It’s just about time to start one of the least favorite but most interesting times of year: The coaching carousel. As a Group of 5 conference, Mountain West head and assistant coaches get offers and leave each season for more prestigious and higher-paying new jobs. It’s just how it is in the college football landscape.

Three, maybe four teams already have coaching openings at the time of this writing (Maryland, Kansas, and Louisville. Rumors leaked on Colorado as well but nothing is official yet). By the end of the month, many more schools will have vacancies as well. This post is an attempt to get ready for coaching carousel season by looking at the likelihood each MWC will have their coach leave, either by getting an offer somewhere else or getting fired by the school. Percentages are listed but it’s not an exact number by any means. It’s more just a estimation of both their relationship and success with their current school as well as how attractive they may look to schools who will be looking for a new coach.

Note: Never say never in this game, so no 0% or 100% listings here today.

Air Force

Troy Calhoun: 99%

If Calhoun wanted to leave, he likely would’ve done it by now. He has a good thing going coaching at his alma mater and has built a program that is usually on the verge of being bowl eligible. For an academy school, that’s about as consistent as one can hope for. Maybe one day he gets an offer he can’t refuse but it would come as a huge surprise.

Boise State

Bryan Harsin: 60%

His name pops up for Power 5 jobs every single year and despite not meeting expectations, this season will be no different. One year, the magic job will open up and lure him away. It may not be this year, but it’s always looming. Think he stays at least one more year and tries to have a big year with a weaker 2019 schedule and cash in, but what do I know.

Colorado State

Mike Bobo: 66%

This year has been about as bad as could possible be for Bobo and his Rams this season. Based on this year alone, there’s no way he should return. However, tenures aren’t made on one year, good or bad. I’ve said it before and I’ll say it again here: Bobo has enough of a track record to get a mulligan for this season. Yes, you can make a joke about the 7-5 road block being his track record, but he should still get a pass for this year. That and his high buyout. But do a repeat performance next year and it’s time to move on.

Fresno State

Jeff Tedford: 35%

Obviously, this is due to the tremendous success Tedford and the program have had the past two seasons. He’s sure to have suitors this winter, as all successful Group of 5 coaches seems to have each year. Tedford does like Fresno, so it’s doubtful he will just jump at any opportunity (but someone else on this list might). However, he figures to be on the short list for most openings, so it’s likely one of those tempts he enough to start talking details. This will be an extremely interesting storyline to follow come coaching carousel season.

Hawaii

Nick Rolovich: 99%

Hawaii loves Rolo. Rolo loves Hawaii. MWCConnection loves Rolo (not relevant but accurate). He’s doing well there, but not well enough to be poached. He’s committed to the program so he won’t be fired for the foreseeable future. Along with Calhoun, he’s the most likely on this list to return.

Nevada

Jay Norvell: 90%

Norvell has had a great second season as head coach. I’d put him right on or maybe even slightly ahead of schedule with building his program. Similar to above, it’s a good marriage between Norvell and the Nevada. While he’s had a successful year, I don’t think it’s successful enough to jump to other pastures, but I could see him on a lower tier of some team’s wish list. Now in a year or two, that might be a different story. For now, enjoy this sweet spot of winning without fear of a coach leaving Wolf Pack fans.

New Mexico

Bob Davie: 5%

Davie’s days are numbered. They probably should’ve been last winter with the allegations, but he held on. A very inconsistent and disappointing season, now capped with a player suspended for fighting a teammate has occurred this year. Between on and off the field issues, there’s no reason for New Mexico to bring him back. He led them to a bowl and should get credit for some nice games/seasons. They may fall back into total obscurity without him, but it’s time to move on. It would be a shock to see him still employed by the end of the month.

San Diego State

Rocky Long: 90%

He’s the most successful coach they’ve had. Winning season after winning season. Bowl game after bowl game. Reload each year. It’s a perfect fit and given his age, it’s hard to imagine a scenario where Rocky doesn’t retire as an Aztec. The only question is when, which is the only reason 99% isn’t listed here.

San Jose State

Brent Brennan: 85%

It would be pretty surprising to see Brennan going anywhere this year. The Spartans aren’t winning for starters. And he’s too young into his tenure to be fired. This site has long said that Brennan is building a nice foundation to the program and is interested to see how things look in year 3 (and hopefully in year 4). Also, his unrelenting optimism seems to make him a good fit for this program and one would imagine the school knows this.

UNLV

Tony Sanchez: 40%

Sanchez has improved every year before now. But 2018 was supposed to be the year they leap into a bowl and they have lost some winnable games that are halting that quest. I’m a believer in new coaches getting three years to show improvement and four to show results. He checked off the three year box, but not the four year box. He probably stays but his seat will be mighty hot in 2019.

Utah State

Matt Wells: 35%

Wells has turned in a remarkable season. He has now come full circle; going from a top coaching candidate to hot seat and now back to a popular name. I think this time he takes the best offer he gets, selling high on himself and not risking another downturn. Perhaps the opening jobs don’t view him as a top candidate but I think he takes what he can get this time around.

Wyoming

Craig Bohl: 75%

Nothing against Wyoming, but it is interesting that Bohl’s name doesn’t come up more often for coaching vacancies. Maybe they are just off the radar in Laramie. But he’s brought success and consistency to a program that was in dire need of it. Though this season was an expected step back, Bohl’s time in Wyoming doesn’t seem to be coming to an end anytime soon. Perhaps he gets some offers but doubtful he is on a sideline other than the Cowboys next season.

Your turn: What did we get right and what did we get wrong? Leave a comment in the discussion below.


Sunday, August 9, 2015

The Beginning of the End

Thirteen years ago today, Casey overdosed for the third and final time. It would be the beginning of the end, the first of ten days that he lay in a coma before we had to let him go. This time would be different from the others, he wouldn't walk out this time. There would be no more chances for recovery.

It has only been in the last couple of years, while listening to a presentation for nurses and other health professionals, that I heard of just how many Kentuckians overdosed that same year and at the same hospital as Casey. The presentation included a slide of data from University Hospital of patients with Kentucky zip codes presenting with an overdose from 2000 to 2011 or 12. While the audience was focusing on the top of the chart, my eyes zeroed in on 2002, the year that Casey was one of those statistics. It was surprising to most that the number of overdoses in 2002 exceeded the number at the top by approximately 1,000.

I thought that one of those more than 5,000 overdoses in 2002 was enough, enough because that one was my son, Casey.

Since Casey's death, my thoughts have often been a series of "what ifs". Today, I can't help but think "what if", wondering whether or not we would be living the nightmare of this heroin epidemic, if people had paid attention 13 years ago! We'll never know. Tragically, most were in denial, believing that heroin would never touch their loved ones and fearing that if it were acknowledged that it would. Even without the acknowledgement and in fact, because of it, more families are in the club that no one wants to join.

Those who have the ability to be optimistic in the face of such devastation would say that we are at the 'tipping point'. On my best days, I would agree. On days when one call after another is one of desperation and hopelessness, I have my doubts.

What I do know is that while resources are still limited and a standard of care is in the early stages of development, the disease of addiction in general and heroin in particular demands attention.

It's also blatantly obvious that we are not where we were and closer to where we hope to be. Hopefully, progress will continue so that 13 years from now we will not be looking back wistfully at what might have been but rather celebrating what is.

In the meantime, perhaps, just perhaps, through our collective efforts, this will again be the beginning of the end, the end of the tragic results of this devastating epidemic and the beginning of affordable, accessible and available evidence-based care for the treatment and recovery of our loved ones.


Georgia: Firefighters Arrested and Charged in Irwin County Arson Case

Insurance and Safety Fire Commissioner John W. Oxendine said four additional arrests have been made in a serial arson case involving Irwinville volunteer firefighters, and additional charges have been filed against the four suspects already arrested.

Eight suspects have been charged in a series of arson fires dating back to last summer, Oxendine said, involving two houses, vehicles, and several woodland and grass fires.

“It’s especially tragic when an arsonist turns out to be a firefighter, someone sworn to protect the public,” Oxendine said.

Chief Rusty Thomas has been charged with two counts of first-degree arson, one count second-degree arson, two counts third-degree arson, one count false statements and one count obstruction of justice, Oxendine said.

Firefighter Eric Lee Cowart has been charged with one count first-degree arson and one count obstruction of justice and also faces probation violation charges, according to Oxendine.

Oxendine said firefighter Roy Brown Jr. has been charged with one count first-degree arson; firefighter Justin McCurdy has been charged with two counts first-degree arson; and firefighter Daniel Spires has been charged with one count first-degree arson and one count second-degree arson.

Firefighter Joe Maye has been charged with one count first-degree arson, one count third degree arson, and one count obstruction of justice, Oxendine said.

Firefighter Sandy Mobley has been charged with one count party to a crime and firefighter Kevin Burton has been charged with one count second-degree arson, according to Oxendine.

First-degree arson is a felony, with a penalty of one to 20 years in prison and/or a fine of up to $50,000.


