Aberdeen Global Income Fund Inc is a closed-end, non-diversified management investment company. The fund's principal investment objective is to provide high current income by investing primarily in fixed income securities. As a secondary investment objective, the fund seeks capital appreciation, but only when consistent with its principal investment objective. The fund invests in Government Bonds and Corporate Bonds and its investments are divided into three categories namely Developed Markets, Investment Grade Developing Markets and Sub-Investment Grade Developing Markets.


It wasn't that long ago that the digital economy was thought to float on a plane above conventional geopolitics and economics. The global Internet, aspiring to be "free and open" and surprisingly close to that in reality, was a general-purpose technology as revolutionary as the internal combustion engine, telephony, electricity and industrial machines all wrapped into one. Phrases such as "the death of distance," "the end of geography" and "organizing without organizations" might have been perceived as a bit over-hyped, but not entirely mistaken. Directionally, at least, they signaled a profound new reality of political economy and social life. Competition would be immense and intense in this new reality, in part because the advantages of incumbency in the pre-Internet era had become the legacy burdens of the obsolete installed base in the new era, and everything was up for grabs from just about anywhere that had a decent bandwidth connection.
That kind of market hyper-competition left no room for rivalry — zero-sum confrontations buttressed by the power of governments. Why battle with rivals over a limited pie when new value could be created by simply routing around or transcending old conflicts? Why have governments steer development when the only limit on private innovation is Moore's Law? This hopeful narrative about digital technology reached its apogee in John Perry Barlow's 1996 Declaration of Independence in Cyberspace: "Governments of the Industrial World, you weary giants of flesh and steel, I come from Cyberspace, the new home of Mind. On behalf of the future, I ask you of the past to leave us alone. You are not welcome among us. You have no sovereignty where we gather." It seems mildly absurd in 2019, but Barlow's words were sufficiently mainstream to be taken seriously when he delivered them at the premier convening of incumbent power, the World Economic Forum's Annual Meeting in Davos, Switzerland.
Fast forward to the present, and the narrative around digital technology seems almost entirely different. Data have become a strategic commodity that companies and governments are trying to protect, defend and even hoard to the exclusion of others.
Fast forward to the present, and the narrative around digital technology seems almost entirely different. Data have become a strategic commodity that companies and governments are trying to protect, defend and even hoard to the exclusion of others. In 2018, it became standard practice for countries around the world (even countries that have very little research or commercial activity to speak of in this area) to write and announce national "AI strategies." Developing human capital in data science and machine learning is becoming a strategic priority for governments. The multiple-winner optimism of market competition has receded in favor of a rivalrous clash for technological hegemony, and governments are no longer standing on the sidelines. The leaders of Russia, China and the United States have all said in one way or another that dominance in AI will over the next decade translate into dominant national power and leadership in the global economy and security.
At the frontiers of technology, competition has transformed into rivalry. How did this happen? And is this a transition phase, or is it rather a new geopolitical reality?
One interpretation is that we've seen this story or at least one very much like it unfold before in digital technology, and that calm is warranted as we transit through a zero-sum, government-led rivalrous phase that will not become anything like a persistent condition. The battles over the semiconductor industry between the US and East Asia during the 1980s had some of these characteristics, but it didn't last. After years of subsidization, the creation of national consortia like Sematech, contentious trade negotiations around business practices like the Structural Impediments Initiative, and much hand-wringing about losing the race for predominance, the world came to an intellectual and political synthesis that significantly turned down the heat of national rivalry in semiconductors.
Japan suffered through an economic collapse that was cushioned little, if at all, by its digital technology assets. Chinese manufacturing rose to the fore and made possible a hyper-efficient global supply chain for computers and other electronics (and later mobile phones) that massively accelerated the dissemination and deployment of today's digital infrastructure around the world. The rise of open-source software and the globalization of the supply chain for software engineering (led by IBM, a US-based multinational that re-constituted itself in the early 2000s as a "globally integrated enterprise") took that part of the digital value chain out of the national rivalry mindset.
When Thomas Friedman in 2005 proclaimed that the world was "flat," he captured the mood of that moment accurately and succinctly — but almost precisely at the moment when this period of relative calm was coming to an end. It might have been natural to assume that the next generation of digital technology — machine learning above all — would continue to fit Friedman's template for a globally competitive level playing field. But machine learning is different.
