text:
Home » Judicial Replication Ceremony Held for Viscardi Alum
Judicial Replication Ceremony Held for Viscardi Alum
Induction Reenactment for Judge Robert Pipia Held for Henry Viscardi School Student Body
March 18, 2015 – A Judicial Replication Induction Ceremony was held at Henry Viscardi School at The Viscardi Center for one of its alumnus, Robert E. Pipia, on January 20, 2015. Pipia was elected to Nassau County District Court Judge last fall and officially inducted in January. In addition to the Henry Viscardi School (HVS) student body and staff, the ceremony was attended by family, including Pipia's wife Maggie a teacher at HVS for 30 years, Viscardi Board members and alumni, and local officials including the Supervisor of the Town of Hempstead Kate Murray, North Hempstead Town Supervisor Judy Bosworth, Assemblyman Edward Ra, and Councilman Peter Zuckerman.
"We wished Dr. Viscardi could have been there to witness the ceremony himself. Rob certainly has done him proud and achieved everything he had hoped the students who attended the Henry Viscardi School would when he founded it nearly 53 years ago," said John D. Kemp, President and CEO, The Viscardi Center. Henry Viscardi School educates students with severe physical disabilities, pre-K through high school (up to age 21), who are often medically fragile.
The U.S. Marine Corp Color Guard opened the ceremony. During the ceremony, Kemp said, "It is a proud day here at The Viscardi Center and School. What an honor it is for all of us to witness this induction ceremony replication and to personally congratulate one of our own. It's a valuable educational experience for our students to see just how far an HVS graduate can go, and it's also a strong reminder of the importance to exercise our right to vote when you become of age. Remember, you can take an active role in shaping our national and local governments' leadership to ensure your personal rights are being upheld."
Kemp than spoke directly to the Henry Viscardi School students, "Think big. That's what many of us in your lives, including your parents, friends, teachers and therapists, have been telling you. Think big, because that's exactly what Judge Pipia has done since the day he entered this school, and look at all that he has accomplished. Think big. Study hard. Shoot for that lofty job. Set your sights on holding leadership positions throughout your life whether it be here or on a Board of Directors one day. Build a good, fulfilling, meaningful life. Simply, think big. And if you need a reminder… call on Judge Pipia. He is a role model and mentor for you. Tap into his knowledge. Speak to him about his experiences. Seek his guidance and advice. Because, like all of us who work alongside you every day, Judge Pipia too, wants you to think big."
Kate Murray, Supervisor of the Town of Hempstead, spoke about her experience working with Pipia. "If Rob is half as good and professional as he was at the Town of Hempstead, he will be a smashing success. I know he will represent us well, courageously and fairly."
Honorable Thomas Adams and Norman St. George reenacted the swearing in. After explaining the role of a District Court Judge, Honorable St. George gave high praise for Pipia. "Rob has done more in his first week than others do in a month."
Following the mock induction, Judge Pipia addressed the audience, noting the staff of Henry Viscardi School always encouraged him to be successful. He also had many kind words about the Center's founder. "Dr. Viscardi was similar to Dr. Martin Luther King, Jr. and a driving force in this country for the civil rights of people with disabilities. If Dr. Viscardi didn't start the road in the 20s through the 40s, and have relationships with the U.S. Presidents, and found Henry Viscardi School, I don't know if you ever get an Americans with Disabilities Act (ADA)."
"Dr. Viscardi called me monthly and I always valued his call. He always talked to me about my future and being an elected official in public office. He also spoke to me about not just being an elected official, but involvement in the government and making an impact in the community," added Pipia.
As the ceremony came to a close, Pipia had some words of encouragement for the students, "Continue the Viscardi tradition. Work harder and longer. You're more resilient than the average person. See your goals through."
About Robert Pipia: Robert E. Pipia was born in Queens, New York, and at the age of 5 was diagnosed as having a Neuromuscular Disorder. At the age of 12, his family relocated to Elmont and he began attending what is now known as Henry Viscardi School. During his high school years, Rob was very active in academics and extracurricular activities, including the National Honor Society and Student Council. In addition to receiving honors in mathematics, he was awarded various athletic school honors and in his senior year was recognized by Sports Illustrated for his athletic achievements. Rob was the salutatorian of the Class of 1982.
Following graduation, he attended the State University of New York in Albany and earned a Bachelor of Science Degree in Accounting. There, he served as President of the University Action for the Disabled (UAD). UAD developed services to aid students with physical disabilities which enabled them to complete their college education. It also educated the university and the surrounding community as to the abilities of those who were physically disabled. During this time, Rob also served as a consultant to University Administrators and as a result of his efforts, he received a citation from the Vice President of Student Affairs for "outstanding service to the disabled community."
In September of 1985, he was elected to the Central Council of the Student Association to represent 5,000 off-campus students. Rob's interest in sports continued in college. He captained the wheelchair hockey team and conducted floor hockey clinics for high school students who were disabled at the New York State Wheelchair Sports Exposition.
After an unsuccessful job search in the field of public accounting after graduation, Rob attended Hofstra Law School. While in law school, Rob continued to be involved in community programs benefiting people with disabilities and school activities, serving in multiple leadership positions. During his third year of Law School, he was selected to be a member of the Hofstra Constitutional Law Clinic, practiced as a student attorney and was involved exclusively with the Civil Rights Case CARECEN vs. City of Glen Cove, the first of its kind to be settled through ADR or alternative dispute resolution. For this work, Rob received the 1992 Clinical Law Award.
Rob passed the February 1993 Bar Exam and was admitted to the Bar in July of 1993, only after he was forced to file a federal suit against the New York State Board of Law Examiners for violations of the Americans with Disabilities Act when he was denied reasonable testing accommodations. This action brought to light the serious patterns of discrimination which the Bar Examiners had followed and sparked a federal investigation by the United States Justice Department.
Since October 1993, Rob has served as a Law Assistant for the Office of the Town Attorney in the Town of Hempstead, as Counsel to the Hempstead Town Board and Deputy Town Attorney, and until his recent election win, as Executive Assistant to Town of Hempstead Supervisor Kate Murray.


This Easter weekend there's plenty to do in the Charlotte area. From local exhibitions to live music and EDM, it's something for everyone. Queen City Nerve Editor Ryan Pitkin joined WFAE's Mark Rumsey for another edition of Weekend In Entertainment.
(11/18/05) Can you believe it? The "baby boomers" are moving into their golden years. WFAE commentator and fellow "boomer" Krissa Palmer thinks it's time her generation got some respect.
(11/18/05) Have you noticed that the holiday season is already upon us? How could you not? Peppermint mochas have returned to Starbucks! WFAE's Jaime Bedrin wanted the scoop on this year's shopping season. She caught up with the Charlotte Business Journal's retail reporter Ashley Gibson.
(11/16/05) The holiday season is typically a time when charities can expect to receive financial gifts. But this year, in the wake of multiple natural disasters, Charlotte-area non-profits are wondering if they'll meet their goals. Organizations fear they could lose out on donations if people are tapped out from giving to other causes. WFAE's Jaime Bedrin reports.
(11/15/05) Sometimes, the debate over health care in America can seem confusing or distant. But at other times, the issue becomes much more poignant and personal. Here's WFAE commentator Gerry Soud on health insurance.
(11/15/05) Can you believe it? Baby Boomers are turning heading into their golden years. WFAE commentator and Boomer Krissa Palmer says it's about time her generation got the respect it deserves.
(11/11/05) Charlotte's social service agencies did some fast work in the two months after Hurricane Katrina's victims got to the city. But the work came with a price: splitting priorities between evacuees and locals. WFAE's Simone Orendain reports.
(11/08/05) It's a good thing Charlotte Mayor Pat McCrory likes his job, because he's got a few more years in office. McCrory easily defeated Democrat challenger Craig Madans with 56 percent of the vote. This will be McCrory's sixth term in office. In other election news, voters rejected a multi-million dollar Charlotte Mecklenburg School bonds package, although they did approve one for Central Piedmont Community College.
(11/08/05) The Environmental Protection Agency wants to change the way it measures air pollution from power plants. Opponents say the agency's proposed new rule would increase air pollution by allowing fossil fuel power plants to run longer. But Republican North Carolina Congresswoman Sue Myrick says it will all help the EPA reach their clean air goals more efficiently. From WFAE's Capitol Hill bureau, Terry Gildea has more.
Yohana Solomon had to learn a different way of living when she emigrated to America 20 years ago. She took political asylum here as her home country of Ethiopia was in the middle of a war. Eventually, she landed in Atlanta. And now she brings the whole world to a Southern supper table.
Get behind-the-scenes insight and analysis about what's happening in local and statewide politics from political reporter Steve Harrison.
Get WFAE news delivered to your inbox.
Sign up for our daily or weekly news email.


text:
/* @flow */
"use strict";

const selectorParser = require("postcss-selector-parser");

module.exports = function(
  selector /*: string*/,
  result /*: Object*/,
  node /*: Object*/,
  cb /*: Function*/
) {
  try {
    selectorParser(cb).processSync(selector);
  } catch (e) {
    result.warn("Cannot parse selector", { node, stylelintType: "parseError" });
  }
};

redpajama_set_name: RedPajamaGithub


text:
package me.hulipvp.chambers.shop.structure;

import java.util.Arrays;

import org.bukkit.ChatColor;

import lombok.AllArgsConstructor;
import lombok.Getter;

@AllArgsConstructor
@Getter
public enum VillagerType {

	COMBAT(ChatColor.RED, "Combat Shop"),
	SELLER(ChatColor.RED, "Sell Shop"),
	TOOLS(ChatColor.RED, "Tools Shop"),
	ENCHANTER(ChatColor.GREEN, "Tim the Enchanter");

	private ChatColor color;
	private String name;

	public String getFormattedName() {
		return this.getColor() + this.getName();
	}

	public static VillagerType getTypeFromString(String string) {
		return Arrays.stream(VillagerType.values()).filter(villagerType -> villagerType.name().equalsIgnoreCase(string)).findFirst().orElse(null);
	}