Philipp Bagus is professor of economics at Universidad Rey Juan Carlos. He is a Fellow of the Mises Institute, an IREF scholar, and was awarded the 2011 and 2017 O.P. Alford III Prize in Libertarian Scholarship, the Ron Paul Liberty in Media Award 2003, the Templeton Fellowship Award of the Independent Institute in 2008, and the Ludwig-Erhard-Forderpreis 2016. He is the author of The Tragedy of the Euro and coauthor of Deep Freeze: Iceland's Economic Collapse. The Tragedy of the Euro has so far been translated and published in Greek, German, French, Slovak, Polish, Italian, Romanian, Finnish, Spanish, Portuguese, British English, Dutch, Brazilian Portuguese, Bulgarian, and Chinese. He is also author of In Defense of Deflation, and co-author with Andreas Marquart of Blind Robbery: How the Fed, Banks and Government Steal Our Money and of the German language book Wir schaffen das alleine - warum Kleinstaaten einfach besser sind. Visit his website at PhilippBagus.com[5].


Pump jacks are ubiquitous in Alberta – and have become just as emblematic of the oil and natural gas-focused province as the fields of wheat or canola they sit in.

But this week, the Supreme Court will tackle a case at the heart of the question of who pays to clean up wells that are no longer economically viable, or those already sitting idle in an era of low oil prices.

On Thursday, the Supreme Court will hear an appeal led by the Alberta Energy Regulator on a case focused on whether provincial regulations requiring the environmental cleanup of old wells can co-exist with a federal insolvency law that puts banks and other lending institutions first in line for getting paid when a company goes bankrupt. A 2016 Alberta Court of Queen's Bench ruling on the case of Redwater Energy Corp. allows energy companies or receivers to "disclaim" wells during insolvency proceedings. The case will have far-reaching implications for oil-and-gas companies, lenders and environmental regulators.

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Redwater is a small company that went bust in 2015 owing money to ATB Financial. The previous court rulings gave priority to the interests of secured creditors to collect rather than to the costs of cleaning up old, unproductive wells as required under provincial environmental laws.

The case has attracted a diverse company of intervenors on the side of the appellants, the Orphan Well Association, an industry-funded group that cleans up wells that do not have financially accountable owners, and the Alberta Energy Regulator (AER). They include Ontario, Saskatchewan and British Columbia – which are concerned about their own environmental regulations. Alberta farmers, Greenpeace, Ecojustice and the Canadian Association of Petroleum Producers (CAPP) also back the appellants.

CAPP says the previous rulings pose an unacceptable environmental and safety risk and it does not want solvent oil-and-gas producers that support the Orphan Well Association to be stuck with cleanup costs. Landowners are terrified old wells will be left on their farms. In Alberta, oil companies can receive leases that allow them to drill on privately owned land if they compensate the owners. Many farmers accepted it, trusting they would clean up when they were finished.

"This was never supposed to happen," said Daryl Bennett, a farmer and landowner advocate in Taber, Alta. "We agreed to let society take our land on the condition that you paid us for the inconvenience and you reclaimed it before you went away. Now, you're reneging on both of those promises, you're threatening our livelihoods, you're threatening our safety and you're threatening food safety."

ATB said in a submission to the Supreme Court that a dismissal of the appeal will safeguard the principles and integrity of Canada's bankruptcy and insolvency regime.

It also notes that Alberta's Court of Appeal said if environmental remediation costs get priority over the rights of secured creditors, a "prudent lender in the circumstances would simply walk away from its loans" and "all of the wells would truly become 'orphaned.'"

But the AER and the Orphan Well Association say the lower-court decisions dealt a severe blow to a long-standing environmental regulatory system. The AER said receivers of insolvent oil-and-gas companies can now keep profitable assets and have no responsibility for cleaning up the duds.

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"This decision has resulted in significant unintended consequences that if not rectified will result in thousands of renounced sites sitting on the landscape, interfering with the ability of innocent landowners and land users to enjoy the impacted sites," the AER's submission said.

The number of Alberta's orphan wells hit 3,714 in January, up from 705 wells in March, 2015.

Alberta requires companies to have enough assets or funds to decommission their own sites. But some environmentalists and farmers say the regulatory regime should be strengthened to prevent the further proliferation of old, unwanted wells.


Lowest temperatures in Sweden

This hit list shows the coldest weather stations in Sweden of today. As usually the lowest temperature is measured during the night, this hit list is updated every morning. It shows the minimum temperature between 20:00 and 8:00 (summer time) or 19:00 and 7:00 (winter time).


Speaking at the Marian shrine in Ireland, the pope begs for forgiveness 'for these sins and for the scandal and betrayal felt by so many others in God's family' in a speech in front of tens of thousands who came to watch him on Sunday morning


`timescale 1ns/1ns

module tb_mipi_csi_packet_decoder;
	reg clk;
	reg reset;
	reg input_valid;
	reg  [31:0]bytes_i;
	wire [31:0]bytes_o;
	wire synced;
	wire [31:0]packet_length;

wire reset_g;
GSR GSR_INST (.GSR (reset_g));
PUR PUR_INST (.PUR (reset_g));

mipi_csi_packet_decoder dec1(.clk_i(clk),
							 .data_valid_i(input_valid),
							 .data_i(bytes_i),
							 .output_valid_o(synced),
							 .data_o(bytes_o),
							 .packet_length(packet_length));

task sendbytes;
	input [31:0]bytes;
	begin
	bytes_i = bytes;
	clk = 1'b1;
	#4
	clk = 1'b0;
	#4;
	end
endtask

task sendpacket;
	reg [31:0]i;
	for ( i= 32'b0; i < 32'h980; i = i + 4)
	begin
		sendbytes(i*10000);
	end
endtask

initial begin
		clk = 1'b0;
		input_valid = 1'h0;
		#50
		reset = 1'b0;
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		input_valid = 1'h1;
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'hB8B8B8B8);
		sendbytes(32'hAB09602B);
		sendpacket();
		input_valid = 1'h0;
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);
		sendbytes(32'h00000000);

		reset = 1'b1;
end

endmodule


[ClassVersion("1.0.0.0"), FriendlyName("SqlRSSetup")]
class DSC_SqlRSSetup : OMI_BaseResource
{
    [Key, Description("Name of the _Microsoft SQL Server Reporting Service_ instance to installed. This can only be set to `'SSRS'`."), ValueMap{"SSRS"}, Values{"SSRS"}] String InstanceName;
    [Required, Description("Accept licens terms. This must be set to `'Yes'`."), ValueMap{"Yes"}, Values{"Yes"}] String IAcceptLicenseTerms;
    [Required, Description("The path to the installation media file to be used for installation, e.g an UNC path to a shared resource. Environment variables can be used in the path.")] String SourcePath;
    [Write, Description("The action to be performed. Default value is `'Install'` which performs either install or upgrade."), ValueMap{"Install","Uninstall"}, Values{"Install","Uninstall"}] String Action;
    [Write, EmbeddedInstance("MSFT_Credential"), Description("Credentials used to access the path set in the parameter **SourcePath**.")] String SourceCredential;
    [Write, Description("Suppresses any attempts to restart.")] Boolean SuppressRestart;
    [Write, Description("Sets the custom license key, e.g. `'12345-12345-12345-12345-12345'`. This parameter is mutually exclusive with the parameter **Edition**.")] String ProductKey;
    [Write, Description("Forces a restart after installation is finished. If set to `$true` then it will override the parameter **SuppressRestart**.")] Boolean ForceRestart;
    [Write, Description("Upgrades the edition of the installed product. Requires that either the **ProductKey** or the **Edition** parameter is also assigned. By default no edition upgrade is performed.")] Boolean EditionUpgrade;
    [Write, Description("Upgrades installed product version if the major product version of the source executable is higher than the currently installed major version. Requires that either the **ProductKey** or the **Edition** parameter is also assigned. Default is `$false`.")] Boolean VersionUpgrade;
    [Write, Description("Sets the custom free edition. This parameter is mutually exclusive with the parameter **ProductKey**."), ValueMap{"Development","Evaluation","ExpressAdvanced"}, Values{"Development","Evaluation","ExpressAdvanced"}] String Edition;
    [Write, Description("Specifies the setup log file location, e.g. `log.txt`. By default log files are created under `%TEMP%`.")] String LogPath;
    [Write, Description("Sets the install folder, e.g. `C:\\Program Files\\SSRS`. Default value is `C:\\Program Files\\Microsoft SQL Server Reporting Services`.")] String InstallFolder;
    [Write, Description("The timeout, in seconds, to wait for the setup process to finish. Default value is `7200` seconds (2 hours). If the setup process does not finish before this time an error will be thrown.")] UInt32 SetupProcessTimeout;
    [Read, Description("Returns the path to error dump log files.")] String ErrorDumpDirectory;
    [Read, Description("Returns the current version of the installed _Microsoft SQL Server Reporting Service_ instance.")] String CurrentVersion;
    [Read, Description("Returns the current name of the _Microsoft SQL Server Reporting Service_ instance _Windows_ service.")] String ServiceName;
};


Staff at satellite communications company Inmarsat work in front of a screen showing subscribers using their service throughout the world, at their headquarters in London March 25, 2014 (Reuters / Andrew Winning)

New satellite images show more than 100 objects in the southern Indian Ocean that could be pieces of wreckage from a Malaysian airliner that disappeared from radar on March 8 with 239 people on board, Malaysia's acting transport minister said.