Machine learning broadly refers to the science and technology of machines capable of sophisticated information processing that are not "programmed" in a traditional sense by people writing sets of instructions (code) that the computer then executes. Machine learning instead uses a set of methods that enable computers themselves to extract patterns from large data sets and evolve their own algorithms (decision rules) that the machine then runs against new data, problems and questions. To recognize a face, for example, a machine-learning system does not run code that a programmer wrote to describe what eyes, ears and noses look like. Instead, it derives an algorithm that infers what faces look like from a training data set according to methods and rules that were the human contribution. The facial-recognition algorithm is a property of the machine-learning system, and even in a case that is only moderately sophisticated, may involve a set of parameters that are orders of magnitude larger and more complex than a human can comprehend.
Data is the fuel that makes the system run. But the analogy only goes so far, because the engine and the fuel both fade into the background as the system learns and improves its performance. And this is where the new dynamics of rivalry come to the fore, because data and machine learning systems together constitute a positive feedback loop where the leaders will tend to accelerate ahead of the laggards at an increasing rate.
The methods and rules that humans contribute to the system are its engine, sitting at the intersection of advanced statistics and computer science. Data is the fuel that makes the system run. But the analogy only goes so far, because the engine and the fuel both fade into the background as the system learns and improves its performance. And this is where the new dynamics of rivalry come to the fore, because data and machine learning systems together constitute a positive feedback loop where the leaders will tend to accelerate ahead of the laggards at an increasing rate. Those leaders and laggards can be countries just as easily as they can be companies, replacing corporate competition with national rivalry that itself can become a positive feedback loop and something of a self-fulfilling prophecy, at least for a time.
The logic of the positive feedback loop is conceptually simple. Consider this abstraction: Users in country X send "raw" data to machine-learning companies in country Y as they use digital products. Those companies use the "imported" data as inputs to their systems that, in turn, create higher value-added data products. These might be algorithms that tell farmers precisely when and where to plant a crop for top efficiency; business process re-engineering ideas; healthcare protocols; annotated maps; consumer predictive analytics; insights about how a government policy actually affects the behavior of businesses or individuals and more. These value-added data products are then exported from companies in country Y back to users in country X.
Here's a concrete example: Imagine that a large number of Parisians use Uber on a regular basis to get around the city. Each passenger pays Uber a fee for her ride. Most of that money goes to the Uber driver in Paris. Uber itself takes a cut, but it's not the money flow that really matters here. Focus instead on the data flow that Uber receives from all its Parisian "customers" (best thought of here as including both "sides" of the two-sided market; that is, Uber drivers and passengers are both customers in this simple model). Each Uber ride in Paris produces a quantum of raw data — for example, about traffic patterns, or about where people are going at what times of day — that Uber collects. This mass of raw data, over time and across geographies, feeds the further development of Uber's algorithms. These, in turn, are more than just a support for a better Uber business model (although that effect in and of itself matters because it enhances and accelerates Uber's competitive advantage over traditional taxi companies). Other, more ambitious data products will reveal highly valuable insights about transportation, commerce, life in the city, and potentially much more (what is possible stretches the imagination). Now, if the mayor of Paris in 2025 decides that she needs to launch a major re-configuration of public transit in the city to take account of changing travel patterns, who will have the data she'll need to make good decisions? The answer is Uber, and the price for data products that could immediately help determine the optimal Parisian public transit investments would be (justifiably) high.
Stories like these could matter greatly for longer-term economic development prospects, particularly if there is a positive feedback loop that creates a tendency toward natural monopolies in data platform businesses. It's easy to see how this could happen, and hard to see precisely why the process would slow down or reverse at any specific point. The more data that machine-learning companies absorb, the faster the improvement in the algorithms that transform raw materials into value-added data products. The better the data products, the higher the penetration of those products into markets around the world. And since data products generate more data as they are used, the greater the character of data imbalance would become over time. More raw data moves from country X to country Y, and more data products move from the country Y back to country X, in a positive feedback loop.
