includegraphics{halpha_SFR.pdf} }

\resizebox{18pc}{!}{\includegraphics{halpha_SFR_Brinchmann.pdf} }
\end{center}
\caption{Comparing total star formation rates from IFU and single-fibre observations of the star-forming galaxies.  The solid lines indicate the 1:1 relationships. The \emph{top panel} shows the comparison between the total IFU star formation rates and the total aperture-corrected GAMA single-fibre star formation rates.  The mean ratio is $\rm{SFR_{GAMA}} / {\rm SFR_{IFU}}=1.26\pm0.23$.  The \emph{lower panel} shows the comparison between the total IFU star formation rates and the total SDSS single-fibre SFR aperture-corrected as per Brinchmann et al. (2004).  The mean ratio $\rm{SFR_{Brinchmann}} / \rm{SFR_{IFU}}=1.34\pm0.17$. The aperture-corrected SFRs are in relatively good agreement with those from the IFU measurements, no matter which aperture correction method is used. However, the uncertainties can still be large for individual systems.}
\label{aperture}
\end{figure}

Calculating the total SFR of galaxies from single-fibre observations requires a correction for the portion of the galaxy enclosed by the size of the fibre used: an aperture correction.  In the GAMA survey the total SFR is calculated by aperture correcting the H$\alpha$ flux measured within the fibre following the method of \cite{hopkins03}.  This aperture correction relies on the assumption that the line emission scales directly with the stellar continuum, as measured by the $r$-band magnitude.  However, there is obviously some uncertainty in that assumption.  We use the total SFR measurements made from our IFU observations to analyse this correction further.  The IFU SFR are compared to the GAMA SFR in the top panel of Figure~\ref{aperture}.

We do not include either galaxy 220328 or the two AGN in this analysis due to a lack of observable star formation and AGN contamination respectively.  The mean difference $\rm{SFR_{GAMA}} / \rm{SFR_{IFU}}=1.26\pm0.23, \sigma=0.90$ i.e. SFR$_{\rm{GAMA}}$ is on average 26 per cent higher than SFR$_{\rm{IFU}}$ with a broad dispersion (the standard error on the mean is calculated as $\sigma/ \sqrt N$).

\cite{gerssen12} analysed the aperture correction applied to calculate total SFR from SDSS spectra by \cite{brinchmann04} using IFU observations of 24 star-forming (H$\alpha {\rm EW}> 20\AA$, $f_H\alpha>448\times10^{-17}$ergs s$^{-1}$ cm$^{-2}$), low-mass ($1\times10^8M_{\odot}<M_{*}<3\times10^{10}M_{\odot}$) SDSS galaxies. They found the \cite{brinchmann04} aperture corrections to underestimate the total SFR by a factor of 2.5 with a dispersion of 1.75, significantly larger than the factor of 1.26 difference and 0.90 dispersion we find between our IFU SFR and the GAMA aperture-corrected SFRs.  We analyse whether the GAMA aperture correction is significantly different to that used by \cite{brinchmann04} by also comparing SFR$_{\rm{IFU}}$ with the most recent total SFR estimated by Brinchmann for the SDSS DR7 data release\footnote{These are the total values given in gal\_totsfr\_dr7\_v5\_2.fits available at: http://www.mpa-garching.mpg.de/SDSS/DR7/sfrs.html} in the bottom panel of Figure~\ref{aperture}.

\cite{brinchmann04} determine total SFRs using a Bayesian approach to calculate the likelihood of fits of the observed spectrum to \cite{charlot01} models, which incorporate an obscuration model. They note that, to first approximation, the dust corrections are based on the H$\alpha$/H$\beta$ ratio.  The \cite{brinchmann04} total SFR are calculated with a \cite{kroupa01} IMF and we convert to the \cite{salpeter55} IMF used here by multiplying their measurements by 1.5. They aperture correct in an empirical manner using the distribution of the SFR/M* ratio at a given ($g-r, r-i$) colour and the photometry outside the fibre to correct the fibre SFR. This aperture correction is updated for the DR7 data release by calculating the light outside the fibre for each galaxy, and then fitting stochastic models to the photometry.