Hishammuddin Hussein told a news conference on Wednesday that the
images were discovered by France-based Airbus Defence and Space
on March 23.

The findings mark the fourth set of satellite images to show
possible debris from Malaysia Airlines Flight MH370 in a remote
part of the Indian Ocean situated about 2,500 km (1,550 miles)
south west of the Australian city of Perth.

Despite international efforts to locate the Boeing 777, no
confirmed pieces of the aircraft have been identified.

A pair of Chinese vessels are searching the area for a 2-metre
object spotted earlier in the day by an aircraft, state news
agency Xinhua reported on Wednesday.

The latest lead in the mystery of the disappearing aircraft comes
one day after hundreds of friends and relatives of the passengers
of flight MH370 rallied outside the Malaysian embassy in Beijing
to protest what they call two weeks of “lies and misleading
information” from the Malaysian authorities.

Air Marshal Mark Binskin, Australia’s deputy defense chief, gave
a sobering reminder of how challenging the search will be.

“We’re not searching for a needle in a haystack – we’re still
trying to define where the haystack is.”

Meanwhile, search teams are facing definite time constraints if
they hope to retrieve the aircraft's black boxes,invaluable
sources of information to researchers in being able to say what
went wrong with the flight.

The black boxes emit a ping - a kind of homing signal to help
locate them; the battery supply is enough for 30 days after a
crash. This leaves search teams another 15 days or so to locate
them.


The Course Module

As the competition and demand for NEET is increasing year-by-year, having a good strategy on how to prepare for NEET Exam to get a seat in the top medical colleges in the country is a must. Biology is the most important subject that every medical aspirant should master and a comprehensive syllabus makes it more difficult to score high. Students are highly recommended to be thorough with NCERT since that is where most of the questions will be asked from. Almost 70-75 questions of Biology are expected directly from NCERT which is the foundation text. Practising Biology Mock Test for NEET topic wise will help students to understand the subject deeply and will increase their problem solving skills effectively. The TCYOnline NEET biology Topic Wise Tests have robust 62 tests with 996 questions to practice and perform. Every chapter of 10+2 Biology Syllabus has been covered under this course. Attempt as many tests as possible to make your chance of acing NEET that much closer. The course module covers:

Why Course Module is a must?

Every topper of NEET has his/her own story to tell. The essential part of this journey is how well candidates planned for their NEET exam preparation and utilized time effectively to achieve the goal. For competitive exams like NEET, aspirants must have a preparation strategy that allows them to concentrate on each and every concept thoroughly as well as practice ample amount of quality NEET online test series available too. Because conceptual clarity and consistent practice can enhance speed in the exam which is the requisite for scoring high. Attempting NEET mock test along with NEET practice paper is most vital for realising it. It is equally important to assess the mocks which will provide a clear understanding on strong and weak areas of students respectively. With extensive 300+ topic wise tests, robust mock tests, previous year tests, beneficial added features like Solution and Analytics, Simulated Test Interface and Study Planners, the course module for NEET is a one-stop comprehensive online learning solution for effective preparation. We always place exceptional focus on relevance and quality of tests by making it performance centric. Not only this, test series at this module are complemented by detailed Performance Analytics and Benchmarking. Study Planner help learners to have a focused and well grounded approach to succeed in exams. The choices are plenty too in terms of Monthly packs, Weekend packs, Combo Medical packs, Night Booster packs etc with extremely cost effective options for students. Enroll with us to perform and ultimately realise your dream of becoming a Doctor.


Q:

Prevent duplicate row values

I've done some digging and I can't find an effective way to prevent duplicate entries based on my needs.  I need columns 2 (proj_id) and column 4 (dept_id) never to be the same, as each dept would only work on a project once.  So, rows 1 and 4, 6 and 7, and 14 and 15 shouldn't be allowed.  I'll keep digging as well.
summary_id  proj_id     hours_id    dept_id     date_entered
1   8   3   6   9/9/2012
2   2   2   6   9/9/2012
3   1   6   19  9/9/2012
4   8   3   6   9/9/2012
5   2   5   17  9/9/2012
6   7   2   5   9/9/2012
7   7   2   5   9/9/2012
8   2   5   17  9/9/2012
9   7   4   17  10/10/2012
10  3   6   1   10/10/2012
11  5   1   15  10/10/2012
12  4   4   3   10/10/2012
13  3   5   1   10/10/2012
14  8   2   13  10/10/2012
15  8   2   13  10/10/2012

A:

Before applying unique combine key to your table, you have to remove duplicate records first then apply the following sql command:
ALTER TABLE your_table_name ADD UNIQUE (proj_id, dept_id);


# Copyright (c) 2012-2016 Seafile Ltd.
import datetime
from importlib import import_module
from warnings import warn

from django.conf import settings
from django.core.exceptions import ImproperlyConfigured

from seahub.auth.signals import user_logged_in

from constance import config

SESSION_KEY = '_auth_user_name'
BACKEND_SESSION_KEY = '_auth_user_backend_2'
REDIRECT_FIELD_NAME = 'next'

def load_backend(path):
    i = path.rfind('.')
    module, attr = path[:i], path[i+1:]
    try:
        mod = import_module(module)
    except ImportError as e:
        raise ImproperlyConfigured('Error importing authentication backend %s: "%s"' % (module, e))
    except ValueError as e:
        raise ImproperlyConfigured('Error importing authentication backends. Is AUTHENTICATION_BACKENDS a correctly defined list or tuple?')
    try:
        cls = getattr(mod, attr)
    except AttributeError:
        raise ImproperlyConfigured('Module "%s" does not define a "%s" authentication backend' % (module, attr))
    try:
        getattr(cls, 'supports_object_permissions')
    except AttributeError:
        warn("Authentication backends without a `supports_object_permissions` attribute are deprecated. Please define it in %s." % cls,
             PendingDeprecationWarning)
        cls.supports_object_permissions = False
    try:
        getattr(cls, 'supports_anonymous_user')
    except AttributeError:
        warn("Authentication backends without a `supports_anonymous_user` attribute are deprecated. Please define it in %s." % cls,
             PendingDeprecationWarning)
        cls.supports_anonymous_user = False
    return cls()

def get_backends():
    backends = []
    for backend_path in settings.AUTHENTICATION_BACKENDS:
        backends.append(load_backend(backend_path))
    return backends

def authenticate(**credentials):
    """
    If the given credentials are valid, return a User object.
    """
    for backend in get_backends():
        try:
            user = backend.authenticate(**credentials)
        except TypeError:
            # This backend doesn't accept these credentials as arguments. Try the next one.
            continue
        if user is None:
            continue
        # Annotate the user object with the path of the backend.
        user.backend = "%s.%s" % (backend.__module__, backend.__class__.__name__)
        return user

def login(request, user):
    """
    Persist a user id and a backend in the request. This way a user doesn't
    have to reauthenticate on every request.
    """
    if user is None:
        user = request.user
    # TODO: It would be nice to support different login methods, like signed cookies.
    user.last_login = datetime.datetime.now()

    if SESSION_KEY in request.session:
        if request.session[SESSION_KEY] != user.username:
            # To avoid reusing another user's session, create a new, empty
            # session if the existing session corresponds to a different
            # authenticated user.
            request.session.flush()
    else:
        request.session.cycle_key()

    request.session[SESSION_KEY] = user.username
    request.session[BACKEND_SESSION_KEY] = user.backend

    if request.session.get('remember_me', False):
        request.session.set_expiry(config.LOGIN_REMEMBER_DAYS * 24 * 60 * 60)
    if hasattr(request, 'user'):
        request.user = user
    user_logged_in.send(sender=user.__class__, request=request, user=user)

def logout(request):
    """
    Removes the authenticated user's ID from the request and flushes their
    session data.
    Also remove all passwords used to decrypt repos.
    """
    request.session.flush()
    if hasattr(request, 'user'):
        from seahub.base.accounts import User
        if isinstance(request.user, User):
            # Do not directly/indirectly import models in package root level.
            from seahub.utils import is_org_context
            if is_org_context(request):
                org_id = request.user.org.org_id
                request.user.remove_org_repo_passwds(org_id)
            else:
                request.user.remove_repo_passwds()
        from seahub.auth.models import AnonymousUser
        request.user = AnonymousUser()

def get_user(request):
    from seahub.auth.models import AnonymousUser
    try:
        username = request.session[SESSION_KEY]
        backend_path = request.session[BACKEND_SESSION_KEY]
        backend = load_backend(backend_path)
        user = backend.get_user(username) or AnonymousUser()
    except KeyError:
        user = AnonymousUser()
    return user


The Institute for Analytical Sociology (IAS)

The researchers at the Institute for Analytical Sociology (IAS) conduct cutting-edge research on important social, political, and cultural matters. The research at IAS is sociological – in its original and broadly conceived meaning. The researchers at the IAS come from several academic disciplines.