This simple logic doesn't yet take account of the additional complementary growth effects that would further enable and likely accelerate the loop. Probably the most important is human capital. If the most sophisticated data products are being built in a few particular places, then it becomes much easier to attract the best data scientists and machine learning experts to those places, where their skills would then accelerate further ahead of would-be competitors in the rest of the world. Other complements (including basic research, venture capital, and other elements of the technology cluster ecosystem) would follow as well. The algorithm economy is almost the epitome of a "learn by doing" system, with spillovers and other cluster economy effects.
No positive feedback loop like this goes on forever. Machine learning systems may run into limits and diminishing marginal returns at some point. Bespoke hardware for machine learning systems may offer another way into positive feedback loops. Some machine learning technologies can become less dependent on data over time, as they create models of their environment which run in simulation and generate "data" endogenously. But none of these compensatory mechanisms is yet visible and viable enough to matter. Without a clear argument as to why, when and how positive feedback loops would diminish or reverse, there's justification for concern about natural monopolies, with real consequences for national rivalry. It's possible to imagine at the limit a vast preponderance of machine learning business being concentrated in one or a very few countries. These countries would then own the upside of data-enabled endogenous growth models. They would combine investments in human capital, innovation, and data-derived knowledge to create higher rates of economic growth, along with positive spillover effects into other sectors. In the parlance of US economist Paul Romer, these countries would be advantaged in both making and using ideas.
And they would almost certainly enjoy an even greater and more significant advantage in what Romer called "meta-ideas," which are ideas about how to support the production and transmission of other ideas. What are the best means of managing the intellectual property around algorithms? What are the most effective labor market institutions that can support the growth of algorithm-driven labor demand? Even if they don't have the same kind of exclusivity as raw data, these kinds of meta-ideas can keep the positive feedback loop going, and they are more likely to emerge in countries and societies that are already ahead in the data economy.
Put this together, and the stakes of national rivalry make a kind of unfortunate sense. What is now possible in machine learning, without yet appealing to science-fiction visions of artificial intelligence, hits directly at the sources of national power and social coherence. Powerful nations cannot afford the political or economic cost of being outside the positive feedback loop, and even a small gap behind a competing nation could turn into a technological chasm. And this is without yet addressing the military applications of machine learning advantage, which are considerable and could be decisive. A leader in autonomous vehicles, facial recognition, and predictive analytics for consumer behavior is also going to be a leader in autonomous weaponry applications and advanced battlefield artificial intelligence systems.
Technology rivalry is different from normal market competition. Rivalry invokes the power and interests of governments not simply as umpires and regulators but as stewards, principal users, direct funders, and sometimes full owners of technology. Machine learning is moving the digital environment overall closer to rivalry, with governments back at the center of the game. A notable indicator of this shift is simply the degree to which discourse around digital technology in national capitals and also in general-interest news and media has in the last few years become almost fully nationalized. Just two or three years ago, the "free and open Internet" narrative that placed governments squarely in the background was still robust (even if it was always somewhat naive). That ideology is mostly gone now, and the new narrative centers on digital technology firmly yoked to the goals of national power as seen through the eyes of governments.
That may be more historically familiar, but it is also a significant discontinuity for the Internet and the digital economy. The transformation itself sets up some thorny challenges that governments and businesses will have to navigate in the very near future. An example is "norm talk" — the notion that shared expectations and rules of the road for companies and governments in the digital environment can be identified and congealed through dialogue and negotiation. That seems unlikely at this very early stage of a new and robust rivalry, when the terms of advantage and disadvantage are still so nascent. Norm talk in more established domains has failed over less. Even though cyber conflicts have been a fixture of international relations for over two decades, the United Nations can barely get the major cyber powers to convene, much less agree on definitions (after nine years, its group of information security experts has agreed on little more than that norms should indeed be established.) Norms and rules of the road are more likely to emerge right now (if at all) through highly visible action (and restraint of action) by the most prominent and powerful of players — the US, China and the data-platform companies in each. But that suggests normative power is also becoming more concentrated in the two leaders, for whom norms serve as another way of reinforcing the positive feedback loops that keep them racing ahead of others.