We find a mean difference $\rm{SFR_{Brinchmann}} / \rm{SFR_{IFU}}=1.34\pm0.17, \sigma=0.67$, i.e. we also find that the Brinchmann correction overestimates the SFR.  This is a much smaller difference than \cite{gerssen12} found.  This also suggests a marginal trend toward higher SFR estimates by aperture correcting using either method, although again with a high dispersion. These results suggest that contrary to the claim by \cite{gerssen12}, the aperture-corrected SFRs for these low-mass galaxies are in relatively good agreement with those estimated from the IFU measurements, no matter which method is used. The large dispersion does however mean that the uncertainties can still be large for individual systems. In addition, this is still only a small sample, and reliable statistics on total SFR estimates compared to those from aperture-corrected measurements will need a much larger sample.

\section{Radial H$\alpha$ Profiles}
\label{sect:profiles}
We determine whether any dependence of SFR on environment is evident in the spatial distributions of H$\alpha$ emission in these galaxies.

The H$\alpha$ surface brightness is calculated by dividing the summed flux in each elliptical annulus by the area of the annulus.  These radial profiles are shown in Figure~\ref{profiles}.

\begin{figure}
\begin{center}
\resizebox{20pc}{!}{\includegraphics{halpha_profR.pdf} }
\end{center}
\caption{Radial H$\alpha$ surface brightness profiles as a function of the effective radius of the galaxy.  Solid lines show galaxies in low-density environments ($<0.77$ Mpc$^{-2}$) and dashed lines show galaxies in high-density environments ($>0.77$ Mpc$^{-2}$), dotted lines indicate regions that do not show emission above the detection limit of $2\times10^{18}$ ergs s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$ and dot-dashed lines indicate the emission of the two AGN.  The average seeing approximates to R/R$_{\rm{e}}\sim0.2$.  The profiles do not show a dependence on environment.
}
\label{profiles}
\end{figure}

Figure~\ref{profiles} shows that the radial H$\alpha$ surface brightness profiles of galaxies in both environments (solid and dashed lines) are very similar to one another, being centrally concentrated with high surface brightnesses over all radii studied.  In contrast, the surface brightness profiles of the galaxies with no emission above the detection limit of $2\times10^{18}$ ergs s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$ (dotted lines) are only present in the highest density environments.  Of these, galaxy 220328 is dominated by absorption and the 2 AGN (136880, 227278) show central emission (dot-dashed lines) and no significant emission beyond that.

We further analyse the relationship of the profiles of the star-forming galaxies with their environment with straight-line fits to the H$\alpha$ surface brightness profiles taking into account the uncertainties in the H$\alpha$ flux measurements.  We do not include the 3 galaxies with undetected emission in this analysis.  We show the fitted gradient and intercept values and $1\sigma$ errors of the 15 star-forming galaxies as a function of environment in Figure~\ref{profile_fits}.

We test the correspondence between these parameters with a Spearman rank correlation, finding that the gradients are correlated with log10($\Sigma_5$) at a significance of only $0.25\sigma$ and the intercepts are correlated at a significance of $0.4\sigma$.  There is no dependence of the radial distribution of the H$\alpha$ emission as a function of environment.

\begin{figure}
\begin{center}
\resizebox{20pc}{!}{\includegraphics{halphaprof_dens.pdf} }

\resizebox{20pc}{!}{\includegraphics{halphaprofinter_dens.pdf} }
\end{center}
\caption{Parameters of straight-line fits to H$\alpha$ surface brightness profiles of the star-forming galaxies as a function of environmental density.  The \emph{top panel} shows the gradient of the fits. The gradients are correlated with environment at a significance of only $0.25\sigma$.  The \emph{lower panel} shows the fitted intercept.  The intercepts are correlated with environment at a significance of $0.4\sigma$.  The error bars show the $1\sigma$ uncertainties on the profile fits. The fits to the surface brightness profiles do not show a dependence on environment.}
\label{profile_fits}
\end{figure}

The galaxies observed here all have very similar stellar masses and we are observing no significant dependence in either H$\alpha$ surface brightness profile shape or amplitude of the star-forming galaxies as a function of environment.