Analytical sociologists seek to arrive at deeper and firmer understandings of important social, political, and cultural processes.

Through a combination of statistical analyses of big data bases, detailed micro research, computer simulations, and computer visualizations, the researchers at IAS seek to explain why people do what they do and the societal consequences of their behavior. The agent-based simulation models are used for understanding the links between micro behavior and macro dynamics. These sorts of simulation models also make it possible to conduct various “virtual societal experiments” that would have been impossible to conduct in reality.
A considerable part of the research at IAS is concerned with individuals’ mobility in different markets - the labor market, the housing market, and the school market.

The main focus is on how these different markets intersect and influence one another. More specifically, we are concerned with the dynamic processes that lead to a concentration of individuals with certain socio-demographic characteristics in different workplaces, schools, and neighborhoods, and the consequences this has for the performance of the organizations and for the individuals themselves.
The interdisciplinary nature of IAS makes it possible for its researchers to make innovative use of methods and analytical tools developed in other disciplines than their own.

IAS was established in 2014. It is administratively linked to the Department of Management and Engineering, but it has a university-wide mission and includes researchers from a range of different disciplines. IAS is governed by a board.Peter Hedström is the Director of the Institute and Sarah Valdez and Karl Wennberg are the Deputy Directors.
You can find us in the beautiful industrial landscape by the Motala River in central Norrköping.

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New MSc Program

Master’s Programme in Computational Social Science

The MSc Programme in Computational Social Science is for students who want to use cutting edge statistical and computational methods to do social research. Learn to analyze complex data to answer questions about the rise of inequality, organizational dynamics, the evolution of culture, and more.

In recent years, there has been an explosion in the size and scope of data related to human choices, affiliations, and interests that can be culled and analyzed in new ways to address fundamental questions about society and human behavior. New computational approaches based on machine learning, agent-based modeling, natural language processing, and network science have made possible ways of analyzing these data that have been heretofore unimaginable. To this end, the Institute for Analytical Sociology (IAS) offers a two-year MSc program in Computational Social Science that is aimed at developing foundational understanding of theories in the social sciences and skills in computational methods for social science research. Our program uniquely emphasizes the methodological advances and perspectives that come from the application of computational theories and approaches to basic research in the social sciences. Our main aim is to take students with substantive interests in the social sciences and bring them up to speed on cutting edge statistical and computational methods, including social network analysis, simulation methods, distributed computing, and machine learning.


Putative role of a Streptomyces coelicolor-derived α-mannosidase in deglycosylation and antibiotic production.
SCO0948 was found to be the single open reading frame annotated to encode an α-mannosidase (AM1) in Streptomyces coelicolor M145. To characterize the protein, we overexpressed SCO0948 in Escherichia coli BL21(DE3). Recombinant AM1, with a molecular weight of 110 kDa, exhibited α-mannosidase activity toward 4-nitrophenyl-α-D-mannopyranoside with a K m of 4.61 mM, a V(max) of 101.6 mM/min, and a specific activity of 47.96 U/mg. Treatment of ovalbumin, a glycoprotein, with AM1 resulted in partial deglycosylation, as assessed by glycostaining and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The S. coelicolor deletion mutant for SCO0948 failed to produce α-mannosidase activity, confirming AM1 as the only α-mannosidase in S. coelicolor M145. Interestingly, the deletion mutant and a complementation strain produced lower levels of the antibiotics actinorhodin and undecylprodigiosin in glucose minimal media. The results indicate that AM1 as an α-mannosidase influences deglycosylation and antibiotic production in S. coelicolor M145.


By Kris Walker

British Engineering: An artistic impression of the SKYLON 'space plane' in flight. Image Credit: http://www.reactionengines.co.uk

A British company is to receive £60 million funding for a revolutionary aircraft that could not only transport passengers from the UK to Australia in four and a half hours but also has capabilities for space travel; rocketing into the stratosphere in just 15 minutes.

From runway to orbit in fifteen minutes! Image Credit: http://www.reactionengines.co.uk

Dr. Alan Bond, founder of Reaction Engines has designed the SKYLON, an unpiloted space plane that could potentially accelerate up to Mach 5.5 before “changing gear” to rocket mode which can propel the plane through the atmosphere at Mach 25.

Revolutionary SABRE Engine has two modes to allow runway take off and space travel. Image Credit: http://www.reactionengines.co.uk

SKYLON’s revolutionary SABRE Engines allow the space plane to set off from a runway and propel into space. Essentially a rocket engine, the SABRE operates in two modes, an air breathing mode, which then leads onto the typically used rocket mode for space travel.

Built for reliable, reusable space travel. Image Credit: http://www.reactionengines.co.uk

The SKYLON is made up of carbon fiber reinforced plastic. The tankage is aluminum propellant with the external shell being a fiber reinforced ceramic that is only 0.5mm thick. This corrugated, lightweight design allows for free maneuverability when under thermal expansion upon entry and re-entry to the earth’s atmosphere.

The SKYLON plane is intended to be reusable, which could well, be a major cost saving positive for space travel.

SKYLON could be configured with a specialized compartment to transport people. Image Credit: http://www.reactionengines.co.uk

The capabilities with the SKYLON space plane could be limitless. Transporting satellites, supplies to space stations and potentially personnel, could all be within reach. What SKYLON could mean for the space industry is reliable cost effective space travel, with the ability to have a spacecraft that can operate from runway to orbit and back.

Be sure to like our AZoNetwork Facebook page and tell us what you think of this technology. You can also follow us on Twitter and ask any questions to our dedicated editorial team using the comments section below.


Use this Slytherin Knit hat to make Draco Malfoy look good on Halloween. The forest green 100% acrylic hat has thin gray, horizontal stripes around the head and a Slytherin schoolhouse crest on the folded portion. The crest features the schoolhouse name and mascot, the serpent. Slip this hat on with any of the Draco Malfoy or Slytherin costumes for a signature look that says trouble all over it.


Mook on Debate: Clinton Shouldn’t Have to Spend Debate Correcting Trump's 'Lies' Mook on debate fact-checking: "Unfair" to ask Clinton to "play traffic cop."

 -- Hillary Clinton's campaign manager Robby Mook said the campaign is concerned about a "double standard" at Monday night's debate where Donald Trump "lies" and still receives a "passing grade."

"All that we’re asking is that if Donald Trump lies, that it’s pointed out," said Mook on ABC's "This Week." "It’s unfair to ask that Hillary Clinton both play traffic cop with Trump, make sure that his lies are corrected, and also to present her vision for what she wants to do for the American people."

Mook called Trump "special," explaining that in past election cycles, presidential candidates have laid out extensive plans before the debate on what they would do as president. The Clinton campaign fears that Trump's lack of details about his plans has lowered expectations for how well he answers questions from debate moderator Lester Holt.

"I think Hillary is going to have to press the point. I think she’s going to have to at times challenge him to reveal what his plans are," Mook told ABC News' George Stephanopoulos. "This is a time for him to present those plans and maybe he will, but we’ll have to see."

Watch the first presidential debate Monday at 9 p.m. ET. Full live coverage and analysis of the debate will begin on ABCNews.com/Live at 7 p.m. ET.


Q:

Element-wise multiplication with Keras

I have a RGB image of shape (256,256,3) and I have a weight mask of shape (256,256). How do I perform the element-wise multiplication between them with Keras? (all channels share the same mask)

A:

You need a Reshape so both tensors have the same number of dimensions, and a Multiply layer
mask = Reshape((256,256,1))(mask)
out = Multiply()([image,mask])

If you have variable shapes, you can use a single Lambda layer like this:
import keras.backend as K

def multiply(x):
    image,mask = x
    mask = K.expand_dims(mask, axis=-1) #could be K.stack([mask]*3, axis=-1) too
    return mask*image

out = Lambda(multiply)([image,mask])

A:

As an alternative you can do this using a Lambda layer (as in @DanielMöller's answer you need to add a third axis to the mask):
from keras import backend as K

out = Lambda(lambda x: x[0] * K.expand_dims(x[1], axis=-1))([image, mask])


package com.wangdaye.me.vm;

import com.wangdaye.me.repository.MyFollowUserViewRepository;

import javax.inject.Inject;

public class MyFollowingViewModel extends MyFollowerViewModel {

    @Inject
    public MyFollowingViewModel(MyFollowUserViewRepository repository) {
        super(repository);
    }

    @Override
    public void refresh() {
        getRepository().getFollowing(this, true);
    }

    @Override
    public void load() {
        getRepository().getFollowing(this, false);
    }
}


Q:

Why isn't this simple PHP Forloop working?

First here's the code:
<?php

$qty = $_GET['qty'];

for($i=0; $i < $qty; $i++)
{
    setcookie('animals', $_COOKIE['animals'].'(lion)', time()+3600);
}

?>

Here's what I'm trying to do:
I want to set the value of the "animals" cookie to "(lion)". The number of instances of "(lion)" that should be in the cookie is determined by the "qty" GET parameter's value. So for example if the pages url is:
http://site.com/script.php?qty=10
then the value of the cookie should be:
(lion)(lion)(lion)(lion)(lion)(lion)(lion)(lion)(lion)(lion)
but now it just sets the value once despite the setcookie function being inside the loop, why isn't it working?