The emerging rivalry landscape won't support the continuation of light-touch regulation and permission-less innovation that governments and business had carved out together as a foundation for the digital economy over the last 20 years. The freedom to develop and deploy new technologies, unless and until it is shown definitively that those technologies are dangerous, was a great formula for private sector innovation, but it is not a great formula for state-based rivalries and it has not shown itself to be a route to improved digital security. We should now expect more rapidly diverging experiments in new regulatory regimes around the world, which means additional space for countries to express their particular values in the digital economy and society, but less common market infrastructure for businesses at global scale.
This also suggests that digital geopolitics should not be seen as a layer superimposed on conventional geopolitics, but as a major geopolitical force itself that will create its own new alignments among new actors, and not only states. Concretely, if you now hold the belief (as many do) that "no one really goes to war over a cyberattack and if they do, it would be about the kinetic consequences of the attack, not about the cyber part of it," it's time to revisit that belief. Data and IP theft are now a foreign-policy problem for states, not just a business-model problem for companies to manage. The attribution of cyberattacks will focus as much on the US National Security Agency as on parastatal and criminal groups. States such as Denmark have already appointed a formal ambassador to the technology sector. Definitions of what constitutes criminal activity and who or what is a criminal are up for grabs. The boundaries are blurring along almost all the key dimensions that defined the core geopolitical alignments of the post-Cold War era, and it may just be the rise of machine learning rivalry that puts the final nail in the coffin of that old order.
Machine learning will make old jobs obsolete more quickly than it creates new ones, and the transition period to some new equilibrium will bring fundamental breakdowns and failures in labor markets, and consequently in politics.
A third significant manifestation of rivalry is the increasingly zero-sum nature of job displacement and inequality. Machine learning will make old jobs obsolete more quickly than it creates new ones, and the transition period to some new equilibrium will bring fundamental breakdowns and failures in labor markets, and consequently in politics. Many Asian countries seem to have a higher level of confidence that their societies can endure these changes, built on their experience of resilience and cohesion in the face of possibly comparable challenges (revolutionized labor markets) just a generation or so back in time with industrialization. That confidence could very well be tested by populist movements not unlike those in the US and Europe. More troubling still is the recognition that the success stories of the developing-country model (low wage manufacturing evolves toward higher value-added jobs along with capital accumulation) may now be dominated by data flows and machine learning products that make that ladder obsolete. Transnational movements of distressed labor could be a new factor — whether or not they cross borders, their ability to organize across borders would be an important part of the new security landscape.
Probably the most consequential decisions that immediately face states revolve around the status of the platform companies, whose relationships with governments, consumers, and societies need special assessment and possibly oversight and regulation. Geopolitical rivalry is coming to shape these debates as much or more than privacy, consumer welfare or other competition policy concerns. Market power and oligopoly are now an assumption in most of the world, but the mood and views around these is different in the US, Europe, and throughout Asia.
When oligopolies serve the national interest, particularly both economic growth and national security interests as governments view them, the tolerance for anti-competitive behavior in markets and politics takes on a different significance. Nobody right now refers to the platform companies as national champions; and almost nobody would think of Google and Baidu as relating to their respective home governments the way in which major defense contractors do. Technology rivalries may surprise both sides by pushing them in that direction.
Rhetoric in the public sphere around technology, particularly machine learning, has been steadily calcifying over the last several years. "Permission-less innovation," "XYZ-as-a-service," "disruption" — these terms reflect a steadfast faith in market competition and a nimble private sector that can stay one step ahead of lumbering governments. But that rhetoric no longer reflects reality. As the consequences of falling behind in machine learning take on geopolitical dimensions, governments are no longer taking a back seat. The shift from competition to rivalry at the frontiers of technology is well under way, and it is changing not only the private sector, but the ways in which nations jostle for power.
Originally published as "Data, Rivalry and Government Power: Machine Learning Is Changing Everything" in GlobalAsia on March 28, 2019. Reprinted with permission.
Steven Weber is a professor at the School of Information and faculty director of the Center for Long Term Cybersecurity.
Gabriel Nicholas is a School of Information MIMS '18 graduate and is currently a fellow at the NYU Center for Cybersecurity.
The opinions expressed in this article are the authors' own.