}


text:
5 Greatest Miami Heat Players Of All Time
5 Greatest Miami Heat Players Of All Time [Flickr]
There have been some great players to play in Miami but here are the five best Heat stars.
by Shawn Lealos
November 15, 2017 at 12:11 AM November 15, 2017 at 12:11 AM
The Miami Heat have one of the most prestigious NBA franchises since the turn of the century. Since 2000, the Heat have won nine division titles, reached the NBA Finals five times and won the crown three times. Three players that played for the franchise had their numbers retired and at least one more will end up with that honor when his career comes to a close. With so much greatness in such a short period, here is a look at the five greatest players in Miami Heat history.
5. Udonis Haslem
Some fans outside of Florida might find it blasphemous that Udonis Haslem made the list of the five greatest players in Miami Heat history and Shaquille O'Neal and Chris Bosh missed out on the list altogether.
There is a reason for that. Yes, O'Neal and Bosh are better players, but when it comes to members of the Heat organization, no one was more loyal than Haslem. He played a part in all three NBA titles and is still with the team, taking a pay cut to help young talent and serve as the veteran leader on the court.
4. Tim Hardaway
As mentioned before, three members of the Miami Heat have their numbers retired. One of those players was no longer around when the Miami Heat started winning titles but was the face of the franchise for six years. The reason that Tim Hardaway is one of the five greatest players in Miami Heat history is that there wasn't a point guard in Heat history that could do what Hardaway did.
When he retired, Hardaway held four franchise records. The Heat retired his No. 10 in 2009.
3. Alonzo Mourning
If there is one player that fans can call Mr. Miami Heat, it would be Alonzo Mourning. He played in Miami from 1995 until 2002 and then again from 2005 until 2008. In those 10 seasons, Mourning led Miami to their first division title (1997) and was part of their first NBA title (2006).
Mourning was a five-time All-Star with the Heat and retired holding six franchise records, making him an easy choice as one of the five greatest players in Miami Heat history.
2. LeBron James
If this list was just about naming the best players in NBA history, LeBron James might still rank No. 2 but behind a very different star.
However, when it comes to the Heat, there is still one person more valuable to the franchise that King James. However, as one of the five greatest players in Miami Heat history, there is no discounting what LeBron meant to the Heat. When he joined the team, they made it to four consecutive NBA Finals, winning two of them (2012, 2013). However, James left the franchise after that fifth NBA Finals appearance, ensuring he remains No. 2 on this list.
1. Dwyane Wade
When it comes to the top of the list of the five greatest players in Miami Heat history, Dwyane Wade sits alone - above LeBron James and even Alonzo Mourning. Alonzo was the heart and soul of the entire franchise, but Wade was there as the star when they made it to all five NBA Finals.
He was the MVP of the NBA Finals in 2006 and was an integral part of the runs with LeBron James as well. Wade also stuck around Miami until the Heat chose to part ways. If there is one man that deserves to retire as a member of the Miami Heat and see his jersey retired and hanging high, Dwyane Wade deserves it above all others.
Shawn Lealos
Shawn Lealos is a freelance writer. Shawn received his Bachelor's degree in Journalism from the University of Oklahoma with a minor in Film Studies. He has worked as a journalist for over 20 years, first in the world of print journalism before moving to online media as the world changed.
Follow shawn on Facebook
Read more on the same topic from Shawn Lealos:
Kyrie Irving talks about his upcoming free agency Lakers have presented Pelicans with 5 trade packages for Anthony Davis The Lakers plan to make a monster offer for Anthony Davis
Blasting News recommends Rams cornerback Jalen Ramsey calls Tom Brady 'great leader', expects TB12 to 'bring it' Von Miller knows what Tom Brady is all about in the playoffs: 'He's incredible' 10-year-old cancer survivor on Tom Brady: 'He's kind of been my hero all along' Julian Edelman now roots for Tom Brady, celebrates Bucs win over Eagles as he wins bet LeBron James destroys Enes Kanter after disrespectful comments Papa John's Pizza walks back NFL protest attack, calls out neo-Nazis on Twitter

redpajama_set_name: RedPajamaCommonCrawl


[Please note: I am posting this announcement on behalf of our department.
development and implementation of the capstone Bioengineering design course.
ABET-related activities and undergraduate advising.
Engineering, Electrical Engineering, Chemical Engineering or related field.
experiments into laboratory modules appropriate to undergraduate courses.
mechanical testing, bioinstrumentation, and physiological measurements.
effectively implement them. Knowledge of OSHA Laboratory Safety Standard.
Preferred: Five years of experience in industry or medical setting.


text:
Valtteri Filppula Ready to Make the Switch to Wing Full-Time
By J.J. from Kansas@JJfromKansas Sep 23, 2011, 5:02pm CDT
Share All sharing options for: Valtteri Filppula Ready to Make the Switch to Wing Full-Time
If one key theme has come out of this offseason for the Red Wings, it has been the concern that they are a middle-heavy team that lacks the true top depth they need to overcome the shortcomings that held them to second round exits for each of the last two season. Of the players being called upon to carry more of the point-producing load for the team in the upcoming season, Valtteri Filppula is among the highest-paid.
Entering year four of a five-year deal, Filppula takes up $3 million in cap space against his real-world $3.5 million salary. In cap dollars, he is the fourth-highest compensated Red Wings forward. Unfortunately, last season he produced only the sixth-highest amount of points for forwards, being outscored by both Danny Cleary and Todd Bertuzzi who are below him on the salary pay scale. The player many expected to become a perennial 50-point producer has struggled through injury and inconsistency for the last two years and, despite solid playoff production from the 2nd or 3rd-line center, he has failed to score more than 40 points in a season.
Fortunately, last night might have been a glimpse of exactly what's needed to turn him from a solid two-way player with speed and offensive upside into a true top-six point producer. So far throughout the preseason, Filppula has moved from his usual center position to the wing in favor of playing on Henrik Zetterberg's wing. All indications (i.e. 1 goal and 2 assists so far in the Red & White Scrimmage and last night's game) are that the move is exactly what Filppula needed.
Now, RedWings.com's Bill Roose has quotes from Filppula that indicate the move may become permanent.
for Filppula, he understands that there's an opportunity this season to product more points from a forward position by playing up with Zetterberg and Franzen.
"I think we have a good line and that we should be able to play real well, and do a lot of good things out there," said Filppula, who had a goal in Thursday's 4-3 shootout win over Philadelphia. "So hopefully, as the preseason goes on and into the season, we can be a good line for us."
Used greatly as a third line center in the past, Filppula sees great potential in playing with Zetterberg, who has averaged 29 goals a season, and Franzen, who is known for scoring goals in bunches.
"Playing with those guys, I expect a lot of myself if I get to play there," Filppula said. "I definitely should have a lot of opportunities to get to play a lot. And when you play more you expect more of yourself, too. If that's going to be our line, I'd hope that I would do well."
While Filppula stops short of sharing any specific goals he's setting for points totals, he does indicate that he expects to do better this season.
The good news as far as what this does for the Wings is that it allows them to better utilize players' strengths across the top three lines and alleviates a bit of the bottleneck that Detroit suffers as far as skilled centers (technically, the line of Filppula-Zetterberg-Franzen consists of three people who can all play the position at a high level).
Filppula playing on Zetterberg's wing gives him the freedom to utilize his speed to attack overzealous defensemen in the Red Wings' zone, to help stretch out the transition game, and to use his vision to set up two incredibly competent finishers in the offensive zone. While this does take away a measure of his overall defensive responsibility, his freedom to move around the zone and to sneak into passing lanes (both offensively and defensively) all while having Henrik Zetterberg to help cover him should make that line a nightmare to play against for the opposition.
What's better is that the split between the Red and White squads further indicates that this is the line which will benefit from playing in front of the Nicklas Lidstrom-Ian White pairing. When considering this as a five-man unit, they should do an incredible job moving the puck and driving the play.
Lest we worry about this move putting all of the Wings' eggs in one basket, we still have Pavel Datsyuk to consider. Datsyuk has been like this for years, but last season was perhaps the most strongly indicative season of his career at just how much better he can make his linemates. When paired with a healthy Danny Cleary, who put up a career-high in goals last season, this line has space to play with any one of three or more additional wingers who have yet-unrealized offensive opportunities: Jiri Hudler, Todd Bertuzzi, or Patrick Eaves.
If preseason talent splits remain as they did, this will give Datsyuk, Cleary, and their lucky mystery winger the ability to play a majority of their shifts in front of Brad Stuart and Niklas Kronwall. I actually don't think this five-man unit is as solidly-constructed as team White's top group, but I'd still feel confident pitting them against the top competition of any team in the league.
What's even more promising about this change is that it opens up the role of the third line center firmly for the grasp of Darren Helm. When placed between Abdelkader and Bertuzzi, this will give the Wings a third line with speed, tenacity, and the size to play as a proper checking line (not to mention two players with above-average puck-handling and one wild card who shoots from all over the ice to create good rebounds). Playing in front of Ericsson-Kindl/Commodore, this combination of players will have the ability to wear down opposing teams and a good amount of counter-attacking capabilities.
Filppula's move to winger on Henrik Zetterberg's line allows him to best-utilize his skill set as a speedy two-way forward with excellent defensive instincts, great on-ice awareness and deft passing. It gives the Red Wings the ability to ice two lines which can compete against other teams' top lines consistently and makes room on the third line for a young centerman to take on the responsibilities for which he's ready.
I can't wait for this season to start.


text:
set -e

REPO_ROOT="$(dirname "$0")"/..
(
    cd "$REPO_ROOT"
    version=$(grep -oP "PROJECT_VERSION \"?\K[0-9.]+(?=\")"? CMakeLists.txt)
    commithash=$(git rev-parse --short=8 HEAD)
    commitdate=$(git show --format=%ci HEAD | head -n 1 | cut - -b1-10 | sed -e 's/-0?/./' | sed -e 's/-0?/./')

    # file exists and has zero size -> not a prerelease
    if [ -e prerelease.txt -a ! -s prerelease.txt ]
    then
        versionstring="$version"
    else
        versionstring="$version-nightly-$commitdate-$commithash"
    fi

    TEMPDIR=$(mktemp -d)
    SOLDIR="$TEMPDIR/solidity_$versionstring/"
    mkdir "$SOLDIR"
    # Store the current source
    git checkout-index -a --prefix="$SOLDIR"
    git submodule foreach 'git checkout-index -a --prefix="'"$SOLDIR"'/$path/"'
    # Store the commit hash
    echo "$commithash" > "$SOLDIR/commit_hash.txt"
    # Add dependencies
    mkdir -p "$SOLDIR/deps/downloads/" 2>/dev/null || true
    wget -O "$SOLDIR/deps/downloads/jsoncpp-1.7.7.tar.gz" https://github.com/open-source-parsers/jsoncpp/archive/1.7.7.tar.gz
    mkdir -p "$REPO_ROOT/upload"
    tar czf "$REPO_ROOT/upload/solidity_$versionstring.tar.gz" -C "$TEMPDIR" "solidity_$versionstring"
    rm -r "$TEMPDIR"
)


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text:
Plagithmysus geranii är en skalbaggsart som först beskrevs av Perkins 1931.  Plagithmysus geranii ingår i släktet Plagithmysus och familjen långhorningar. Inga underarter finns listade i Catalogue of Life.