A:

Due to the way that cookies work (the browser needs to send the value back to the server as a part of the page request), you can't read and update the contents of the cookie in a single page load like you're attempting to.
As such, instead of attempting to append values to the variable in the $_COOKIE array, simply use a temporary variable as such:
<?php
    $quantity = intval($_GET['qty']) ? intval($_GET['qty']) : 10;

    $tempString = '';
    for($loop=0; $loop < $quantity; $loop++) {
        $tempString .= '(lion)';
    }

    setcookie('animals', $tempString, time()+3600);
?>


Q:

Delete row if same value in all columns

I have a space-delimited large file with thousands of rows and columns. I would like to remove all lines which have the same value across all columns but the first.
Input:
CHROM   108 139 159 265 350 351
SNP1    -1  -1  -1  -1  -1  -1
SNP2    2   2   2   2   2   2
SNP3    0   0   0   -1  -1  -1
SNP4    1   1   1   1   1   1
SNP5    0   0   0   0   0   0

Desired
CHROM   108 139 159 265 350 351
SNP3    0   0   0   -1  -1  -1

There is a similar question asked for the Panda Framework  (Delete duplicate rows with the same value in all columns in pandas) and I found a somewhat partial solution that removes lines containing only zero
awk 'NR > 1{s=0; for (i=3;i<=NF;i++) s+=$i; if (s!=0)print}' input > outfile

but I want to do this for the numbers -1, 0, 1 and 2 in one go with header and 1st column as the identifier.
Any help will be highly appreciated.

A:

I believe you can do something like this:
awk '{s=$0; gsub(FS $2,FS)} (NF > 1) {print s}' file

Which outputs:
CHROM   108 139 159 265 350 351
SNP3    0   0   0   -1  -1  -1

How does this work?

{s=$0; gsub(FS $2,FS)}: This action contains 2 parts:

Store the current line in variable s
Substitute in the current line $0 all values of the second field including its starting field separator FS (FS $2) with a field separator FS. This has as a side effect the $0 is redefined and all field variables and the total number of field NF are redefined. The field separator FS is needed to avoid matching xx if $2=x

(NF > 1) {print s}: If you have more then 1 field left, print the line, it means you have various numbers.


The Mafia in the Park: A charcoal syndicate is threatening Virunga, Africa’s oldest national park

An illegal charcoal cartel is helping to finance one of the most prominent militias in central Africa and destroying parts of Africa’s oldest national park. Nursing alliances with Congolese army and police units and operating remote trafficking rings in the sanctuaries of Congo’s protected forests, the Democratic Forces for the Liberation of Rwanda (FDLR) is a kingpin in Africa’s Great Lakes region’s organized crime networks and a continuing threat to human security. For years, the group has helped sustain its activities by exploiting valuable natural resources, including minerals, ivory, fish, and marijuana. But one of the FDLR’s most successful revenue-generating businesses is the illicit charcoal trade in the Democratic Republic of Congo’s cherished Virunga National Park.

Headquartered deep in the remote southwestern sector of Virunga, the illegal charcoal trade is lucrative. Some have estimated it has an annual value of up to $35 million. The FDLR and its collaborators have developed tremendous business acumen, increasingly motivated by profit incentives and enabled by high-level state cover. As one park ranger told Enough, “Armed groups have turned Virunga into their sanctuary.”The FDLR is under sanctions by both the United States and United Nations, and its charcoal-trafficking activities constitute ongoing violations of both sanctions regimes. In the regular course of business, the FDLR also commits a range of domestic and international crimes, including forced labor and illegal taxation. Yet, impunity for charcoal trafficking crimes remains absolute for high-level perpetrators. The FDLR’s business elements are distinct from its traditional combat structure and “have become the main modus operandi for FDLR survival,” according to a 2014 U.N. study. Even the most effective efforts to address the FDLR’s military and political interests will fail if its profit incentives are left untended.

Virunga faces a number of threats, including poaching and oil exploration, but the illegal charcoal trade is uniquely damaging. As far back as 2008, a U.S. Department of State cable described it as “the most important single threat to the park’s long-term sustainability.” Since then, demand for charcoal has only grown. The illegal charcoal trade is also a serious threat to regional human security. By providing funding to the FDLR and other armed groups, including Congolese state actors, it helps sustain patterns of corruption and violence. “It’s not just FDLR,” a source who requested to remain anonymous told Enough. “It’s police, politicians, and businessmen. It’s a big mafia.”

The success of the illegal charcoal trade relies on the widespread deforestation of parts of Virunga and the perpetration of human rights abuses, including reprisal murders and sexual slavery. These acts stoke one another and accelerate cycles of insecurity, poverty, fear, and environmental destruction. As activist Jeredy Kambale Malonga told Enough of the FDLR, “They use violence directly to make the [charcoal] business work.”

Charcoal made from the park is particularly valuable—rare higher-density wood yields longer-burning, higher quality charcoal, and can sell for over 60 percent more than lower-quality charcoal. An estimated 92 percent of charcoal used in North Kivu comes from Virunga.The trees are cut and turned to cooking fuel inside or near the parks, then transported to markets in nearby communities or larger cities. While demand for Virunga’s charcoal is concentrated in Congo, the business is also regional, with smugglers transporting illegal charcoal from Virunga into both Uganda and Rwanda, where old growth forests have nearly disappeared.

The FDLR does not work alone. Some Congolese national police and military commanders are involved in the illegal charcoal trade. They draw significant revenues from profit-sharing with the FDLR, as well as their own production, trafficking, and taxation of illegal charcoal. Some state officials also provide critical protection to the FDLR’s commanders and officers in Virunga. These activities illustrate Congo’s broader violent kleptocratic regime, involving the state’s manipulation of proxy groups, valuable natural resources, force, and licit state authority in service to the accrual of personal wealth through parallel state systems. Civilians are also a critical component of the illegal charcoal trade, with the FDLR recruiting local people by force or through economic pressure to help produce, guard, transport, and sell charcoal from Virunga.

Charcoal trafficking is part of the FDLR’s broader network of criminal activity including kidnapping, minerals smuggling, and elephant poaching. While much more is needed to curb the group’s other sources of conflict financing, a number of policy responses—especially aimed at mining and poaching—are in motion. Meanwhile, the charcoal trade goes virtually unnoticed, and largely uninhibited by law enforcement or policy interventions.

Virunga’s governing body, the Congolese Institute for the Conservation of Nature (ICCN), and its park rangers have effectively protected some parts of Virunga from deforestation and armed group takeover. However, they are outmatched militarily by the FDLR in direct combat scenarios, and rangers are not currently dispatched to patrol Virunga’s southwestern sector where charcoal production is rampant. As long as the FDLR is sustained and emboldened by lucrative business operations like the charcoal trade, peacebuilding in eastern Congo will falter.

Given these dynamics, it is time for a policy shift related to counter-FDLR operations and the protection of Virunga National Park. Policymakers should view the FDLR not as a strictly military, political, or ideological threat; it is also a profit-seeking organized crime network with state and civilian collaborators. In order to counter Congo’s charcoal mafia, high-ranking FDLR commanders and their partners within the Congolese army should be targeted for sanctions and prosecuted for their roles in the illegal trade. Authorities should improve sustainable defection opportunities for low-ranking soldiers within the FDLR in Virunga, to deprive the illegal trade of essential manpower. Perhaps most importantly, given widespread dependence on charcoal as a primary source of fuel among households across the region, coercive efforts to end the charcoal trade such as military operations and targeted arrests must be accompanied by alternative fuel initiatives to prevent a sudden deficit of cooking fuel among millions of people in the region.

Some initiatives have begun to address the charcoal trade, but they are insufficient to either curb the growing regional demand for illegal charcoal or dismantle the FDLR’s deadly networks. Some Congolese community-based organizations investigate economic and environmental crimes, but face debilitating threats. Recent Congolese army operations against the FDLR have disrupted some FDLR strongholds, but they have been largely piecemeal and under-resourced. Alternative energy initiatives like microhydro power and legal charcoal plantations need more support to scale up and reach more end-users. Training for justice officials on prosecuting environmental crimes has begun, but more domestic political pressure and international investment is needed for capacity-building efforts to translate into action.

In order to help end the FDLR’s threat, restore accountability, and protect Virunga, Congolese government and military institutions, foreign governments, finance institutions, and the United Nations should take steps to halt the illegal charcoal trade. To this end, the Enough Project recommends the following:

Recommendations

Alternative Energy: Impact investors and financial institutions like the United Kingdom’s development finance institution CDC Group plc, the International Finance Corporation (IFC), the U.S. Overseas Private Investment Corporation (OPIC), and the U.S. Trade and Development Agency (USTDA) should invest in Virunga Alliance’s microhydro power projects to improve local access to clean, alternative, sustainable energy and livelihoods. The Central African Forest Initiative (CAFI) should ensure that its $200 million grant to the Congolese government to address deforestation supports microhydro power. These investors and donors should also support the rapid expansion of shorter-term, legal alternative energy initiatives starting with comprehensive market assessments and collaboration with local organizations. These alternatives include legal charcoal plantations and the use of alternative biomass briquettes and fuel-efficient cookstoves, like those led by the World Wildlife Fund (WWF) and Rwanda-based Inyenyeri. Finally, the World Bank should evaluate the potential for supporting the development of an electrical grid for the city of Goma, to distribute power from Virunga’s microhydroelectric projects to illegal charcoal’s primary end-users.