Zayn Malik has been dropped by long-term manager Sarah Stennett, amid claims he's "challenging to work with".
The 25-year-old singer, who first found fame as one-fifth of boyband One Direction, had been working with Sarah since 2015, but their professional relationship came to an end on Monday (16Apr18), the music mogul confirmed to Variety.
Sarah, the co-founder of management company First Access Entertainment, told the publication: "Sometimes in life you have to make extremely difficult decisions to effect positive change for everyone."
Zayn has yet to comment on the news, but sources told Variety that his refusal to tour to promote his last album Mind Of Mine, and his frequent declining of promotional opportunities had a lot to do with him and Sarah parting ways.
He is said to have had a change of heart and agreed to tour to support his upcoming sophomore album, due for release in June, but it seems his decision wasn't enough to save his relationship with Sarah. A representative for Zayn could not be reached for comment by Variety.
After taking on Zayn as a client, Sarah said that she was determined to make the young star "an important artist".
Zayn is the second name to leave First Access Entertainment in the past week, as Ellie Goulding made the decision to leave the company after 10 years. She's now with Tap Management, whose clients include Lana Del Rey and Dua Lipa.


Desirably equipped with a four-speed manual transmission, power steering, and a Becker Mexico TR radio, this 220SEb was purchased new by S.C. Pohlmann of San Francisco. Mr. Pohlman took delivery of the car in Europe in late 1961 and went on to drive it on an extended continental tour. Maintenance records reflect that the car received its first 500 mile service at G. Bergstaller & Co. in Vienna, Austria, and a 1,900 mile service at Mercedes-Benz S.A. Garage de la Frontiere in Monaco.
Later imported to California, the Mercedes-Benz received a comprehensive, fully documented restoration between 1980 and 1983 that was recognized by numerous Concours d' Elegance and marque publications. In 1991 the gorgeous coupe was the subject of a cover feature in "The Star", the official Mercedes-Benz Club of America magazine. The car also appeared in several Mercedes-Benz television commercials and attended numerous marque celebrations and concours, where it always scored 99 points or higher. The condition today remains the same, concours standard correct and pristine.
In 2008, this 220 SEb was entrusted to the experts at Mercedes-Benz Classic Center in Irvine, California, for a thorough mechanical freshening with no expenses spared. Two years later, the car was acquired by a Texas-based collector, who, in late 2010, commissioned the installation of a period-correct Behr air-conditioner with a tastefully upgraded modern compressor for superior cooling. The current owner purchased the car at auction in 2013 and has kept the car in a climate controlled collection environment with low profile carpeted and heated floors while putting limited mileage on the car and maintaining a proper servicing regime.
This 220 SEb Coupe is accompanied by the original owner's manual, a service booklet (including numerous period entries), original data cards, registration cards, copious restoration and service documentation, tool roll, first-aid kit, jack, spare assembly, and accessories. This car needs nothing is turn-key ready for show or drive.