Källor

Långhorningar
geranii

redpajama_set_name: RedPajamaWikipedia


text:
Red Bull Stratos: Mission Accomplished
Austria's Felix Baumgartner earned his place in the history books on Sunday after overcoming concerns with the power for his visor heater that impaired his vision and nearly jeopardized the mission. Baumgartner reached an estimated speed of 1,342.8 km/h (Mach 1.24) jumping from the stratosphere, which when certified will make him the first man to break the speed of sound in freefall and set several other records* while delivering valuable data for future space exploration.
After flying to an altitude of 39,045 meters (128,100 feet) in a helium-filled balloon, Felix Baumgartner completed Sunday morning a record breaking jump for the ages from the edge of space, exactly 65 years after Chuck Yeager first broke the sound barrier flying in an experimental rocket-powered airplane. The 43-year-old Austrian skydiving expert also broke two other world records (highest freefall, highest manned balloon flight), leaving the one for the longest freefall to project mentor Col. Joe Kittinger.
Baumgartner landed safely with his parachute in the desert of New Mexico after jumping out of his space capsule at 39,045 meters and plunging back towards earth, hitting a maximum of speed of 1,342.8 km/h through the near vacuum of the stratosphere before being slowed by the atmosphere later during his 4:20 minute long freefall. Countless millions of people around the world watched his ascent and jump live on television broadcasts and live stream on the Internet. At one point during his freefall Baumgartner appeared to spin rapidly, but he quickly re-gained control and moments later opened his parachute as members of the ground crew cheered and viewers around the world heaved a sigh of relief.
"It was an incredible up and down today, just like it's been with the whole project," a relieved Baumgartner said. "First we got off with a beautiful launch and then we had a bit of drama with a power supply issue to my visor. The exit was perfect but then I started spinning slowly. I thought I'd just spin a few times and that would be that, but then I started to speed up. It was really brutal at times. I thought for a few seconds that I'd lose consciousness. I didn't feel a sonic boom because I was so busy just trying to stabilize myself. We'll have to wait and see if we really broke the sound barrier. It was really a lot harder than I thought it was going to be."
Baumgartner and his team spent five years training and preparing for the mission that is designed to improve our scientific understanding of how the body copes with the extreme conditions at the edge of space.
Baumgartner had endured several weather-related delays before finally lifting off under bright blue skies and calm winds on Sunday morning. The Red Bull Stratos crew watching from Mission Control broke out into spontaneous applause when the balloon lifted off.
Red Bull Stratos: Felix B...tner in a Flying HD OBVan
Red Bull Stratos
Airborne Images
Flightline Films
Felix Baumgartner's Mission as captured by GoPro


I usually don't like to put up a post that simply references someone else's content. As an architect I like to think of myself as someone who creates content. However, this map on Forbes is so amazingly cool that I had to pass it along. Go to the map, click on any county in the United States and you can see the immigration and emigration from that county. Most importantly you can view where folks are coming from and going to.


text:
EnSegs
Helping you Produce and Conserve Energy.
How to Conserve Energy
Conserve Energy @ Home
Conserve Energy @ Work
Tools for Measuring CO2
Invest In Renewal Energy
What Are Carbon Offsets?
Energy Segments
Solar Photovoltaic (PV)
Introduction To Solar PV
Will It Work Here?
Produce My Own Energy
EnSegs Newsletter
What EnSegs Offers
What Are Energy Segments?
The Project Sponsor
The Energy Segment Owner
Invest Today!
Why Join EnSegs
The Hiring Process
1) Introduction to Solar PV
What is a solar photovoltaic (PV) system?
Why Install Solar PV?
Solar energy potential in Canada, really?
Is PV electricity expensive?
How does a Solar PV system Work?
How much electricity will a PV system produce?
Grid tied systems vs. off grid systems.
Solar PV systems come in many different sizes and types. A system could be as simple as a single PV module connected to a water pump, designed to pump water when the sun is shining. The most common PV systems found are called grid connected systems and they usually contain many PV modules, racking, an inverter(s), and a bidirectional meter.
The smallest component of a solar PV system is called the solar cell. Many cells, usually 60 or more, are wired together to produce a single PV module or solar panel. The two terms, modules and panels, are often used to describe the same thing a single PV module; however, using the term module is more accurate and is less likely to cause confusion. Technically a number of modules wired together is called a panel. Finally, when several panels are wired together they form an array.
PV modules are sold in a range of sizes (e.g. 60 or 72 cell ) and power outputs (e.g. 270 watts). The materials, the processes, and the technology used affect the cost and efficiency of the modules. An interesting fact for those of us living in colder regions is that the voltage and the efficiency of a modules increases with colder temperatures.
Most modules produce DC electricity, a car battery also provides DC power. When connected to the electrical grid in the city this electricity is converted to alternating current (AC) electricity by the inverter so that it can be used in your home or business. AC electricity is the energy required by most electrical devices.
Batteries can be included in grid tied systems to provide backup power, but they are mostly used in off-grid systems. Batteries are nice to have, but they add cost to a system and they may require maintenance. In grid tied systems there are inverters available that have the ability to provide backup power, but they only provide power when the sun is shining.
Solar PV systems produce the most energy on sunny, summer days where there is little cloud cover and the sun is high in the sky. The greatest production happens when the sun is perpendicular to the surface of the modules. This point in time will depend on the angle that the modules were installed at, often the angle of the roof, and the time of day and the time of year.
For questions or comments on the "What is a solar photovoltaic (PV) system?" section please send us an email to:CustomerService@ensegs.com.
Copyright © 2019 EnSegs Inc. | Helping You Produce and Conserve Energy


text:
import ListPage from './ListTemplate';
import EditPage from './EditTemplate';
import DetailPage from './DetailTemplate';
import RichDetailPage from './RichDetailTemplate';

export { ListPage, EditPage, DetailPage, RichDetailPage };


Ulticon Supports Indigenous People in Mindanao Via Charity Golf Tournament Sponsorship - Ulticon Builders, Inc. Ulticon Builders, Inc.
Carlos "Charlie" Gonzalez of Ulticon Builders Incorporated based in Davao City, Philippines has always made it his mission to support the local organizations to help uplift the lives of its members and their respective families. Amongst the organizations that Ulticon Builders Incorporated supports is the MBFEA or the Mindanao Banana Farmers and Exporters Association, Inc. This association was founded in 2005 and the Board of Directors and members of the association primarily intends to uplift the plight of the small Filipino Cavendish Banana growers through the organization. The organization aims for the betterment of the banana industry.
Since their overall mission is in line with the principles of UBI, the company sought to help them in their projects. One of their projects was the MBFEA OPEN GOLF TOURNAMENT which was held on November 24, 2018. The tournament was intended to be a charity event with which part of the proceeds will be for the IP school children of Sitio Talos, Brgy. San Jose, Sto. Tomas, Davao del Norte. The tournament was held at the Apo Gold & Country Club, Inc. in Bago, Davao City, Philippines.
Ulticon Builders Incorporated sought to give aid by being a Platinum Sponsor for the said event. Why do you think they are so passionate to support these local associations? It's because they want to put a halt to the old adage, "the rich get richer and the poor get poorer". For Mr. Carlos "Charlie" Gonzalez of Ulticon Builders Incorporated, to ensure we don't delay progress for everyone's good and so we can put a stop to this vicious cycle, the key is uplifting those who are trying to make better lives for themselves and their families.
An avenue for this is to provide education and to help our young ones realize that they have the power to change the status quo, to dream and to rise up above every challenge that comes their way. However, this self-motivation can better be accomplished by more than just talk. That is why, Ulticon Builders Incorporated also sought to give them a helping hand to reach this dream. We should support our youth and support all the endeavors of all the communities that share our vision. Why? Because that's what makes us Filipinos.


text:
tinydb-git
==========

A storage backend for tinydb that stores database changes inside a git
branch.

``tinydb-git`` lets you use any branch in a git repository as a backend for
tinydb_.

.. code-block:: sh

    hiro@wintermute:tmp$ git init example
    Initialized empty Git repository in /tmp/example/.git/

Every modification of the database results in a new commit:

.. code-block:: pycon

    >>> import tinydb
    >>> from tinydb_git.json import JSONGitStorage
    >>> db = tinydb.TinyDB('example', storage=JSONGitStorage)
    >>> db.insert({'text': 'first record'})
    1

.. code-block:: sh

    hiro@wintermute:example$ git log
    commit de9a07844783b8e420fce6f9568e126dd7779e74

        Updated by tinydb-git 0.1.dev1

    commit 3b31825cf312cb5d42f792998faddf20b634c7d9

        Updated by tinydb-git 0.1.dev1

Multiple ``insert()`` calls result in a commit for each call. This can be
avoided by using a tinyrecord_ transaction:

.. code-block:: pycon

    >>> from tinyrecord import transaction
    >>> with transaction(db.table('_default')) as t:
    ...         t.insert({'b': 2})
    ...         t.insert({'c': 3})
    ...         t.insert({'d': 4})
    ...
    >>>

The result:

.. code-block:: sh

    hiro@wintermute:example$ git log
    commit e02a3af06d7cd7eeb6990277777cc24d384249e8

        Updated by tinydb-git 0.1.dev1

    commit de9a07844783b8e420fce6f9568e126dd7779e74

        Updated by tinydb-git 0.1.dev1

    commit 3b31825cf312cb5d42f792998faddf20b634c7d9

        Updated by tinydb-git 0.1.dev1

Internally, data gets stored as json, with ``sort_keys=True`` and ``indent=2``,
to make diffs pleasant to read and help with compression:

.. code-block:: sh

    hiro@wintermute:example$ git diff master^ master
    diff --git a/tinydb.json b/tinydb.json
    index a27ff44..d9711f0 100644
    --- a/tinydb.json
    +++ b/tinydb.json
    @@ -2,6 +2,15 @@
       "_default": {
         "1": {
           "text": "first record"
    +    },
    +    "2": {
    +      "b": 2
    +    },
    +    "3": {
    +      "c": 3
    +    },
    +    "4": {
    +      "d": 4
         }
       }
     }
    \ No newline at end of file

.. _tinydb: http://tinydb.readthedocs.org/
.. _tinyrecord: https://github.com/eugene-eeo/tinyrecord


text:
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At Vivekanandha College of Technology for Women, we always believe in equipping our students with the right talent and personality to face the industry requirements. Our focus on placement centers on creating new approaches to attract the best from the industry to our campus. The Placement & Training Cell functions with the primary aim of placing students in top-notch companies even before the course completion and further provides ample opportunities to the students to develop their personality by conducting programs regularly in communication and soft skills with the view of making students Industry-friendly and Industry ready candidates. The Cell is well equipped with ample infrastructure in terms of Seminar Halls, Meeting/Consultancy Hall for Pre Placement Talk, Presentations, etc. An exclusive cell under the guidance of our principal collects the data of the graduating students and maintains a comprehensive database ready for reference of interview committees. The placement cell operates round the year to facilitate contacts between companies and graduates.
It plays a very important and key role in counselling and guiding the students of the college for their successful career placement.


text:
2Format
3Races
3.1Current races (2023)
3.2Former races
4Champions
Auto racing championship held worldwide
Not to be confused with FIM Endurance World Championship, World Enduro Championship, or World Sportscar Championship.
Endurance racing
Inaugural season
Prototype Classes
Hypercar, LMP2
GT Classes
LMGTE Am
Tyre suppliers
Michelin, Goodyear
Drivers' champion
Hypercar:
Ryō Hirakawa
LMP2:
LMP2 Pro/Am:
Alessio Rovera
François Perrodo
Nicklas Nielsen
LMGTE World Endurance:
James Calado
Alessandro Pier Guidi
LMGTE Am:
Ben Keating
Marco Sørensen
Makes' champion
Hypercar: Toyota Gazoo Racing
LMGTE: Ferrari
Teams' champion
LMP2: Jota
LMP2 Pro/Am: AF Corse
LMGTE Am: TF Sport
fiawec.com
The FIA World Endurance Championship is an auto racing world championship organized by the Automobile Club de l'Ouest (ACO) and sanctioned by the Fédération Internationale de l'Automobile (FIA). The series supersedes the ACO's former Intercontinental Le Mans Cup which began in 2010 and is the first endurance series of world championship status since the demise of the World Sportscar Championship at the end of 1992. The World Endurance Championship name was previously used by the FIA from 1981 to 1985.
The series features multiple classes of cars competing in endurance races, with sports prototypes competing in the Hypercar (LMH) and LMP2 categories, and production-based grand tourers competing in the LM GTE Pro and Am categories. World champion titles are awarded to the top-scoring drivers and manufacturers over the season,[1][2] while other cups and trophies will be awarded for drivers and private teams.[3]
The World Endurance Championship was first run in 2012 as a replacement for the Intercontinental Le Mans Cup,[4] following much of the same format and featuring eight endurance races across the world, including the 24 Hours of Le Mans.[2] There were four categories: LMP1 and LMP2 prototypes along with GTE grand tourers, divided into GTE Pro for teams with professional driver line-ups, and GTE Am for teams featuring a mixture of amateur drivers.
Faced with declining manufacturer interest in the LMP1 class after the 2017 season, the FIA commissioned a study into the future regulations of the championship's top category. Known as the Le Mans Hypercar (LMH), the proposal called for a move away from Le Mans Prototype entries and less reliance on hybrid technologies. The proposal was designed to make the championship more appealing to car manufacturers, and cited flagship models such as the Aston Martin Vulcan and McLaren Senna GTR as examples of the cars the new regulations were hoping to attract.[5][6] The Hypercar class first appeared in the 2021 season, with LMH entries from Alpine, Glickenhaus and Toyota.[7] From 2023, LMDh entries will also be able to compete full-time in the Hypercar class alongside LMH.[8]
In 2021, the ACO announced that the series would move away from its two LMGTE categories, following a rapid decline in manufacturer interest. The 2022 season will be the last for the LMGTE Pro class, and from 2024, LMGTE Am will be replaced by a GT3-based category, described as a "GT3 Premium" featuring a cost-capped body kit conversion from standard GT3 machinery.[9][10] According to the president of the FIA Endurance Commission Richard Mille, the FIA are aiming at a customer-focused category where the manufacturers cannot enter officially.[11]
Format[edit]
Ten titles are awarded each season based on total point tally, with four being deemed world championships: Hypercar World Endurance Drivers' Championship, GT World Endurance Drivers' Championship, Hypercar World Endurance (Manufacturers') Championship and GT World Endurance Manufacturer's Championship.[12] The points system is similar to that used in the FIA's other world championships, awarding points to the top ten finishers on a sliding point margin scale from first to tenth. Cars finishing the race but classified eleventh or further are awarded a half point. For 8 and 10-hour races, points are worth roughly 1.5x as much (i.e. 25 points for a win is worth 38 points at these races). For the 24 Hours of Le Mans, points are worth roughly 2x as much.[13]
Races[edit]
Current races (2023)[edit]
1000 Miles of Sebring Sebring International Raceway 2019, 2022-Present
6 Heures de Spa-Francorchamps Circuit de Spa-Francorchamps 2012–present
24 Hours of Le Mans Circuit de la Sarthe 2012–present
6 Hours of Monza Autodromo Nazionale di Monza 2021–present
6 Hours of Fuji Fuji Speedway 2012–2019, 2022-present
8 Hours of Bahrain Bahrain International Circuit 2012–2017, 2019–present
(2 races in 2021)
6 Hours of Portimão Algarve International Circuit 2023-
Former races[edit]
4 Hours of Shanghai Shanghai International Circuit 2012–2019
4 Hours of Silverstone Silverstone Circuit 2012–2019
6 Hours of Nürburgring Nürburgring 2015–2017
6 Hours of Mexico Autodromo Hermanos Rodriguez 2016–2017
6 Hours of São Paulo Autódromo José Carlos Pace 2012–2014
8 Hours of Portimão Algarve International Circuit 2021
12 Hours of Sebring Sebring International Raceway 2012
Lone Star Le Mans Circuit of the Americas 2013–2017, 2020
Champions[edit]
Main article: List of FIA World Endurance champions
IMSA SportsCar Championship
European Le Mans Series
Asian Le Mans Series
^ "2012 FIA World Endurance Championship". fia.com. Fédération Internationale de l'Automobile. 2011-06-03. Archived from the original on 2011-06-06. Retrieved 2011-06-04.
^ a b "World Motor Sport Council". fia.com. Fédération Internationale de l'Automobile. 2011-06-03. Archived from the original on 2011-06-06. Retrieved 2011-06-04.
^ "The FIA World Endurance Championship is unveiled!". lemans.org. Automobile Club de l'Ouest. 2011-06-09. Archived from the original on 2011-06-16. Retrieved 2011-06-09.
^ "FIA announces World Endurance Championship". Planetlemans.com. Archived from the original on 18 October 2011. Retrieved 12 November 2011.
^ "FIA gives green light to WEC's 'hypercar' LMP1 prototype successor". autosport.com. Archived from the original on 23 August 2021. Retrieved 11 June 2018.
^ "FIA announces 'hypercar' rules for 2020/21 WEC season". speedcafe.com. Archived from the original on 23 August 2021. Retrieved 11 June 2018.
^ "The 2021 WEC season entry list in full". www.motorsport.com. Archived from the original on 2021-04-11. Retrieved 2021-08-17.
^ "Classes - FIA World Endurance Championship". www.fiawec.com. Retrieved 2021-08-24.
^ "GT3 cars to replace GTE class at Le Mans from 2024". www.motorsport.com. Archived from the original on 2021-08-23. Retrieved 2021-08-20.
^ "WEC drops GTE Pro class for 2023". www.autosport.com. Retrieved 2022-08-10.
^ Lloyd, Daniel. "ACO's Future GT Class Set to Prohibit Factory Entries – Sportscar365". sportscar365.com. Retrieved 2021-08-26.
^ "Trophies & cups - FIA World Endurance Championship". www.fiawec.com. Archived from the original on 2021-08-14. Retrieved 2021-08-17.
^ "Points - FIA World Endurance Championship". www.fiawec.com. Archived from the original on 2021-08-19. Retrieved 2021-08-17.
Wikimedia Commons has media related to FIA World Endurance Championship.
FIA World Endurance Championship (in English and French)
Automobile Club de l'Ouest
Fédération Internationale de l'Automobile
Intercontinental Le Mans Cup
World Sportscar Championship
FIA World Endurance Championship rounds
BHR1
FIA World Endurance Championship circuits (2012–present)
Current (2023)
Sakhir
Future (2024)
FIA World Endurance Championship champions
World Endurance Drivers' Championship
Benoît Tréluyer
Marcel Fässler
Allan McNish
Tom Kristensen
Loïc Duval
Anthony Davidson
Timo Bernhard
Marc Lieb
Romain Dumas
Neel Jani
Earl Bamber
Mike Conway
José María López
World Endurance GT Drivers' Championship
Gianmaria Bruni
Toni Vilander
Richard Lietz
Nicki Thiim
Michael Christensen
Kévin Estre
FIA World Motor Sport Council
FIA Hall of Fame
Commission Internationale de Karting
FIA Institute Young Driver Excellence Academy
FIA Contract Recognition Board
FIA Foundation for the Automobile and Society
International Sporting Code
FIA World Championships
World Endurance Championship
WRC2
Junior WRC
World Rallycross Championship
World Rally-Raid Championship
World Cup for Cross-Country Bajas
World Karting Championship
FIA European Championships
Masters Historic Formula One Championship
European Rally Championship
European Rallycross Championship
European Autocross Championship
European Hill Climb Championship
European Truck Racing Championship
European Drag Racing Championship
European Cup for Cross-Country Bajas
European Karting Championship
Étienne van Zuylen van Nyevelt (1904–1931)
Robert de Vogüé (1931–1936)
Jehan de Rohan-Chabot (1936–1958)
Hadelin de Liedekerke Beaufort (1958–1963)
Filippo Caracciolo di Castagneto (1963–1965)
Wilfred Andrews (1965–1971)
Amaury de Merode (1971–1975)
Paul Alfons von Metternich-Winneburg (1975–1985)
Jean-Marie Balestre (1985–1993)
Max Mosley (1993–2009)
Jean Todt (2009–2021)
Mohammed bin Sulayem (2021–present)
FIA Drivers' Categorisation
List of FIA events
List of FIA member organisations
FIA Super Licence
FIA Global Pathway
FIA Heritage Certificate
FIA Historic Technical Passport
Current championships
Le Mans Cup
Former championships
European Le Mans Series (2001)
Japan Le Mans Challenge
Major races
24 Hours of Le Mans
1000 km Silverstone
1000 km Spa
1000 km Nürburgring
1000 km Fuji
Car classes
Le Mans Prototype (list)
Le Mans Prototype Challenge
LMGT classes
List of world sports championships
Rugby 7s
Aquatic sports
Bobsleigh and skeleton
Boxing (amateur)
Dance Sport
Equestrianism
rhythmic
artificial track
natural track
Olympic Class Combined Worlds
Real tennis
Paralympic sports
Blind football
Para ice hockey
Wheelchair handball
Mixed team
beach wrestling
Carom billiards
Three-cushion
Five-pins
blackball
chinese eight ball
eight-ball
men nine-ball
women nine-ball
team nine-ball
ten-ball
straight pool
six-red
Mind sports
draughts-64
draughts-64 women
Rallying
Sports Car Endurance
Motorcycle sports
SuperEnduro
team endurance
Snowcross
team long track
indoor nations
Aeroplane sport
Aerobatic GP
F4s
Radio-controlled racing
1:10 electric off-road
1:8 nitro off-road
Tank biathlon
Air racing
Sports Car Sprint
Ball hockey
ODI (men)
ODI (women)
T20 (men)
T20 (women)
Canoe polo
Formation Latin
biathle
triathle
laser run
Rogaining
Roll Ball
Sepaktakraw
Armwrestling
mountain running
long distance mountain running
Tenpin
Ninepin (singles, team)
wildwater
canoe sailing
waveski
Crokinole
women association croquet
men golf croquet
team association croquet
women golf croquet
team golf croquet
mountain bike marathon
artistic skating
inline alpine
inline downhill
inline speed skating
roller freestyle
practical handgun
practical rifle
practical shotgun
telemarking
SUP/paddleboard
long distance duathlon
cross duathlon
eSailing
NES Tetris
Pro Evolution Soccer
See also: World cups
Retrieved from "https://en.wikipedia.org/w/index.php?title=FIA_World_Endurance_Championship&oldid=1133368166"
Endurance motor racing
Recurring sporting events established in 2012
Sports car racing series
World auto racing series
Articles with French-language sources (fr)