\section{Discussion}
\label{sect:discussion}

We have presented observations of the spatially-resolved H$\alpha$ emission of galaxies over a wide range of environment with the aim of examining how the radial distribution of star formation varies as a function of environment.  We observe a weak but not significant difference in total star formation rate and no difference of radial profile of the star-forming galaxies' H$\alpha$ emission as a function of local galaxy environment in this sample of 18 galaxies with stellar masses $\sim10^{10}M\odot$.

Before making general comments on the effect of environment on star formation based on our observations, we show that our sample is unbiased and representative of the broader galaxy population in this narrow stellar mass range.  The uncertainties given below are $1\sigma$ binomial errors \citep{cameron11}.  There are 424 galaxies in GAMA with accurate surface densities (i.e. not affected by survey edges) that have stellar masses, $6\times10^9M_{\odot}<M_{*}<2\times10^{10}M_{\odot}$, and redshifts, $0.02<z_{\rm{TONRY}}<0.06$.  We use an updated version of the \cite{wijesinghe12} classification (those not classified as AGN with stellar absorption-corrected H$\beta$ EW $> 1.0\rm{\AA}$, BD $< 15$ and SFR $> 10^{-3}M_{\odot}$yr$^{-1}$) to quantify star-forming galaxies.  Of the 424 galaxies, there are roughly equal numbers of AGN in each environmental density: 21/212 ($10^{+2}_{-2}$ per cent) in low-density environments and 19/212 ($9^{+2}_{-2}$ per cent) in high-density environments.  There are 147/212 ($69^{+3}_{-3}$ per cent) of galaxies in low-density environments that would make our star-forming galaxy criteria and 93/212 ($44^{+3}_{-3}$ per cent) in high-density environments.

In the sample observed here, in the low-density environments, there are no AGN and 11/11 ($100_{-14}$ per cent) of the galaxies make the updated star-forming galaxy criteria.   In the high-density environment there are 2/7 ($29^{+20}_{-11}$ per cent) AGN and a further 2/7 non-star-forming galaxies, meaning that 3/7 ($43^{+18}_{-15}$ per cent) make our updated star-forming galaxy criteria.

We can conclude from this that the numbers of galaxies in this sample meeting the star-forming criteria in each environment are within $2.2\sigma$ of those in the broader sample.  This sample therefore follows the distributions of the general population.

The sample studied here is broadly representative of the general population and we find that the total SFRs of the star-forming galaxies do not depend significantly on their local environmental density (Figure~\ref{SFR}). However, due to the small size of the sample and the scatter observed we do not draw a definitive conclusion about a possible SFR dependence on environment.  Examining the spatial information provided by the H$\alpha$ surface brightness profiles, we observe no difference in amplitude or shape of the H$\alpha$ surface brightness profile of star-forming galaxies as a function of environment (Figures~\ref{profiles} and ~\ref{profile_fits}). We also find no evidence for `clumpiness' in H$\alpha$ emission depending on environment (Appendix~\ref{maps}).