Law Enforcement: Virunga Alliance donors, the U.N. Organization Stabilization Mission in the Democratic Republic of the Congo (MONUSCO), and the U.N. Office on Drugs and Crime (UNODC) should support the improvement of intelligence gathering related to charcoal activities in Virunga. In particular, the ICCN should receive financial and logistical support to reestablish legal checkpoints on the park’s major access roads to gather data and interdict major charcoal shipments coming from southwestern Virunga. The ICCN should continue its scoping missions in southwestern Virunga and eventually dispatch ranger forces there with the support of MONUSCO troops. The U.S. Congress should pass H.R. 2494 – Eliminate, Neutralize, and Disrupt Wildlife Trafficking Act of 2016– to support the professionalization of wildlife conservation law enforcement agents to better address charcoal trafficking in Virunga. The Presidential Task Force on Combating Wildlife Trafficking should also support training by the U.S. Agency for International Development (USAID) and the U.S. State Department on charcoal trade interdiction as part of its efforts to improve upstream law enforcement related to wildlife trafficking.

Protection for defenders: MONUSCO justice and human rights units should increase protective monitoring and support to conservation activists who are targeted for defending Congo’s national parks and investigating environmental crimes, and refer cases of abuse to justice officials for investigation. The U.S. Congress should pass S.284 – Global Magnitsky Human Rights Accountability Act, which would give the United States authority to impose sanctions on anyone committing abuses against individuals seeking to expose illegal government activity. It should also pass the aforementioned anti-wildlife trafficking legislation, H.R. 2494, which would authorize technical assistance for protecting rangers and improving legal responses to attacks on forest defenders.

Domestic Criminal Accountability: U.N. and U.S. Special Envoys to the Great Lakes Region, Said Djinnit and Tom Perriello, should increase pressure on the Congolese government to establish an internationalized justice mechanism to investigate and prosecute grave international crimes. In the meantime, Congo’s military court prosecutors should pursue economic crimes including the pillage of natural resources and extortion in eastern Congo, especially those related to FDLR and Congolese army units in Virunga. They should prioritize the arrest of high-level perpetrators and seizure of their assets, and interview low-level perpetrators to gather intelligence and evidence rather than fining or imprisoning them. The United States Institute of Peace should continue its initiative providing capacity-building for jurists on the prosecution of economic crimes, emphasizing improved intelligence-gathering strategies, high-level investigations, and applying the war crime of pillage legal framework. In its consultations with justice officials in Congo, the U.S. State Department’s Office of Global Criminal Justice should emphasize the importance of investigating and prosecuting economic crimes alongside atrocity crimes.

International justice: As part of its ongoing case against the FDLR’s top military commander, Sylvestre Mudacumura, the International Criminal Court (ICC)’s Office of the Prosecutor (OTP) should investigate Mudacumura’s command and control over FDLR business operations—especially charcoal cartels—and pursue charges of natural resource pillage if sufficient evidence arises. The court should also use its Article 77 authority to pursue defendants’ assets if they are the proceeds of crimes charged, including forced labor and murder perpetrated in tandem with the exploitation of forests and mines in eastern Congo.

Military Interventions: As plans for joint Congolese army-MONUSCO operations advance, Special Envoys Djinnit and Perriello should encourage selective joint operations against FDLR strongholds in Virunga, incorporating MONUSCO’s plan to target charcoal hubs and apprehend key FDLR commanders there. MONUSCO along with the U.N. and U.S. special envoys should encourage the Congolese army to vet its commanders stationed in Virunga, and suspend and prosecute those complicit in the charcoal trade. MONUSCO bases near charcoal-trafficking hubs should monitor counter-FDLR operations for civilian reprisal risk, and shore up civilian protection units in communities vulnerable to attack.

Demobilization Efforts: As MONUSCO considers reestablishing joint counter-FDLR operations with the Congolese army, it should improve its disarmament, demobilization, repatriation, reintegration, and resettlement (DDR/RR) efforts for FDLR combatants in Virunga. It should launch a revitalized defection campaign in Virunga, and provide opportunities for repatriation, third country asylum, and sustainable livelihoods in Congo for defectors coming out of FDLR business-oriented strongholds in Virunga. Special Envoys Perriello and Djinnit should continue to encourage the governments of Rwanda and DRC to increase support for repatriation and third country asylum for FDLR defectors, with particular attention to the combatants who are part of the FDLR’s business operations in North Kivu.


Torque transmitting devices such as clutches or brakes are used throughout the automotive industry. For example, vehicle transmissions employ multiple clutches to engage and disengage the gearsets of the transmission to provide forward and reverse gear ratios.
Generally, a clutch includes a friction plate and a reaction plate. The friction plate has a layer of friction material attached to the surface that opposes the reaction plate. Conventional friction materials are (a) cellulose/Kevlar/resin based materials; (b) sintered and/or metallic friction materials; and (c) woven carbon fiber friction materials.
Attempts have been made to use woven carbon fiber as a friction material for shifting/launch clutches. Carbon fiber material is typically more durable and has higher thermal conductivity as well as permeability in comparison with cellulose-based material, which favorably affect the friction characteristics of the clutch. The carbon fiber woven friction material is attached to the core steel plate by polymer-based adhesive. The adhesive has low thermal conductivity.
U.S. Pat. No. 6,360,864 ('864) issued Mar. 26, 2002 to Ford Global Technologies Inc, of Dearborn, Mich. attempts to decrease the instant temperature of the lubrication fluid in the clutch. The '864 patent increasing the area of contact between the fluid and steel reaction plates by providing either internal channels open for the fluid to flow through the reaction plate or having reaction plate split into two halves with a spacer between in an attempt to decrease the instant lubrication fluid temperature.
While the device of the '864 patent and other prior art devices work for their intended purpose improvements are still needed. For example, it would be desirable to provide a device that reduces the temperature of the lubricating fluid and addresses clutch overloading.