and find homework help for other A Christmas Carol questions at eNotes. Thus, we begin to see that one of the text's main messages is to help us to learn the. The moral of A Christmas Carol has everything to do with the transformation of the main character, Ebenezer Scrooge. He begins the story as a miserly, closed-hearted man. Through the events of the. In the text 'A Christmas Carol', the author Charles Dickens presents the character of Ebenezer Scrooge as central to the moral message in a number of different ways.
To identify this, a number of different aspects within the text shall be looked at. 10 Surprising Lessons from "A Christmas Carol". We hold his character up as the epitome of selfishness, but that's to overlook how A Christmas Carol ends. To. Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"? Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London.
Oct 28, 2011. The Ghost of Christmas Past and Future teach Scrooge the lesson to do. Christmas Carol What is Charles Dickens moral message and how. Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"?
Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London. The moral of A Christmas Carol has everything to do with the transformation of the main character, Ebenezer Scrooge.
He begins the story as a miserly. Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"? Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London. 'A Christmas Carol' conveys simple but effective moral messages, such as the fact that happiness is not found in wealth, and to treat others as you yourself would like to be treated.
By showing the infinite change in a single character, Dickens manages to achieve all aims set in the preface, and to raise moral issues to make The moral message of a christmas carol reader think. Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"?
Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London. Looking at the state of economic inequality in the United States, Isabel Sawhill draws parallels between A Christmas Carol and the lessons of Ebenezer Scrooge. Economic leaders would be wise to. In the text 'A Christmas Carol', the author Charles Dickens presents the character of Ebenezer Scrooge as central to the moral message in a number of different ways.
To identify this, a number of different aspects within the text shall be looked at. Looking at the state of economic inequality in the United States, Isabel Sawhill draws parallels between A Christmas Carol and the lessons of Ebenezer Scrooge. Economic leaders would be wise to. In 'A Christmas Carol', Dickens intelligently conveys a deeper moral message via a simple story. By using emotional engagement, the reader is encouraged to alter his actions in the real world, rather than being preached to about what is the right thing to do.
Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"? Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London. Moral of Christmas carol? The Christmas Carol was written by Charles Dickens. It is the story of an elderly miser who has buried his humanvirtues in an unending search for wealth. Dec 17, 2013. Looking at the state of economic inequality in the United States, Isabel Sawhill draws parallels between A Christmas Carol and the lessons of.
The moral of A Christmas Carol has everything to do with the transformation of the main character, Ebenezer Scrooge. He begins the story as a miserly, closed-hearted man. Through the events of the. Revise and learn about the themes of Charles Dickens's novella, A Christmas Carol with.
The moral message of the novella is that all human beings have the. A Christmas Carol is the story of the moral redemption of Ebeneezer Scrooge, a heartless, mean, old money-lender who hates everybody and doesn't have any morals. It's the perfect mixture of Christmas magic, winter horror, and moral lesson. Sadly, the lessons taught to us by A Christmas Carol seem to be lost on a surprising number of Americans in this day.
The moral of" A Christmas Carol" is to make the people think back about the birth of Jesus Christ which we know celebrate as Christmas. Moral Message. Summary: Discusses the theme of" A Christmas Carol" by Charles Dickens. A theme is a moral message in a story. In" A Christmas Carol" Scrooge is a greedy old man who only cares about money. He soon learns about himself and how he acts. The theme of this story is that money should not matter and it. Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"?
Christmas carol is a novel written by Charles Dickens (1812-1870) during the Victorian times in London. Hi, I would like to know what is(are the moral message(s) and the morality tale of" A Christmas Carol" by Charles Dickens. Dickens was sending a message to his readers that Christmas is the time of year where. In 'A Christmas Carol Charles Dickens portrays Scrooge as a very. A allegory is a extended metaphor consisting of symbolism and all the elements of a novel.
A Christmas Carol, is an allegory that is delivering several message by using characters and scenes. 'A christmas carol' is an allegory. He is saying that people, who live a greedy senseless life, will suffer themselves in the future.
If we live our life doing good deeds and generally getting into the spirit of seasons then we will be rewarded in life and the after life. With each Ghost's tale functioning as a parable, A Christmas Carol advances the Christian moral ideals associated with kindness, and universal love for your community and of Victorian England in general. The book also offers a distinctly modern view of Christmas, less concerned with solemn religious ceremony and defined.
In the preface to 'A Christmas Carol', Dickens states that he had "endeavoured in this Ghostly little book, to raise the Ghost of an idea". To what extent do you think he is The moral message of a christmas carol in creating an enjoyable Christmas story with a serious moral message. The Christmas Carol was written by Charles Dickens.
It is the story of an elderly miser who has buried his human virtues in an unending search for wealth. An intervention is provided by his dead. Dec 23, 2015. 10 Surprising Lessons from "A Christmas Carol". This is related to our previous lesson, but points out an important part of the process: letting. In the preface to 'A Christmas Carol Dickens states that he had.
'A Christmas Carol' conveys simple but effective moral messages, such as the fact that. In the text 'A Christmas Carol', the author Charles Dickens presents the character of Ebenezer Scrooge as central to the moral message in a number of different ways. To identify this, a number of different aspects within the text shall be looked at.
Christmas Carol What is Charles Dickens moral message and how does he communicate it to the reader in "A Christmas Carol"? Christmas carol is a novel written. A Christmas Carol has attracted generations of readers with its clear parable-like structure and compelling ghost story. It's a moral tale that has proven timeless, but Dickens also wrote the story with a very present problem in mind, and his structure was designed to make the real issues of Victorian London stand out and provide greater.
A Christmas Carol by Charles Dickens is one of the most enduring and well-loved holiday stories. In fact, the novella, which was first published in 1843, is responsible for giving us many of our holiday customs, including the name "Scrooge" for a miser, the exclamation "Bah, humbug! " and. The Enduring Power of "A Christmas Carol": Hope, Redemption, Story As Eric mentions, a good story has the power to bring moral truths alive for daily life, and Dickens' "A Christmas Carol" is a great example of that.
christmas Reclaiming 'A Christmas Carol' By Stephen Skelton The Entertainment Ministry. CBN. com – Stephen Skelton, author of the new book A Christmas Carol: Special Church Edition, thinks that among the red-nosed reindeer and talking snowmen of the season, Charles Dickens' beloved Christmastime classic has been misplaced.
A Christmas Carol by Charles Dickens is one of the most enduring and well-loved holiday stories. In fact, the novella, which was first published in 1843, is responsible for giving us many of our holiday customs, including the name "Scrooge" for a miser, the exclamation "Bah, humbug!
" and. Charles dickens novella, 'A Christmas carol' has been assembled in a delicate yet powerful in order to have the maximum impact upon the reader. Dickens has constructed the story in 'staves' to help support and reinforce the moral message of redemption. The Christmas Carol was written by Charles Dickens.
It is the story of an elderly miser who has buried his human virtues in an unending search for wealth. An intervention is provided by his dead.