The only comparable analysis to date examined the spatial star formation histories inferred from the colours of 44,964 galaxies in SDSS \citep{welikala08}.  They found that the mean star formation rate of each galaxy as a function of radius is dominated by star formation in the central regions of galaxies, and that the trend for suppression in high-density environments is driven by a reduction in that central star formation. They also find that the mean star formation rate in the outskirts is independent of environmental effects.  \cite{welikala08} conclude that the environment itself cannot suppress the star formation as the outer regions should otherwise be most affected and therefore this points to an evolutionary or AGN feedback origin.  We do not observe any significant radial dependence of the surface brightness of H$\alpha$ emission as a function of environment, either centrally or in the outer regions.  However, the suppression observed by \cite{welikala08} in their highest star-forming galaxies (SFR$>1.02M_{\odot}$yr$^{-1}$) is a factor of $<2$, of the order SFR$\sim0.002M_{\odot}$yr$^{-1}$.  This difference is significantly smaller than we can detect with these observations so we cannot rule out the suppression they observe.  \cite{welikala09} considered the density-morphology relation in the same sample, observing the strongest relation in the lowest luminosity galaxies with the highest star formation rates.  However, they conclude that it cannot solely explain the observed suppression of star formation in galaxies in high-density environments.  Table~\ref{sample} shows that 3 out of the 4 galaxies with Sersic $n_r>2$ are in high-density environments, of which 2 are not star forming. The mean $n$(high density)~$=1.7\pm0.3$ and (low density)~$=1.2\pm0.2$, suggesting that there are signs of a difference in morphology as a function of environment in our sample but that it alone does not explain the lack of significant dependence of star formation on environment.

If these observations are borne out in larger samples, then combined with the known decreasing fraction of star-forming galaxies as a function of increasing environmental density (e.g. \citealt{balogh04,baldry06,bolzonella10, mcgee11, wetzel12, wijesinghe12}) and the small numbers of galaxies in transition between star forming and non-star forming observed in large samples (e.g. \citealt{wijesinghe12, mendel13}), this would suggest that if environment does drive the change in fractional contribution it must either act very rapidly (the `infall-and-quench' model; e.g. \citealt{balogh04,bamford08,nichols11,wetzel13}) or have occurred a long time ago due to density-dependent evolution (an `in-situ evolution' model; \citealt{wijesinghe12}), such that galaxies in transition are rare at this time. In-situ evolution would involve galaxies in dense environments evolving faster than galaxies in low-density environments, building their stellar mass faster and earlier, leading to the observed morphology-density relation, and consistent with the measured SFR-density relations at both low and high redshift.  The in-situ evolution model is similar to `downsizing' \citep{cowie96}, `staged evolution' \citep{noeske07} and the `mass quenching' model of \cite{peng10}, however, galaxies of common mass would evolve differently in different environments in order to give rise to the observed population mix.  Transition redshifts, at which the dependence of the specific star formation rates of galaxies on increasing environmental density transitions from increasing to decreasing, have been observed (e.g. \citealt{elbaz07,greene12}) giving weight to this argument.

We note that there are some caveats to this argument.  Firstly, this is a small sample. A larger sample would increase the robustness of our results.  Our sample also does not reach the densest cluster environments where galaxies are observed to be affected by ram pressure stripping \citep{owers12,merluzzi12} and tidal distortions (e.g. \citealt{moss93, vogt04, bretherton13}).  Our choice of environmental metric may play a role as the SFRs of galaxies at a fixed stellar mass have been observed to increase as a function of increasing cluster-centric radius, rather than environmental density \citep{vonderlinden10,rasmussen12,haines13}.  In addition, \cite{vandenbosch08} argue that the relationship between SFR and environment is driven by evolutionary differences between central and satellite galaxies in a dark-matter halo and we are only studying satellite galaxies here. We will examine the effects of our choice of environmental metric in a forthcoming paper (Brough et al., in prep.).  Dust may also play a role as \cite{koyama13} find dustier galaxies in higher-density environments mask a trend of increasing specific SFR with increasing environmental density.

To separate the two scenarios of `infall-and-quench' and `in-situ evolution' and address these caveats requires observations of a very large sample of galaxies, covering a broad range of stellar mass and environment, in order to place stringent limits on the number density of any transition galaxies.  It will be crucial to detect the very faintest levels of star formation present, as well as its spatial dependence. This will require very high signal-to-noise IFU spectra to enable careful decomposition of emission and absorption contributions \citep{sarzi06}.  The new Sydney Australian Astronomical Observatory (AAO) Multi-object-IFU (SAMI; \citealt{croom12}) instrument with 13 deployable IFUs over a 1 degree field-of-view, and associated survey will enable this crucial next step.