he nearest to 0?  (a) 5  (b) -178  (c) -6  (d) -0.03  (e) -1
d
Which is the nearest to 98?  (a) -5  (b) -1/5  (c) 1/37  (d) 2.2  (e) -1/4  (f) 4
f
Which is the closest to 0.4?  (a) 2  (b) 0.1  (c) -0.4  (d) -5670  (e) 4/3
b
Which is the nearest to -17?  (a) -25  (b) 25  (c) 0.0401
a
Which is the nearest to 0.051?  (a) -96  (b) 14321  (c) 0.2
c
Which is the closest to 198?  (a) -2.8  (b) -8  (c) -1  (d) 1/5  (e) -4  (f) -3/10
d
What is the nearest to -3 in -2, 1127, 0.2, -0.5, 92?
-2
Which is the nearest to -11?  (a) -302  (b) -0.01  (c) -0.3  (d) -8/5  (e) 1
d
What is the closest to -8 in -13, 54, 15, 0, -2/5?
-13
What is the closest to 3/11 in 3/8, -1/160, 5, -396?
3/8
Which is the nearest to -1641/5?  (a) 3/2  (b) 0.51  (c) -0.1
c
What is the closest to -18/5 in 4/31, 1, 10, 2/3, -0.15?
-0.15
Which is the closest to 0.1?  (a) -5.943  (b) 0.3  (c) -31  (d) -3  (e) 0.1  (f) -2
e
Which is the closest to -30?  (a) -0.3  (b) -1  (c) -555633
b
What is the nearest to 47/4 in -2825, 3/4, 4/5, 5, -0.2?
5
Which is the nearest to -0.21?  (a) -0.6  (b) 4.948  (c) 4
a
What is the closest to 0.91 in 1/3, 0.1, -2/5, 6, -82/11?
1/3
What is the nearest to 194 in 1/16640, 1, 5?
5
Which is the nearest to 2686?  (a) 4/5  (b) 2/3  (c) -1  (d) -28
a
Which is the closest to -334/23?  (a) -1/2  (b) 108  (c) 2/5
a
What is the nearest to -89574 in -1/4, -4, 1/4, 0.063, -5/2?
-4
Which is the nearest to 5254?  (a) 0.2  (b) -5  (c) -0.6  (d) 0.08  (e) -3  (f) 2
f
What is the closest to 1/3 in -17, -5/104, 0, 1/29?
1/29
What is the closest to -0.46 in 0.5, 4, -38, -1.1, -1?
-1
What is the closest to -2 in -2, 2/41, -4, 0.011, 35?
-2
Which is the nearest to 0.1?  (a) -2078  (b) -5/17  (c) -1/4
c
What is the nearest to 0.1 in 0.4, -0.1, 0.5, 2/30879, 1/9?
1/9
What is the nearest to -2 in -1/2, 92056, 0.8?
-1/2
Which is the closest to 0.17?  (a) -1  (b) 0.4  (c) 132/5  (d) -18/7
b
What is the closest to 0.2 in 132/13, -0.2143, -4, 34?
-0.2143
Which is the closest to 65?  (a) 0.2  (b) 24  (c) -22  (d) 163
b
Which is the nearest to 6465?  (a) -1/3  (b) -2/7  (c) 1  (d) -0.3  (e) -5/2
c
What is the nearest to 1/3 in -51, -9.6, 81, 1.4, -4?
1.4
Which is the nearest to 0.2?  (a) 0  (b) -1  (c) -58/117  (d) -43
a
What is the closest to 1 in -5, 3/76, 1/7, -4?
1/7
Which is the nearest to 1?  (a) 3783  (b) 2  (c) 8  (d) -1
b
Which is the nearest to -2/3?  (a) 1  (b) 19/4  (c) -1/14  (d) 9
c
Which is the closest to 0?  (a) 0.051  (b) -706/7  (c) -2
a
Which is the nearest to -11?  (a) 0.5  (b) 7  (c) 857  (d) 54
a
What is the closest to -10 in 0.4, 534, 22?
0.4
Which is the nearest to 2/9?  (a) 5  (b) 3569635  (c) 2  (d) -3  (e) 1
e
Which is the closest to -0.04?  (a) -2.06  (b) 1.5  (c) 10
b
What is the nearest to -2/2601 in 3, 5, 3/64, 1/3, 0.2, -5/2?
3/64
Which is the nearest to 0.139?  (a) 2/5  (b) 4  (c) 3577  (d) 3  (e) 1/4  (f) -0.4
e
Which is the nearest to 0.5?  (a) -1/2  (b) 0.4  (c) 1.9  (d) 10/73  (e) 4  (f) 8
b
Which is the nearest to -1/7?  (a) -0.3  (b) -3  (c) -1  (d) 1.11  (e) 0.006
e
Which is the closest to 1?  (a) -25  (b) -10  (c) 1.84
c
What is the closest to 2/3 in -0.3, 1/16, 483/5, 2/15?
2/15
Which is the nearest to 0.13?  (a) -0.8124  (b) 0.3  (c) 2
b
Which is the closest to 0?  (a) 0.02  (b) 1  (c) 0.16  (d) 13  (e) 82/3  (f) 0.2
a
What is the nearest to 0.1 in -5/3, -2/3, -7/16, -5, -9, -1/7?
-1/7
Which is the closest to 2/9?  (a) 5  (b) -89073  (c) 7  (d) -5  (e) 0.2
e
Which is the closest to 0.1?  (a) -0.22  (b) 52  (c) 1592
a
Which is the closest to -4/9?  (a) 0.7  (b) -1/2  (c) -21.1
b
Which is the nearest to -537?  (a) -3  (b) 2  (c) 17094
a
What is the nearest to 44 in 0.29, 3.4, -10?
3.4
What is the nearest to 21/40 in 0.081, 0.1, 2, 1/15?
0.1
Which is the closest to -2?  (a) -23  (b) -0.5  (c) -0.73  (d) -4  (e) 0.11
c
Which is the closest to 0.374?  (a) -0.4  (b) 5  (c) -2.7  (d) -4/5  (e) 2
a
What is the nearest to 4/23 in 0.5, -1/11, 1, 12, 8?
-1/11
What is the nearest to -3 in 15.075, 0, -1, 3, -0.5?
-1
What is the closest to -3 in -1/3, -2, -2/433999, -20?
-2
Which is the closest to -0.3?  (a) -5  (b) -2/9  (c) -10/7  (d) 3.91
b
Which is the nearest to 29?  (a) -17  (b) 18  (c) -4  (d) 0.3  (e) -0.1
b
Which is the nearest to 28?  (a) -291  (b) 1/3  (c) -5  (d) 4
d
Which is the nearest to 1/3?  (a) -1  (b) 0.4  (c) -0.1  (d) 1/4  (e) -90/197
b
Which is the nearest to -1?  (a) 488  (b) 1/6  (c) -2  (d) -7  (e) -131  (f) 0.5
c
Which is the nearest to -2/7?  (a) 5  (b) 79  (c) 1194/23
a
What is the closest to 16 in -0.17, 158/23, -42?
158/23
What is the nearest to -14 in 2/221, 698, 6?
2/221
Which is the nearest to 2?  (a) 1  (b) 2/15  (c) -4  (d) -44.609  (e) 2/7
a
Which is the closest to 0.4?  (a) 1/6  (b) 18  (c) -1  (d) 0.44  (e) -5
d
What is the nearest to 0 in 5, -0.1, 521, 4/21, -0.4?
-0.1
What is the closest to 0 in -2/5, -11165, 4, -0.2, 54?
-0.2
Which is the nearest to -0.2?  (a) -40  (b) -0.1  (c) 174  (d) 9
b
Which is the nearest to -67?  (a) 0.498  (b) 1/4  (c) 0  (d) -0.5
d
What is the closest to -1 in 4/31, -14/87, -7, -2?
-14/87
What is the nearest to 3 in 0, 14510, 1/2, 1/3, 2, -5?
2
What is the closest to -431 in 2/7, 0.4, -4, 2722?
-4
What is the nearest to 0.1 in 408, 5, 0, 6581, 0.5, -4?
0
What is the closest to 0.7 in 1/6, -14, 2/7, 1/9, -3/4?
2/7
Which is the nearest to 0.1?  (a) -1003706  (b) 4  (c) -2  (d) -2/3
d
Which is the closest to -2/47?  (a) -2/13  (b) 0  (c) 0.13  (d) -2/7  (e) 0.3
b
What is the closest to 1/873 in -7461, 1/8, 4/3?
1/8
What is the closest to 88 in 0.4, 8932, -0.4?
0.4
What is the nearest to 4 in 0, 3, -738?
3
Which is the closest to 1/3?  (a) -299  (b) -498/13  (c) 0.18
c
What is the nearest to 68211 in 2, 1, 15, -2/3?
15
Which is the nearest to -69/4?  (a) -1.1  (b) 4  (c) -3  (d) -2  (e) -13
e
What is the closest to 0.119 in 1, -0.4, -0.01, -3782, -1?
-0.01
What is the nearest to 2/5 in 3, 0.75118, -5, 4, -0.5?
0.75118
What is the nearest to -2/7 in -1287381, 5, -1/2, -3?
-1/2
Which is the nearest to 2/25?  (a) 1  (b) 1491  (c) 3/4  (d) -1/5
d
Which is the nearest to 0.3?  (a) -0.16  (b) 350  (c) 0  (d) -11
c
Which is the nearest to 0.7?  (a) 14/5  (b) 1.66  (c) 7  (d) -3/4  (e) -0.8  (f) 0.06
f
Which is the nearest to -3?  (a) -8  (b) -0.7  (c) -76  (d) -2.2
d
Which is the nearest to -6863?  (a) -1/4  (b) -2427  (c) 3
b
Which is the nearest to -29?  (a) 0  (b) 16  (c) -0.07  (d) 2  (e) -0.2
e
What is the closest to -0.1 in -5, -1/8, 7, -3, -1/4, 77394?
-1/8
What is the closest to 55 in 0.3, -0.3, -1/8, 26.23, 2, -3.7?
26.23
Which is the closest to -1/3?  (a) -46  (b) -0.05  (c) -22
b
What is the nearest to 0.328 in -0.295, -17, -0.01, -2/7?
-0.01
What is the closest to 2 in 59952, -1.4, 9?
-1.4
Which is the closest to -2763.1?  (a) -3  (b) -0.3  (c) 0.07  (d) 0.4  (e) 1/9  (f) -2
a
Which is the nearest to 0.1?  (a) 415/4  (b) -2/13  (c) 2  (d) -1.2  (e) 10/21
b
Which is the nearest to -12?  (a) 0.3  (b) -166/575  (c) 5  (d) 2  (e) 0.5
b
What is the nearest to 0 in 867, 5, 0.5, 5721?
0.5
What is the closest to -1692 in 0, -3, 638, -2?
-3
What is the closest to 5 in 3, 1, -1.173083, 0.4?
3
Which is the closest to -0.1?  (a) 2  (b) -28  (c) -2/5  (d) 256030
c
What is the nearest to -3/5 in -5, 0.55, 0.4, -1/2, -2/5?
-1/2
What is the nearest to -2/9 in 2/13, 2, 0.1, 0.5, 3538.1?
0.1
Which is the closest to -11?  (a) 831/8  (b) 1/3  (c) -5  (d) -2/9  (e) -0.2
c
Which is the nearest to 11314?  (a) -1  (b) 0  (c) -6  (d) -1/4
b
Which is the closest to -2?  (a) -0.2  (b) 1/10  (c) -69  (d) -39/4  (e) 1/9
a
What is the nearest to 0.1 in -1/2, -2/13, 5.2, 0, -4.03?
0
What is the closest to -0.09 in 4, 392, 15864?
4
What is the nearest to -0.2 in -10/24843, -3, -0.05, 1/4, 4, 2/3?
-0.05
Which is the closest to 12?  (a) -7.6  (b) 4/9  (c) -9  (d) 9/2  (e) 2/15  (f) 0
d
Which is the nearest to 1/123?  (a) 5  (b) 2  (c) -5/2  (d) 1.2  (e) 4/5
e
What is the closest to -4 in -0.1, 1/8542, 2, -2?
-2
What is the closest to -29 in 0.137, 3, 34/3, 27?
0.137
What is the nearest to 1 in -1, -0.069, -15.183?
-0.069
What is the nearest to 3 in 1/18, 2/13, -64113?
2/13
What is the nearest to -0.05234 in 6, -44, -1?
-1
What is the nearest to -2 in 4, 3/5, -2/7, -0.07, 418?
-2/7
Which is the nearest to 265?  (a) 2  (b