text:
Charlotte Hornets 2018 NBA Mock Draft Roundup: June 6th
Some players have been picking up steam as potential Hornets as the draft gets closer and closer.
By Dy1an Jackson@JaxonNBA Jun 6, 2018, 1:43pm EDT
Share All sharing options for: Charlotte Hornets 2018 NBA Mock Draft Roundup: June 6th
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The NBA Draft is the most unpredictable, destiny-driven, crapshoot there is in sports. Nobody knows who is going to be good or who is going to be a flat-out bust. That is what makes the event so incredibly fun. Sure, the Hornets are known for picking painfully average players above perennial superstars, but would you rather have Devin Booker or Frank Kaminsky? It's obviously Frank Kaminsky, right?
While you think on that, let's take a look at who the experts predict the Hornets will take in a couple weeks:
Fansided (Brendon Kleen): Shai Gilgeous-Alexander, Guard, Kentucky
We're going to try the #FanSidedMock thing here again, Hornets fans. I understand Gilgeous-Alexander isn't much of a consolation prize after a disappointing season and complete reset in the front office, but he just might be the best player available here. In addition, the Hornets are facing decision time on Kemba Walker and will soon need a replacement ball-handler.
The freshman was incredibly efficient leading the young Wildcats over the course of the season, getting better game by game. He is 6-6 with legitimate lead ball-handler skills, a rarity with clear value, especially considering the way the league's best teams play. The Hornets have very little young talent, but Gilgeous-Alexander is the type of player who would smoothly make everyone better, from stretch big Frank Kaminsky to Michael Kidd-Gilchrist, a sweet fit on defense who needs support as a scorer.
My take: Shai Gilgeous-Alexander seems to be the consensus pick among Hornets bloggers. His length and fluidity are rare for a point-guard and he should be a plus defender almost instantly. Gilgeous-Alexander could use some work on his jump-shot but made strides at the end of the season for the Kentucky Wildcats with his scoring. SGA would fit in very nicely alongside Malik Monk and might even replace All-Star guard Kemba Walker in the long run, should Charlotte choose to trade him.
Bleacher Report (Jonathan Wasserman): Miles Bridges, Forward, Michigan State
Bridges should be a draft-night target for the Hornets, who need offense from both forward spots. He would work best as a small-ball stretch 4 alongside Dwight Howard, though continued progress on his shot-creating and off-the-dribble scoring should mean Bridges could also play next to Marvin Williams.
My take: Miles Bridges is a low-risk player. Bridges can play the small forward or power forward position and has the athleticism to be a dynamic player. He has an underrated shot and decent mechanics beyond the 3-point line. However, Bridges can get tunnel vision when attacking the basket instead of deferring the ball to open teammates. His effort is questionable at times, but if Charlotte wants a 'safe' player, Bridges is about as good as it gets this year.
The Ringer (Draft Guide): Lonnie Walker IV, Wing, Miami
An explosive, shifty guard who showed flashes of go-to scoring skills once his role was increased midseason.
My take: We went from one of the safest players to one of the biggest risks in this draft. Lonnie Walker is not a 'sure thing.' Walker's jump shot is amazing, however, his efficiency could use some improvement. According to the Stepien, Walker only shot 32 percent from the NBA line. He is one of the best athletes in this draft, along with Zhaire Smith and Mohammed Bamba, but his off-ball defense is a major flaw. He is often caught flat-footed and seems paralyzed when the opponents shot is in the air. All in all, this would be a very risky selection.
My Prediction: Shai Gilgeous-Alexander, Guard, Kentucky
The Hornets need help in the frontcourt, but in a draft so top-heavy with forward and big talent, there won't be much there for the Hornets at eleven. However, they will likely have a nice crop of guards and wings to pick from, including Zhaire Smith, De'Anthony Melton, Lonnie Walker, and maybe even Collin Sexton. But above all of those players, Shai Gilgeous-Alexander simply makes the most sense.
Charlotte is absolutely loaded with scorers in the backcourt, with Kemba Walker, Jeremy Lamb, and future MVP Malik Monk (come on, you know it's true), the impact is there. The Hornets, however, need more defensive reliability and more shot creation. Gilgeous-Alexander brings both of these things.
Recap: Big second half propels Hornets past Heat, 122-117 Terry Rozier scored 31 in the win.
Preview: Hornets head back out on the road to face Bucks It's a three-game trip to the Great Lakes region for the Hornets this time around.


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Abstract: This paper aims at comparatively investigating the impact of institutional environment quality (IEQ) on tax evasion in old (pre-2004) and new (post-2004) European Union (EU) member states. IEQ is measured by the World Bank's Worldwide Governance Indicators, which include voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption. The size of their shadow economy is used as a proxy for tax evasion. Using a linear mixed model to analyze the data, the results indicate a higher level of tax evasion in new member states compared to the old member states. Further, our analysis indicates that tax evasion is decreasing in the old member states, but at a lower rate compared to the new EU members. Overall, our results indicate that the relationship between IEQ and tax evasion is different between old and new member states. Specifically, our results indicate that while regulatory quality, voice and accountability, control of corruption, political stability, and government effectiveness are significant determinants of tax evasion levels in older EU members, government effectiveness is the only significant factor in the new EU member states.


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text:
\section{Introduction}

A bipartite network is a graph which connects two distinct sets
(or partitions) of nodes, which we will refer to as the $top$ and the $bottom$ set.
An edge in the network runs between a pair of a $top$ and a $bottom$ node but never between a pair of $top$ or a pair
of $bottom$ nodes (see Fig. \ref{fig:scheme_bnw}).
Typical examples of this type of networks include collaboration
networks
such as the movie-actor~\cite{ramasco,watts_98,collaboration3,Alava:06,movie1,movie2},
article-author~\cite{collaboration4,collaboration5,collaboration6,collab7,lambiotte_05}, and board-director~\cite{caldarelli_05, strogatz_01} network.
In the movie-actor network, for instance, the movies and actors are
the elements of the $top$ and the $bottom$ set respectively, and an edge
between an actor $a$ and a movie $m$ indicates that $a$ has acted in
$m$. The actors $a$ and $a'$ are $collaborators$ if both have participated in the same movie, i.e., if both are connected to the same node $m'$.
The concept of $collaboration$ can be extended to include so diverse phenomena represented by bipartite networks as the city-people network~\cite{eubank_04}, in which an edge
between a person and a city indicates that the person has visited that particular city, the
word-sentence~\cite{cancho,Latapy}, bank-company~\cite{souma_03} or donor-acceptor network, which accounts for injection and merging of magnetic field lines~\cite{sneppen_04}.

Several models have been proposed to synthesize the structure of
bipartite networks when both partitions grow unboundedly over time ~\cite{ramasco,watts_98,collaboration3,Alava:06,Latapy}.
It has been found that for such growth models when each incoming $top$ node connects
through preferential attachment to $bottom$ nodes the emergent
degree distribution of $bottom$ nodes follows a power-law~\cite{ramasco}.
Another important property of bipartite networks is that the clustering coefficient cannot be measured in the standard way~\cite{watts_98}, and has to be measured as a cycle of four
connections ~\cite{lind_06}.

On the other hand, bipartite networks, where one of the partitions remains fixed over time (i.e., the number of
$bottom$ nodes are constant), have received comparatively much less attention.
Recently it was shown through numerical simulations that restrictions in the growth rate of the partitions can lead to non-scaling degree distribution highly sensitive to the parameters of
the growth model~\cite{dahui_05}. However, there is still no systematic and analytical study of this kind of networks.
Realizations of this type of bipartite networks include
numerous relevant
systems such as
the interaction between the codons and genes as well as amino acids and proteins in biology and elements and compounds
in chemistry.
We can also include
in this group those networks in which one partition can be
considered to be in a pseudo-steady state while the other one keeps on
growing at a much faster rate. For instance, it is reasonable to assume that for the city-people network~\cite{eubank_04}, the city growth rate is zero compared with the
population growth rate. Other examples of this type of networks could be the phoneme-language~\cite{Choudhury:06,Mukh:06}, in
linguistics, or train-station~\cite{sen_03,seaton} in logistics.

In this work, we study the growth of bipartite networks in which the
number of nodes in one of the partitions is kept fixed.
We explore random and
preferential attachment as well as a combination of both.
We obtain an exact analytical expression for the degree distribution of the $bottom$ nodes assuming that the
attachment is sequential, i.e., a single edge is added to the network in one time step. We also present an approximate
solution for the case of parallel attachment, i.e., when more than one edge are incorporated into the network in a
given time step.
We show that, depending on the relative weight of random
to preferential  attachment, the degree-distribution of this type
of network falls into one of four possible regimes which range from
a binomial distribution for pure random attachment to an u-shaped
distribution for dominant preferential attachment.
For combinations of random and preferential attachment the
degree-distribution asymptotically tends to beta-distribution with time.

\begin{figure}
\centering\resizebox{\columnwidth}{!}{\rotatebox{0}{\includegraphics{fig_1.eps}}}
\caption{Scheme of a growing bipartite network. In the example, the number of fixed $bottom$ nodes is $N=4$.
Each $top$ nodes arrives with $\mu=2$  edges. The $top$ node $D$ represents a new incoming node.} \label{fig:scheme_bnw}
\end{figure}

\section{The growth model}\label{sec:syn}

We consider the case in which the $top$ partition grows with time
while the number of nodes in the $bottom$ partition $N$ is kept
constant. We grow the network in the following way. At each time
step a new node is incorporated to the $top$ set.
Then, $\mu$ edges are connected from the new node to the nodes in
the $bottom$ set (see Fig. \ref{fig:scheme_bnw}).
The probability of attaching a new edge to the $bottom$ node $i$ is
$\widetilde{A}(k_{i}^{t})$, where $k_{i}^{t}$ refers to the degree of
the $bottom$ node $i$ at time $t$. We refer to
$\widetilde{A}(k_{i}^{t})$ as the attachment kernel and define it
as:
\begin{equation}\label{eq:kernel_attachment}
\widetilde{A}(k_{i}^{t}) = \frac{\gamma k_{i}^{t} + 1}{\sum_{j=1}^N
(\gamma k_{j}^{t} + 1)}
\end{equation}
where the sum in the denominator runs over all $bottom$ nodes, and
$\gamma$ is a model parameter which controls the relative weight of random to
preferential attachment. $\gamma$ can be
thought of as $\gamma=1/\alpha$, where  $\alpha$ is a positive constant
known in previous models
as {\em initial attractiveness}~\cite{mendes}.