\section{Conclusions}
\label{sect:conclusions}
We present observations of the spatially-resolved star formation as a function of local environment from optical integral field unit (IFU) observations of 18 galaxies with stellar masses $M_*\sim10^{10} M\odot$ selected from the GAMA survey.  Our conclusions can be summarised as:

\begin{itemize}

\item{The total star formation rates measured from the IFU data are consistent with the total aperture-corrected star formation rates measured from both the GAMA and SDSS surveys.  The mean differences are $\rm{SFR_{GAMA}} / \rm{SFR_{IFU}}=1.26\pm0.23, \sigma=0.90$; $\rm{SFR_{Brinchmann}} / \rm{SFR_{IFU}}=1.34\pm0.17, \sigma=0.67$.}

\item{Off-centre and clumpy H$\alpha$ emission does not depend on environment.  It is present in 2/7 ($29^{+20}_{-11}$ per cent) galaxies in high-density environments and 5/11 ($45^{+15}_{-13}$ per cent) galaxies in low-density environments show similar features.}

\item{In this sample, we see weak but not significant evidence of a dependence of total star formation rate on environment, using IFU observations for the first time. }

\item{We observe no clear environmental trend on the amplitude or shape of the radial profile of H$\alpha$ emission. This implies that, for this sample, there is no strong outside-in or inside-out quenching.}

\item{The lack of dependence of the radial profile of H$\alpha$ emission shape or amplitude on environment suggests that if environment drives the known change in fractional contribution of star-forming galaxies in different environments, it must either act very rapidly (the `infall-and-quench' model) or galaxies must evolve in a density-dependent manner (an `in-situ evolution' model), to explain the lack of transition galaxies observed in large samples.}

\end{itemize}

In order to identify more precisely how and when any transition due to environment occurs requires high signal-to-noise, spatially-resolved spectra as well as a very large sample that covers a range in stellar mass, environment and star formation stage, including post-starburst galaxies. The new Sydney Australian Astronomical Observatory (AAO) Multi-object-IFU (SAMI; \citealt{croom12}) instrument will address this with its associated survey.

\section*{Acknowledgments}

We thank the anonymous referee for their comments which greatly improved the paper.  SMC acknowledges the support of the
Australian Research Council via a Future Fellowship (FT100100457).  GAMA is a joint European-Australasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the Sloan Digital Sky Survey and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programs including GALEX MIS, VST KIDS, VISTA VIKING, WISE, Herschel-ATLAS, GMRT and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO, and the participating institutions. The GAMA website is http://www.gama-survey.org.