text:
Kathleen Wells, J.D., Contributor
Host of The Kathleen Wells Show, KCAAradio.com
Professor Lawrence Davidson Discusses Egypt, the U.S., and Israel
Lawrence Davidson says, "Keep your eye on the language: When South Africa assigned rights according to race they called it apartheid. When Israel assigns rights according to religion they call it the only democracy in the Middle East."
Lawrence Davidson is a professor at West Chester University in West Chester, Pennsylvania. His academic work is centered on the history of American foreign relations with the Middle East.
Throughout his career, Davidson has informed public discourse with his critique of American foreign policy in the Middle East and has embarked on this endeavor in a way that promotes citizen awareness. Davidson analysis has centered on the reality of American conduct in the Middle East and has performed this analysis in conjunction with an awareness of the propaganda that has permeated this debate for the past 65 years. Given this analysis and focus, Davidson has become an outspoken and unflinching critic of the U.S. alliance with Israel and the Zionists' treatment of the Palestinian people.
Davidson is the author of several books. His latest, published in 2009, is Foreign Policy, Inc.: Privatizing America's National Interest. This work locates the source of U.S. foreign policy formulation in the activity of powerful lobbies rather than in the White House or State Department.
Kathleen Wells: Talk to me about the significance of the events taking place now in Egypt i.e., the protest against Mubarak/the government. What will these events - the actual protests - mean for the region in general and Israel specifically?
Lawrence Davidson: The protests in Egypt, and Tunisia as well, are very significant because they show the people of the Middle East (and perhaps beyond) what is possible. That there is power in numbers - numbers that are organized and determined. It is not easy to bring these numbers into the streets. Indeed, people can go a very long time accepting oppression. But at some point action is possible. That is what the present situation demonstrates and it is significant.
For the region it means that no dictatorship is truly secure unless its army or police are willing to shoot down their own people, and even then they risk civil war. Governments are expected to provide economic security for their people. This is a real challenge for the regimes in the Middle East because, tied as most of them are to the world markets and Western banking institutions, they cannot actually solve their economic problems. The dictatorships try to get around this predicament by creating economic security for elite (usually a ruling class plus the military) and keep the rest of the population under control through force. But Tunisia and Egypt now show that that strategy is not foolproof. These dictators are increasingly in a bind.
For Israel, the present events are deeply disturbing. Israel's leadership, from the very beginning of the state, has believed that security is a function of alliances with the West and military force in the region. They have never sought any meaningful compromises with their neighbors. Their only "friends" in the region are dictators who cooperate with Israel because they fear it and because the Americans pay them to do so. This is not a good basis for long term security. Israel's strategy of security through the application of force is now being revealed as inadequate. The country is confronted with implacable enemies in the north - an increasingly well armed Hezbollah backed by Syria and Iran. If Mubarak falls and Egypt becomes a democracy, Israel's ability to control matters to its west will be seriously weakened. The situation in Gaza will slip from its control because a popular regime in Cairo will normalize its border with Gaza. The Israeli blockade will collapse. The entire scenario also points up the fragility of the monarchy in Jordon. Israel will begin to feel as if it is surrounded by enemies once more. Yet they are so ideologically blinded that they will fail to realize that their own policies helped make it so.