There is a subtlety related to the attachment kernel and $\mu$ that
is worth to mention. The stochastic process can be performed in such
a way that the attachment of the $\mu$ incoming nodes is done
sequentially, i.e., one edge is attached per time step. This implies
that the denominator of $\widetilde{A}(k_{i}^{t})$ has to be updated
for each incoming node (and hence an edge), and that $t$ refers to the event of
incorporating a new edge to the $bottom$ set.
Alternatively, the attachment of the $\mu$ new edges can be done in
parallel. This implies that the new $\mu$ edges have all the same
probability of attaching to $bottom$ node $i$. In this case, $t$
refers to the event of incorporating a new node to the $top$ set.

There are two significant limits to consider: $\gamma = 0$ and
$\gamma \longrightarrow \infty$. For $\gamma = 0$, Eq.
(\ref{eq:kernel_attachment}) reduces to
$\widetilde{A}(k_{i}^{t})=1/N$, which implies that all $bottom$ nodes
have the same probability of being selected by an incoming edge.
This limit corresponds to pure random attachment.
For $\gamma \longrightarrow \infty$ Eq. (\ref{eq:kernel_attachment})
reduces to $\widetilde{A}(k_{i}^{t})=k_{i}^{t}/\sum_{j=1}^N (
k_{j}^{t})$, which means that higher degree $bottom$ nodes have higher
probability of being selected. This case corresponds to pure
preferential attachment.

Stochastic simulations have been performed with the initial
condition
where all $bottom$ nodes at time $t=0$ have zero degree, i.e., initially no
edges are connected to the $bottom$ nodes.

\section{Evolution equation for sequential attachment}\label{sec:derive}

Now we aim to derive an evolution equation for the degree
distribution of the $bottom$ nodes. We focus on sequential attachment.
Let $p_{k,t}$ be the probability of finding a randomly chosen $bottom$
node with degree $k$ at time $t$.
We recall that $t$ refers to the $t$-edge attachment event.
$p_{k,t}$ can be defined as $p_{k,t} = \left< n_{k,t} \right>/N$,
where $n_{k,t}$ refers to the number of nodes in the $bottom$ set with
degree $k$ at time $t$, and $\left< ... \right>$ denotes ensemble
average, i.e. average over realizations of the stochastic process
described above.
We express the evolution of $p_{k,t}$ in the following way:
\begin{equation}\label{eq:markovchain}
p_{k,t+1} = (1 - A(k,t)) p_{k,t} + A(k-1,t) p_{k-1,t}
\end{equation}

where $A(k,t)$ refers to the probability that the incoming edge
lands on a $bottom$ node of degree $k$.
$A(k,t)$ can be easily derived from Eq. (\ref{eq:kernel_attachment}) and takes the
form:
\begin{equation}\label{eq:kernel_mu1}
A(k,t)=\frac{\gamma k + 1}{\gamma t + N}
\end{equation}
The reasoning behind Eq. (\ref{eq:markovchain}) is the following.
The probability of finding a $bottom$ node with degree $k$ at time
$t+1$ decreases due to the number of nodes, which have a degree $k$ at time $t$
and receive an edge at time $t+1$ therefore acquiring degree
$k+1$, i.e., $A(k,t) p_{k,t}$. Similarly, this probability increases due to the number of
nodes that at time $t$ have degree $k-1$ and receives an edge at time $t+1$
to have a degree $k$, i.e., $A(k-1,t) p_{k-1,t}$. Hence the net increase in the probability can be expressed as in Eq.
(\ref{eq:markovchain}).

According to what was done in the stochastic simulations, we assume that at time $t=0$ all
$bottom$ nodes have zero degree, which implies the initial condition
$p_{k,t=0}=\delta_{k,0}$, where $\delta_{k,0}$ is the Kronecker
delta function.

\section{Exact solution for sequential attachment}\label{sec:derive}

We look for the exact analytical solution of sequential attachment.
For this purpose we express Eq. (\ref{eq:markovchain}) as:
\begin{equation}\label{eq:markovvectorial}
\mathbf{p}_{t+1} = \mathbf{M}_t\mathbf{p}_t = \big[\prod_{\tau=0}^t
\mathbf{M}_{\tau}\big] \mathbf{p}_0
\end{equation}
where $\mathbf{p}_t$ denotes the degree distribution at time $t$ and
is defined as $\mathbf{p}_t = [p_{0,t}\ p_{1,t}\ p_{2,t}\
\ldots]^T$, $\mathbf{p}_0$ is the initial condition expressed as
$\mathbf{p}_0 = [1\ 0\ 0\ \ldots ]^T$, and $\mathbf{M}_{\tau}$ is
the evolution matrix at time $\tau$ which is defined as:
\begin{equation}
\mathbf{M_{\tau}} = \left( \begin{array}{c c c c c}
1 - A(0, \tau) & 0 & 0 & 0 & \ldots\\
A(0, \tau) & 1 -A(1, \tau) & 0 & 0 & \ldots\\
0 & A(1, \tau)& 1 - A(2, \tau) & 0 & \ldots\\
\vdots & \vdots & \vdots & \vdots & \ddots
\end{array}
\right)
\end{equation}

Since our initial condition is a vector with zeros in all position
except in the first one, all the relevant information, i.e., the
degree distribution of the $bottom$ nodes, is in the first column of
$\big[\prod_{\tau=0}^t \mathbf{M}_{\tau}\big]$. A close inspection
to the evolution of this column, explicitly using Eq. (\ref{eq:kernel_mu1}), reveals that the $k$-th element of it, which corresponds
to $p_{k,t}$, can be expressed as:
\begin{equation}\label{eq:solutionsequential}
p_{k,t} = \left( \begin{array}{c} t \\ k \end{array}\right)
\frac{\prod_{i=0}^{k-1}{(\gamma i+ 1)} \prod_{j=0}^{t-1-k}{(N - 1 +
\gamma j)}}{\prod_{m=0}^{t-1}{(\gamma m + N)} }
\end{equation}
for $k \leq t$, and $p_{k,t} = 0$ for $k > t$, and where we have
defined  $\prod_{i=0}^{-1}{(...)}=1$, and $\left( \begin{array}{c} t \\ k \end{array}\right)$ refers to the combinatorial number $t!/[\left(t-k\right)! k!]$.

Eq. (\ref{eq:solutionsequential}) is the exact solution of Eq.
(\ref{eq:markovchain}) using as initial condition
$p_{k,t=0}=\delta_{k,0}$, i.e., the analytical expression of the
degree distribution of the $bottom$ nodes when sequential attachment
is applied.

In the limit of $\gamma=0$ Eq. (\ref{eq:solutionsequential}) reduces
to:
\begin{equation}\label{eq:solutionsequential_ra}
p_{k,t} = \left( \begin{array}{c} t \\ k \end{array}\right)
\left(\frac{1}{N}\right)^{k} \left(1-\frac{1}{N}\right)^{t-k}
\end{equation}
for $k \leq t$, and $p_{k,t} = 0$ for $k > t$. In other words, Eq.
(\ref{eq:solutionsequential_ra}) is the solution of the sequential
problem when pure random attachment is applied.
\begin{figure}
\centering\resizebox{\columnwidth}{!}{\rotatebox{0}{\includegraphics{fig_2.eps}}}
\caption{The four possible degree distributions depending on $\gamma$.
Symbols represent average over $5000$, in (a)-(c), and $50000$, in (d), stochastic simulations. The dashed curve is the theory given by Eq. (\ref{eq:solutionparallel}).
From (a) to (c), $t_0=1000$, $N=1000$ and $\mu=20$.
(a) at $\gamma=0$, $p(k,t)$ becomes a binomial distribution.
(b) $\gamma=0.5$, the
distribution exhibits a maximum which shifts with time for $0\leq\gamma < 1$.
(c) $\gamma=1$, $p(k,t)$ does not longer
exhibit a shifting maximum and the distribution is a monotonically
decreasing function of $k$ for $1\leq \gamma\leq (N/\mu) - 1$.
(d) $\gamma=2500$, $t_0=100$, $N=1000$ and $\mu=1$. $p(k,t)$ becomes an u-shaped curve for $\gamma > (N/\mu) - 1$.
} \label{fig:transition_snapshots}
\end{figure}
\section{Parallel attachment}\label{sec:derive}
We focus on parallel attachment, i.e., when more than one edge are
added per time step. We do not aim to derive an exact analytical
expression for the degree distribution of this problem but provide a
reasonable approximation.
We recall that for parallel attachment $t$ refers to the event of
incorporating a new $top$ node.
We assume that $\mu \ll N$ and expect Eq. (\ref{eq:markovchain}) to
be a good approximation of the process after replacing $A(k,t)$ with
$A_p(k,t)$. We define $A_p(k,t)$ as
\begin{equation}\label{eq:kernel_mu_gt_1}
A_p(k,t)=\frac{\left( \gamma k + 1 \right)\mu}{\gamma \mu t + N} \, .
\end{equation}
The term $\mu$ in the denominator appears since in this case the total degree of the $bottom$ nodes at any point in time
is $\mu t$ rather than $t$ as in Eq. (\ref{eq:kernel_mu1}). The numerator contains a $\mu$ since at each time step there are $\mu$
edges that are being incorporated into the network rather than a single edge.

It is important to mention here that Eq. (\ref{eq:markovchain}) cannot exactly represent the stochastic
parallel attachment because it explicitly assumes that in one time
step a node of degree $k$ can only
get converted to a node of degree $k+1$. Clearly,
the incorporation of $\mu$ edges in parallel allows the possibility
for a node of degree $k$
to get converted to a node of degree $k+ \mu$. The correct
expression for the evolution of $p_{k,t}$ reads:
\begin{equation}\label{eq:parallel}
p_{k,t+1} = (1 - \sum_{i=1}^{\mu}{\widehat{A}(k,i,t)}) p_{k,t} +
\sum_{i=1}^{\mu}{\widehat{A}(k-i,i,t)} p_{k-i,t}
\end{equation}
where $\widehat{A}(k,i,t)$ represents the probability at time $t$ of a node of
degree $k$ of receiving $i$ new edges in the next time step. We
expect Eq. (\ref{eq:markovchain}) to be a good approximation of Eq.
(\ref{eq:parallel}) when $\widehat{A}(k,1,t) \gg \widehat{A}(k,i,t)$ where $i>1$.