redpajama_set_name: RedPajamaArXiv


text:
Live Shows, Reviews	— October 31, 2017 at 7:26 am
Pennywise & The Bronx – The Enmore Theatre, Sydney – October 29, 2017
Approaching the famous Enmore Theatre on a very hot Sunday night I was immediately surrounded by hundreds of guys looking like they were straight out of a NOFX or New Found Glory video clip, this was 100% a very anticipated punk rock show.
Beerwolf – Sydney based punk rock band were first up and delivered a solid show embossed with a few classic (if you were a 14 year old Misfits fan) jokes. With such songs as "Eat Shit or Die" the band definitely appealed to their target audience.
Everyone seemed to be particularly stoked to see LA hardcore punks The Bronx in all of their glory! The ever excited frontman Matt Caughthran belted out "Sore Throat" off recently released album The Brvnx, as soon as Caughthran was finished with the opening track he swiftly jumped into the crowd, creating a circle pit and making fans absolutely ecstatic! Caughthran later delivered a pretty interesting speech addressing the crowd. "On the first day God created the Earth and the Heavens. On the second day God created man and woman in his image, third day <he paused> God created Australia, fifth – Enmore Theatre, sixth – Beerwolf, The Bronx and Pennywise and on the seventh – this event that we are all here for tonight." The crowd went absolute bonkers and I have never in my life had this much alcohol spilled on me! So much, I could've gotten blind drunk off it.
While Caughthran was having a ball delivering a stellar performance in the crowd, the rest of the band sounded and looked solid, while they seemed to be used to this kind of a show! Toby J. Ford and Ken Horne on guitar paced around and struck a pose or two, while Brad Magers on bass and David Hidalgo Jr, were perfectly in tune making every song sound twice as punchy as they normally are. The Bronx really looked and felt like a co-headliner with their over an hour set. It was a treat hearing such songs as "Heart Attack American", "Broken Arrow", "Knifeman", "Stranger Danger" and "They Will Kill Us(With Mercy)".
By the time everyone was ready to see the return of Pennywise the merch table got savaged and a few people were escorted out of the venue. It might've been a skate-punk show, but the crowd got as rowdy as at any hardcore/trash gig. Jim Lindberg takes the stage with his hands in the air and in that moment you could kind of guess that majority of people present are huge fans of the record that is "Full Circle"(1997) – 20 years on and for the first time Australians are about to hear it back to back! Apart from general ramble between the songs talking about meat pies, drugs and taking a dump, the band sounded very energetic and fun. I enjoyed a non-restricted view from the back balcony seats and during "Society". I have to admit, I've never seen that many people jump on stage and crowd surf, like ever. The drummer Byron McMackin had the most 90's drum kit ever and was constantly hiding behind the cymbals bopping to the beat of every song. After successfully going "Full Circle" with playing the album, Lindberg asked if the crowd were into Circle Jerks, The Misfits, Black Flag or Dead Kennedys while favouring a Circle Jerks cover of "Wild In The Streets". To everyone's surprise Fletcher Dragge started playing AC/DC's "TNT" topping it off with a classic sing-along that is "Stand by Me" and closing the night with "Brohymn" – by that time there was over 20 people from the crowd on stage and the security seemed to have given up.
Overall it was a great show and a fun drunken night out for over 35's. Pennywise are more relevant than ever, even 20 years after releasing their most famous record.
Review by: Annette Geneva
Remaining Tour Dates:
Tuesday 31 October: Nex, Newcastle – 18+ (With Pennywise)
Thursday 2 November: HQ, Adelaide – 18+ (With Pennywise)
Friday 3 November: Metropolis, Fremantle – 18+ (With Pennywise)
Tickets are available from www.tickets.destroyalllines.com
Venue: The Enmore Theatre – Sydney
Support: Beerwolf
Presented by: Destroy All Lines
Photos by: Annette Geneva – Every Day Is Saturday – Check out the full gallery HERE
Tags Beerwolf Bullet Proof AU Destroy All Lines Pennywise The Bronx

redpajama_set_name: RedPajamaCommonCrawl


Among the challenges associated with getting rid grades and mastery learning is the idea of redos.
Some folks say that students shouldn't be able to redo work as it doesn't adequately show what students know and can do and others say that students need multiple opportunities to learn.
Every person deserves a do-over in the learning process. It is a valuable chance to evaluate what was initially understood and what needs further exploration. By allowing students to work on the same task for longer after feedback is provided, we are offering an essential chance to approach the learning from a different angle.
The more time we give to the task, the better equipped the students will be when the situation arises somewhere else and they are asked to apply the initial learning in a new situation.
And that's the goal of learning, right? To get students to really understand the skills and content we teach them so that they can apply it and synthesize in different situations without our help moving forward.
Very few human beings get what they need from a learning experience the very first time they try. Depending on the experience we are providing students with, the depth of learning can vary. Tests and other "one and done" situations are never going to get the best out of students particularly because of the nature of time and memorization.
When we move to more formative tasks and learning opportunities, multiple chances for growth are built into the process. Students are naturally more collaborative and teachers are involved and watching the process. They work through problems in class over a period of time and the teacher can observe, answer questions, pose new questions and offer specific feedback at the time it is needed and not just after.
The traditional way of learning sets students up and not in a good way. We need to start considering what we want the kids to take away from school and do everything in our power to help them be successful in the pursuit of that.
First we need to make sure our tasks are higher level tasks or redos will just be chasing points. We need to de-emphasize point accumulation and focus on skill building and content mastery.
Redos shouldn't be for a higher grade, but for depth of understanding.
No two students learn at the same pace or in the same time, so we need to allot for these variables in how we teach without penalizing students who take longer or rewarding students who do it faster.
The goal is always for as many students as possible to achieve mastery of a certain skill set and content knowledge, they have a year or more to achieve that, so we must offer them multiple opportunities to practice and master as they go.
Collaboration is an excellent way of helping students become more independent and innovative as they can work together to come up with new ideas while learning other social emotional skills like listening and compromising while they work.
Formative learning experiences allow for on-going growth and readjustment that help solidify mastery. They also offer feedback opportunities.
We need to remove the justice mindset that forces us to want to penalize kids who don't comply with our rules and directions. Make sure to provide an opportunity for student input and really look at the what the students are sharing. What they come up with may be more meaningful than what we have.
Too often in education, those in charge forget what the learning is all about it. It isn't about compliance or mere task completion but a development of a skill set and depth of understanding that continues to be built upon and adjusted for mastery. We must, it is our obligation, to provide students with the richest learning experiences that we can and allow them to take away from each one what they need.