Kathleen Wells: Respond to statements made from Israeli spokespersons that the protest in Egypt demonstrates that Israel is the only stable government in the Middle East and that Israel is the only real example of democracy in the region.
Lawrence Davidson: Israel is a democracy in the same sense that, say, Alabama was a democracy prior to Civil Rights. Real democracy includes a realistic level of equity under the law for all citizens. That is completely lacking in Israel where 20 percent of the population (the Israeli Arabs) are systematically discriminated against. So when Israeli leaders claim that their country is a democracy, they are simply saying that the Israeli Arabs can cast a vote. But that vote will never be able to change the inherently discriminatory system. So the vote is meaningless. The game is rigged.
There are, of course, other democracies in the region which the Israelis and their supporters conveniently forget about. Turkey is a viable democracy, especially now that the Turkish military is no longer interfering in politics. Lebanon is, in fact, more democratic than it ever was before the outmoded sectarian system imposed by the French was destroyed by civil war (That is what it took to democratize Lebanon!). And even Palestine was a democratic place before the Israelis and Americans decided that having Hamas win a free and fair election was unacceptable. So the claim that Israel is the only real democracy in the region is incorrect.
As to stability, well perhaps Israel is too stable. There are definite signs that the country is flirting with fascism. The present Knesset is passing laws that could destroy much of the Israeli left. That is not the kind of stability that is healthy for a supposed democratic country.
Kathleen Wells: General Petraeus submitted written testimony to the Senate Armed Services Committee last March which stated, "... enduring hostilities between Israel and some of its neighbors present distinct challenges to our ability to advance our interests in the area of responsibility."
Is Israel an asset or a liability to the United States? And specifically address how the characterization of asset or liability relates to policy formation.
Lawrence Davidson: General Petraeus's recent observation that the ongoing Arab-Palestinian conflict works against U.S. interests in the Middle East was simply a statement of fact. The unspoken, but clearly understood, second part of this was it works against us because of our close identification with Israel. What is so remarkable is that a high-ranking U.S. general publicly made the connection.
In my estimation the U.S. really does not behave as if it has interests in the Middle East separate from those of Israel. This can be so because our access to the oil in the Persian Gulf has been successfully separated from the issue of Israel. And that is so because the Gulf Arabs chose not to use oil as a weapon to influence our policy. That leaves the field of Middle East interests (apart from oil) wide open to Zionist lobby pressure and manipulation. So the tail (Israel) is definitely wagging the dog (U.S.) in this regard.
So is Israel an asset or a liability? Well, it is an asset to most of the representatives and senators in the Congress who get so much money and electoral support from Zionist-oriented lobbies and their members. And it is a horrible liability to the U.S. as a country in that Israeli behavior supported by America generates sheer revulsion in millions of Arabs and Muslims. But, you know, as Tip O'Neil once observed, "All politics are local." And what the members of Congress and those running the political parties are into is winning elections here in America. Lobby money greases that process. That is more important to them than hatred in the Middle East - even if that hatred can be predicted to lead to on-going terrorist actions. That is the way our politics works.
Politics News Foreign Policy Barack Obama Middle East Tunisia