The solution of Eq. (\ref{eq:markovchain}) with the attachment kernel given by Eq. (\ref{eq:kernel_mu_gt_1})
 reads:
\begin{equation}\label{eq:solutionparallel}
p_{k,t} = \left( \begin{array}{c} t \\ k \end{array}\right)
\frac{\prod_{i=0}^{k-1}{\left(\gamma i+ 1\right)}
\prod_{j=0}^{t-1-k}{\left( \frac{N}{\mu} - 1 + \gamma
j\right)}}{\prod_{m=0}^{t-1}{\left(\gamma m + \frac{N}{\mu}\right)}
}
\end{equation}

We expect Eq. (\ref{eq:solutionparallel}) to approximate the degree
distribution of the stochastic process with parallel attachment for
$\mu \ll N$. This means that we cannot expect the approximation to hold for large values of $\gamma$ or $\mu/N$.

In the limit of random attachment, i.e., $\gamma=0$, Eq.
(\ref{eq:solutionparallel}) becomes $p_{k,t} = \left(
\begin{array}{c} t \\ k \end{array}\right)
\left(\frac{\mu}{N}\right)^{k} \left(1-\frac{\mu}{N}\right)^{t-k} $.

Figs. \ref{fig:transition_snapshots}(a)-(c) and \ref{fig:temporalevolution}(a)-(b) show a comparison between stochastic simulations and Eq.(\ref{eq:solutionparallel}) and prove that Eq. (\ref{eq:solutionparallel}) is a good approximation for
$\mu \ll N$ and relative low values of $\gamma$. For large values of $\gamma$, as said above, the approximation fails. However, for $\mu=1$ Eq. (\ref{eq:solutionparallel})
reduces to Eq. (\ref{eq:solutionsequential}), which in this case is the exact solution, and then the theory works for all values of $\gamma$ (see Figs. \ref{fig:transition_snapshots}(d) and \ref{fig:temporalevolution}(c)).

\begin{figure}
\centering\resizebox{\columnwidth}{!}{\rotatebox{0}{\includegraphics{fig_3.eps}}}
\caption{Temporal evolution of $p(k,t)$ for various values of
$\gamma$. Symbols represent average over $5000$, in (a)-(b), and $50000$, in (c), stochastic
simulations. The black dashed curve is the theory, represented through Eq. (\ref{eq:solutionparallel}).
The red solid curves correspond to the approximation given by the beta-distribution, Eq. (\ref{beta}).
(a) $\gamma=0.5$, and (b) $\gamma=1$. $N=1000$ and $\mu=20$. Compare with Fig. \ref{fig:transition_snapshots}(b) and (c).
(c) $\gamma=2500$, $N=1000$ and $\mu=1$, see Fig. \ref{fig:transition_snapshots}(d). }
\label{fig:temporalevolution}
\end{figure}

\section{From random to preferential attachment}\label{sec:derive}

Fig. \ref{fig:transition_snapshots} shows that there is a clear
transition from random to preferential attachment.
At $\gamma=0$ (see Fig. \ref{fig:transition_snapshots}(a)) we observe that $p_{k,t}$ is centered around the
maximum (mode of the distribution) which shifts with time at a speed
of $\mu/N$ per time step, while the width of the distribution also spreads with
time. This behavior
corresponds to a situation in which all $bottom$ nodes receive roughly
the same amount of edges with time. The well defined maximum tells
us about the average number of edges each $bottom$ node has, while the
variance of the distribution indicates the presence of fluctuations
around that mean value which increases with time.

For $0 < \gamma < 1$ the
distribution is not longer symmetric (see Fig. \ref{fig:transition_snapshots}(b)). $Bottom$ nodes having small degree rarely receive an edge, and so
$p_{k,t}$ decays slowly for small value of $k$. However the distribution still
exhibits a maximum, mode of the distribution, which shifts with time (see Fig. \ref{fig:temporalevolution}(a)).

For $1 \leq \gamma \leq (N/\mu)-1$ the distribution looses the (local)
maximum and becomes monotonically decreasing (see Fig.
\ref{fig:transition_snapshots}(c)). We can always find a
$bottom$ node with small degree because small degree nodes hardly get
an edge. On the other hand, there are very few nodes with high
degree, and these ones receive almost all incoming edges. The temporal evolution of the distribution for this range of $\gamma$ is shown in Fig. \ref{fig:temporalevolution}(b).

For $\gamma > (N/\mu)-1$ the distribution described by Eq. (\ref{eq:solutionparallel})
exhibits an u-shape. As said above, we cannot expect Eq. (\ref{eq:solutionparallel}) to
approximate the stochastic process for such large values of $\gamma$. Stochastic simulations performed in this range of $\gamma$ for $\mu>1$ are very noisy and the u-shape
cannot be obtained by averaging over few simulations. However, for $\mu=1$ we can illustrate the u-shaped distribution in a clear way, see Fig.
\ref{fig:transition_snapshots}(d).
As in the previous case, we still can find a
$bottom$ node with small degree because small degree nodes hardly get an edge (see maximum at $k=0$). But on the other hand, we can be sure that there is at least one node with
very large degree, because
the node with the largest degree at time $t-1$ very likely is going to get an edge at time $t$, in an effect like ``winner takes all" (see peak at $k=t$). The node
with largest degree keeps on increasing its degree with time, and so $p_{k,t}$ has two peaks, one located at $k=0$ and the other one at $k=t$  (see Fig.
\ref{fig:temporalevolution}(c)).

\section{Beta Distribution}\label{sec:beta}

In the following we offer a  quantitative
 analysis of the transition by showing that $p_{k,t}$ behaves asymptotically with
time as a beta-distribution for $\gamma > 0$.

For $t \gg \eta$, where $\eta = N/ (\gamma \mu)$, we can approximate
the products in Eq. (\ref{eq:solutionparallel}) by gamma-functions
and apply Stirling's approximation. After some algebra we obtain:
\begin{equation}\label{beta}
p_{k,t} \simeq  C^{-1}\left( k/t \right)^{\gamma^{-1}-1} \left(1-
k/t \right)^{\eta-\gamma^{-1}-1}
\end{equation}
where $C$ is a normalization constant defined by $C = \int_{0}^{t}{
\left( k'/t \right)^{\gamma^{-1}-1} \left(1- k'/t
\right)^{\eta-\gamma^{-1}-1}}dk'$.

Fig. \ref{fig:temporalevolution} shows a comparison between
stochastic simulations (circles), the theoretical solution given by Eq. (\ref{eq:solutionparallel}) (black dashed curve), and the approximation given by Eq. (\ref{beta}) (red
solid curve) for two different values of $\gamma$ at various times. In Fig.
\ref{fig:temporalevolution} it can be observed that $p_{k,t}$
approaches asymptotically to Eq. (\ref{beta}) (compare the black dashed and the red solid curves). Notice that Eq.
(\ref{beta}) does not have any fitting parameter and represents a
beta-distribution $f(x;\alpha, \beta)$ of the variable $x=k/t$ and
fixed parameters $\alpha=\gamma^{-1}$ and $\beta=\eta -
\gamma^{-1}$.

For $0<\gamma<1$,  $\alpha>1$ and $\beta>1$ the mode of the
distribution is given by $(\alpha - 1)/(\alpha + \beta
-2)=((\gamma^{-1})-1)/(\eta - 2)$. This can be easily verified by
taking the first derivative of Eq. (\ref{beta}) equal to zero. From
this we learn that in this range of $\gamma$ the maximum of the
distribution $k_{max}$ is located at
$k_{max}=t((\gamma^{-1})-1)/(\eta - 2)$ (see Fig.
\ref{fig:temporalevolution}(a)). In the limit of $\gamma
\longrightarrow 0$ we retrieve the behavior of $k_{max}$ observed
for pure random attachment, i.e., $k_{max}=t(\mu/N)$.

At $\gamma=1$, $\alpha=1$ and $\beta>0$, the moving peak is no longer found,
i.e., the mode of the distribution is located for all times at
$k_{max}=0$ (see Fig.
\ref{fig:temporalevolution}(b)). This condition also holds for $1<\gamma\leq(N/\mu)-1$.

For $\gamma>(N/\mu)-1$, there is another regime for the degree distribution. For $\alpha<1$
and $\beta<1$, $p_{k,t}$ becomes u-shaped with a peak fixed at $k=0$ and the other one shifting with $t$. For $\mu=1$
the additional peak is located at $k=t$ (see Fig.
\ref{fig:temporalevolution}(c)).

\section{Concluding remarks}\label{sec:conc}

We have studied the growth of bipartite networks in which the number
of nodes in the $bottom$ set is kept fixed.
We consider random and preferential node attachment as well as the
combination of both.
We have derived the degree distribution evolution equation for
sequential and parallel attachment of nodes.
For sequential attachment we have provided the exact analytical
solution of the problem.
For parallel attachment we have obtained an approximate expression
for the degree distribution. Through simulations we have provided
numerical evidence which shows that the approximation for parallel attachment is reasonable
when $\mu \ll N$ and $\gamma$ is small.

Finally, we have shown that for both, sequential and parallel
attachment, the degree-distribution falls into one of four possible
regimes: a) $\gamma=0$, a binomial distribution whose mode shifts
with time, b) $0<\gamma<1$, a skewed distribution which
exhibits a mode that shifts with time, c) $1 \leq \gamma \leq
(N/\mu) - 1$, a monotonically decreasing distribution with the mode
frozen at $k=0$, and d) $\gamma>(N/\mu) - 1$, an u-shaped
distribution with peaks at $k=0$ and $k=t$.

Our results might be useful to explain the dynamical growth of various systems like the speech sound
inventories of the world's languages, which can be rendered a bipartite structure as explained through the
phoneme-language network in~\cite{Choudhury:06,Mukh:06}. A detailed study of the parameter $\gamma$ leading to the
degree distribution of the network can then shed some light on the amount of randomness/preference that has gone into
shaping the evolution of such a system.

\acknowledgments

This work was supported by the Indo-German (DST-BMBT) project grant. The authors would like to
extend their gratitude to Dr. Andreas Deutsch, Dr. Lutz Brusch and Dr. Luis G. Morelli for
their valuable comments and suggestions. MC and AM would like to thank Media Lab Asia and
Microsoft Research India respectively for financial assistance. They would also like to
extend their gratitude to Prof. Anupam Basu for providing them with the laboratory
infrastructure. FP would also like to acknowledge the hospitality of IIT-Kharagpur and financial support through Grant No.
11111.

redpajama_set_name: RedPajamaArXiv


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