To import the AppNeta v30 into vSphere you will need an OVA template, which you can download from AppNeta at > Manage Monitoring Points > + Add Monitoring Points > Virtual Monitoring Point. Leave that page open because you'll need the name of your AppNeta instance and site key. At the end of the install AppNeta will redirect you to the next step.
Open vSphere Client, select File > Deploy OVF template, and browse for the v30 OVA you downloaded.
Click Next through the configuration options, leaving the defaults if desired. Before clicking Finish, check Power on after deployment.
Wait for the v30 deployment to complete, then access the VM inventory.
Click on the v30 in the inventory tree. Make sure the v30 is running: the play button should be depressed. Then select the v30 from the inventory tree open the console.
You might need to wait for the monitoring point to boot. Once it does, a setup wizard will launch. You are prompted to choose a name for the monitoring point. This is the name that AppNeta will use to refer to the v30, so it can be the same or different than the name you chose for the v30 during the VM configuration.
You'll use the password you choose here to log in to the v30 console via vSphere Client, manage the monitoring point via Web Admin, or SSH to the v30 via another client. The username is root and cannot be changed. Your AppNeta instance and site key are available on the Monitoring Point Setup page, which should still be open from step 1.
Select OK, and then go back to the Monitoring Point Setup page which should still be open.
The Monitoring Point Setup page should redirect to the next step in less than a minute. If it doesn't—either because your session timed out or you navigated away—its no problem. When you return, resumes the setup process where you left off. If you decide to abandon the setup, just remember to assign the v30 at least a base license, which you can do from the Manage Licenses page, and set it's location from the Manage Monitoring Points page.