/*
 * Copyright 2013 Samsung Information Systems America, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *        http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

// Author: Koushik Sen

(function(module){

    var SymbolicStringPredicate = require("./SymbolicStringPredicate");
    var SymbolicLinear = require("./SymbolicLinear");
    var SymbolicBool = require("./SymbolicBool");

    function FromCharCodePredicate(intParts, stringPart) {
        if (!(this instanceof FromCharCodePredicate)) {
            return new FromCharCodePredicate(intParts, stringPart);
        }

        if (intParts instanceof FromCharCodePredicate) {
            this.intParts = intParts.intParts;
            this.stringPart = intParts.stringPart;
        } else {
            this.intParts = intParts;
            this.stringPart = stringPart;
        }
    }

    FromCharCodePredicate.prototype = {
        constructor: FromCharCodePredicate,

        not: function() {
            throw new Error("Not of FromCharCodePredicate is illegal");
        },

        substitute : function(assignments) {
            var s = "";
            var i, len = this.intParts.length;
            for (i=0; i<len; i++) {
                var tmp = (this.intParts[i] instanceof SymbolicLinear)?this.intParts[i].substitute(assignments):(+this.intParts[i]);
                if (typeof tmp !== 'number') {
                    return this;
                }
                s += String.fromCharCode(tmp);
            }
            var sym = this.stringPart.getField("length").symbolic.toString();
            assignments[sym] = s.length;
//            var len1 = sym.substitute(assignments);
//            if (typeof len1 === 'number' && s.length !== len1) {
//                return SymbolicBool.false;
//            }

            return new SymbolicStringPredicate("==", s, this.stringPart);
        },

        getFormulaString : function(freeVars, mode, assignments) {
            if (mode === 'integer') {
                var i, len = this.intParts.length;
                for (i=0; i<len; i++) {
                    if (this.intParts[i] instanceof SymbolicLinear) {
                        this.intParts[i].getFreeVars(freeVars);
                    }
                }
                return "(TRUE)";
            } else {
                throw new Error("Cannot get formula for FromCharCodePredicate in string mode");
            }
        },

        toString: function() {
            return "("+this.stringPart + ") = String.fromCharCode("+this.intParts+")";
        },

        type: require('./Symbolic')
    };

    module.exports = FromCharCodePredicate;
}(module));


"Longing" "Rusted" "Seventeen" "Daybreak" "Furnace" "Nine" "Benign" "Homecoming" "One" "Freight car" "Good morning, Soldier." "Ready to comply." "I have a mission for you." "Sanction and extract." "No witnesses." "Well done Soldier." "For a man who disapproves of diplomacy, you're getting quite good at it." "I'm happy, Father." "Thank you." "Thank you." "Homecoming" "One" "One" "Freight car" "I have your breakfast." "I could smell it before I opened the door." "Side of bacon and black coffee." "Again." "I can make you something different, if you like." "This is wonderful..." "I will just put this on your..." "It's okay, I can manage!" "Suspect has broken containment!" "...he's headed down the east stairwell!" "Longing" "Rusted" "Seventeen" "Daybreak" "Furnace" "Nine" "Benign" "Homecoming" "One" "Freight car" "Soldier?" "Ready to comply." "James Barnes the suspect in the UN Vienna bombing escaped custody today." "...also missing Avenger Captain Steve Rogers... and Sam Wilson." "It hurts!" "Good work." "Get me out of here." " this is room 201..." "Bacon and black coffee again today?" "You know me so well..." "Hello?" "Your breakfast is here." "May I let myself in?"


Medical Assistant Schools & Programs in Arkansas

Have you been wondering about pursuing a career in medical assisting? If so, there are variety of programs available in Arkansas —including certificates, diplomas and degree programs.

Medical assistants, not to be confused with physician assistants, work in clinical or administrative settings or perform a variety of both. They schedule patients’ appointments, change bandages, use electronic health records (EHRs) software, and record patients’ vitals. Before we get into education information for medical assistants in Arkansas, we thought you’d be interested to learn some general education information about the state...

Arkansas General Education Information and Data[vii]

There are 27 four year institutions in Arkansas, compared to the national average of 56.

There are 24 two year institutions compared to the national average of 33.

The national average for total male fall enrollment is 171,951 and Arkansas has 68,943.

The total female fall enrollment in Arkansas is 99,409 while the national average is 228,592.

F.A.Q.'s for Medical Assistants in Arkansas

What are the medical assisting job and earning statistics from Arkansas?

There are currently 2,320 medical assistants employed in Arkansas[i]

There are 2,480 projected jobs by 2022, which is a 23% increase and approximately 90 annual job openings[ii]

The annual mean 10th percentile wage for medical assistants in Arkansas is $19,790[i]

The hourly mean 10th percentile wage is $10.23[i]

Where do medical assistants work?

Medical assistants usually work in physician's offices, hospitals, clinics, and other healthcare facilities. They perform administrative and clinical tasks that involve working with patients, doctors, and other healthcare professionals. Did you know Arkansas boasts several hospitals ranked by U.S. News and World Report? The CHI St. Vincent Infirmary is even ranked as high performing for 3 specialties, including orthopedics and urology.

Top 3 Regionally Ranked Hospitals in Arkansas:

CHI St. Vincent Infirmary

Arkansas Surgical Hospital

Washington Regional Medical Center

What salary information is available for specific metro areas of Arkansas?

The highest (90th%) and lowest (10th%) annual mean salary for medical assistants in each of these metro areas is as follows:[i]

Metro Area

Lowest 10th% Salary

Highest 90th% Salary

Fayetteville-Springdale-Rogers, AR-MO

$21,090

$39,870

Fort Smith, AR-OK

$17,920

$30,440

Hot Springs, AR

$22,190

$34,250

Jonesboro, AR

$16,550

$32,870

Little Rock-North Little Rock-Conway, AR

$19,320

$35,580

Pine Bluff, AR

$17,860

$34,600

What is the annual mean 10th percentile wage for other health related fields in Arkansas?

Medical Billing & Coding: $21,060[iii]

EMT: $18,300[iv]

Pharmacy Technician: $20,000[v]

CNA (certified nursing assistant): $16,540[vi]

How do I earn a medical assistant certification in Arkansas?

Are you passionate about pursuing a career as a medical assistant? If so, you may want to look into earning your medical assisting certification or degree, since many employers tend to prefer employees who are certified. There are a variety of medical assisting programs in Arkansas to choose from within technical or vocational schools, colleges, universities, and even community colleges. The National Commission for Certifying Agencies accredits five certifications for medical assistants.

Below are a few related fields that do require state licensure:

CAN (Certified Nurse Assistant):[viii]Requires certification via the Arkansas Department of Human Services. You must take an initial exam and then renew your certification every two years. Experience requirements for the initial certification also include 90 hours of classroom and clinical training and an Arkansas state background check.

Emergency Medical Technician:[ix] Requires certification via the Arkansas Department of Health. Requirements for initial certification include successfully passing the NREMT certification exam (CBT), successfully completing an Arkansas criminal history background check, completion of an approved National EMS Educational Standards course, and successfully passing the State Psychomotor (Skills) exam. License renewal is every two years.

Registered Dental Assistant:[x]Requires certification via the Arkansas State Board of Dental Examiners. Must complete on-the-job training through an Arkansas-licensed dentist using the Educational Packet provided by the board or must be a graduate of an American Dental Association Commission on Dental Accreditation accredited school. Completion of a nitrous oxide administration and monitoring course approved by the board and an additional course for sedation monitoring is also required.

What medical assisting professional organizations are there in Arkansas?

If you are serious about medical assisting and are a recent graduate, then becoming part of a professional medical assistant organization may open the door to great opportunities for you. In the state of Arkansas, the Arkansas Society of Medical Assistants has information about continuing education, meetings, and networking for members. By visiting their website at http://www.arsma.org, you can find out more details about this organization.

If you are thinking about pursuing a career in medical assisting in the state of Arkansas and are excited to learn more, then the list of schools below could help. Keep in mind that, although certification or a degree may not be mandatory to become a medical assistant, many employers may want to hire medical assistants who have their certification or degree.