text:
Hanson Professional Services Inc.
DOT & Tollway
Commissioning and Energy
Planning and Management
Construction and Project Delivery
Decision Optimization Technology
Sustainability and Resiliency
Hanson Awards
Grow Our Own
Shadow Hanson
STL Next Gen
Tennessee waterways assessment study
Client: U.S. Army Corps of Engineers, Nashville District
Location: State of Tennessee, TN Date Completed: 07/31/2008
The U.S. has one of the most extensive water transportation systems in the world, with 40 states having direct access to either a coastal deepwater port or a federally maintained, inland navigable waterway. With nearly 12,000 miles of inland waterways in the U.S., waterway transportation affects economic development and global trade.
Hanson assisted the Tennessee Department of Transportation (TDOT) and the U.S. Army Corps of Engineers (USACE) Nashville District to collect and deliver recommendations to support Tennessee ports and waterways. The project deliverable was a formal report.
"Hanson was very easy to work with." — Stuart Stein, GKY & Associates
With its central location on the inland river system, Tennessee's rivers play an integral role in the nation's freight system. Tennessee is home to three major navigable arteries – the Cumberland, Mississippi, and Tennessee Rivers; four public riverports; and more than 170 private river terminals. The state ranks 11th out of 40 for most navigable waterways in the U.S.
In order to formulate functional initiatives for TDOT, Hanson investigated the roles and responsibilities of other state departments of transportation to learn more about how those states support water transportation and ports. Data collected from each state included:
the governmental body responsible for ports and waterways,
the organizational placement of the waterways individual or department within the governmental body,
the number of navigable waterway miles,
the most recent annual waterborne freight tonnage,
the number of public port facilities, and
the extent of involvement and assistance provided by these states for their ports and waterways.
This investigation provided a comparative analysis of possible roles for Tennessee.
Hanson then toured the facilities at each of the public ports in Tennessee. Hanson's team worked with the ports to identify short- and long-term capital needs to increase port potential in facilitating access to the state's natural freight transportation system.
The project team held a series of collaborative stakeholder meetings across the state, explaining the project and its objectives and seeking stakeholder feedback on types of state-level assistance and/or programs that they desire.
During these sessions, stakeholders had the opportunity to describe and rank, in order of importance, the types of state assistance they envisioned as most beneficial. The categories included organizational structure, financial assistance, technical assistance, marketing assistance, and policy considerations.
After compiling the results, Hanson analyzed the stakeholder input in light of the team's knowledge about other programs around the country. The Hanson team worked with TDOT and the USACE to identify commonalities and arrive at practical recommendations that would be most beneficial to the waterway industry and the state.
In addition, Hanson provided information about how the waterways could affect the sale or success of the Tennessee Valley Authority Megasites and other similar economic development sites.
marketing@hanson-inc.com


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text:
Climate and temperature
Puerto Baquerizo Moreno
Floreana
Requests and Complaints
Dianna Seals
No Excuses: The Making of a Head Coach by Bob Stoops, Gene Wojciechowski
No Excuses: The Making of a Head Coach
Bob Stoops, Gene Wojciechowski
Download ebook for itouch No Excuses: The Making of a Head Coach FB2 ePub in English by Bob Stoops, Gene Wojciechowski 9780316455923
From the legendary Oklahoma coach, a candid and inspiring memoir. When Bob Stoops took over as football coach in 1999, the Oklahoma Sooners were in disarray with back-to-back losing seasons. But in just two years' time, Stoops achieved the seemingly impossible: winning a national championship and returning the struggling Sooners to their powerhouse status, churning out NFL talent, Heisman Trophy winners and conference championships, bowl wins and national title runs on a regular basis. During his 18 seasons at OU, his record was a remarkable 190-48. At only age 56, at the peak of his career, he stunned the college football world by walking away. For the first time, Bob opens up about his career alongside the evolution of the game itself. From his unlikely emergence as a star player at the University of Iowa, to his coaching apprenticeships under giants like Hayden Fry, Bill Snyder, and Steve Spurrier, Stoops recounts how the game he fell in love with as a boy has evolved into a billion-dollar business often compromised by recruiting wars, aggressive agents, overzealous boosters and alumni, and the emergence of the CEO head coach rather than mentor and teacher. Bob holds nothing back while explaining why it was time to step away from the game-and players-he still loves. Told with a rare combination of sincerity, vulnerability, and pure heart, No Excuses is both an engaging and eye-opening football memoir and an unprecedented portrait of a coach of one of the greatest legacy programs in the history of the college game.
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info@sancristobalgalapagos.gob.ec


Its hard to write about yourself I've found. It's took me two posts to attempt writing about me. But I'm doing a blog as I read so many blogs about things to try and wear, ideas for food and living and decided I needed my own outlet to put them to practice! I'm still learning... Yesterday I reposted my post to my page and I'm really not sure how to get a theme but as I keep going on I'll update this till I'm a Wordpress expert!


$1,500.00 USD Monthly Gas and Heat Included.
"Heat, Hot Water and Gas! Included"
Nicely Built 2 Bedroom Apt in Private Home.
Cozy put together very nicely.
Very Nice entry to the Living quarters.
Marble Floors in The Bathroom.
Floor to ceiling Tiles in the bathroom.
New Floors and walls throughout this home.
Heat Hot Water and GAS is Included.
Combined Income should be 60,000 or close.