redpajama_set_name: RedPajamaCommonCrawl


A recent survey by YouGov shows that the British youth overwhelmingly chooses to vote for the Labour party under Jeremy Corbyn against the Conservative party under Theresa May.
Perhaps the most interesting feature here is that the power of the Conservatives grows linearly with the age of the voters, which shows the gap between younger generations and the older ones. The younger would like to see Corbyn's socialist policies implemented, to drive UK forward against neoconservatism and neoliberalism. On the contrary, the older remain conservative and unwilling to see real changes.
We see a similar picture here with the primary elections of the Democrats in the US, where the American youth supported massively Bernie Sanders and managed to boost his power against Hillary Clinton. When the establishment saw his power grow rapidly, the DNC itself decided to get him out of the game.
Various polls in the UK show a bigger gap between Conservatives and the Labour, but all show that the gap is closing significantly as we approach the election day. Will Jeremy Corbyn manage to make the surprise, despite the war against him from the establishment and the media?
Everything shows that the British youth could bring a political earthquake in the UK that could affect significantly the political developments in Europe, despite Brexit.
Take the red pill, escape the Matrix!


Uri: The Surgical Strikes starring Vicky Kaushal and Yami Gautam released last week and has received great reviews from both audience and critics. The theatres are running houseful thanks to the powerful performance by the cast, but we suggest you better get in (the) line and watch the drama-thriller movie at a theatre near you.
Piracy is a big problem in India and the illegal downloading cause filmmakers to lose out on a lot of money, because these torrents release complete films for free. Same goes for online streaming. In fact, movies and TV shows often get leaked even before they are released. Remember the leaked 'The Spoils of War' episode of Game Of Thrones Season 7? Four people in the country got arrested for this!
So, the makers of Uri have found a hack to prevent such illegal leaks and downloads of the film in their own creative way and you won't see it coming until your torrent notifies you with a 'Download Complete'. Here is what happened when few users put the movie on download.
SPOILER ALERT: "Jab hamari army unki territory me ghus ke aatankvaadio ko maar sakti hai, toh kya hum aapke torrent me nahi ghus sakte?", is what you will hear Yami Gautam say.
When people downloaded close to 4GB of the movie, all they got was this one-minute clip with the movie's opening scene.
The filmmakers themselves released this fake clip working on a simple logic that most people would give up on the idea after downloading a file as heavy as 3.8 GB.
So, to quote Vicky, "Picture dekhiye. Garv se. Theatre mein jaa kar." See you at the movies, people. And book your tickets here but before that, here are 33 reasons why you MUST watch it right away.


If you visit participating AMC theater and show the coupon found below, you and up to three friends will get to see the movie "Begin Again" for free!
You must present the coupon. Presenting the coupon gets you up to four tickets. Coupon is only valid between August 29, 2014 and September 1, 2014. Only valid in the United States.


text:
package org.anyline.mail.util;

import org.anyline.mail.entity.Mail;
import org.anyline.util.AnylineConfig;
import org.anyline.util.BasicUtil;
import org.anyline.util.DateUtil;
import org.anyline.util.FileUtil;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import javax.mail.*;
import javax.mail.internet.InternetAddress;
import javax.mail.internet.MimeMessage;
import javax.mail.internet.MimeMultipart;
import javax.mail.internet.MimeUtility;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.UnsupportedEncodingException;
import java.util.*;

public class Pop3Util {
	private static final Logger log = LoggerFactory.getLogger(Pop3Util.class);
	private MailConfig config = null;
	private Properties props = new Properties();
	private static Hashtable<String, Pop3Util> instances = new Hashtable<String, Pop3Util>();

	public MailConfig getConfig() {
		return config;
	}

	static {
		Hashtable<String, AnylineConfig> configs = MailConfig.getInstances();
		for(String key:configs.keySet()){
			instances.put(key, getInstance(key));
		}
	}
	public static Hashtable<String, Pop3Util> getInstances(){
		return instances;
	}

	public static Pop3Util getInstance() {
		return getInstance(MailConfig.DEFAULT_INSTANCE_KEY);
	}

	public static Pop3Util getInstance(String key) {
		if (BasicUtil.isEmpty(key)) {
			key = MailConfig.DEFAULT_INSTANCE_KEY;
		}
		Pop3Util util = instances.get(key);
		if (null == util) {
			util = new Pop3Util();
			MailConfig config = MailConfig.getInstance(key);
			if(null != config) {
				util.config = config;
				util.props.put("username", config.ACCOUNT);
				util.props.put("password", config.PASSWORD);
				util.props.put("mail.store.protocol", config.PROTOCOL);
				util.props.put("mail.pop3.host", config.HOST);
				util.props.put("mail.pop3.port", config.PORT);
				instances.put(key, util);
			}
		}
		return util;
	}

	/**
	 *
	 * @param fr 发送人姓名
	 * @param to 收件人地址
	 * @param title 邮件主题
	 * @param content  邮件内容
	 * @return boolean
	 */
	public boolean send(String fr, String to, String title, String content) {
		log.warn("[send email][fr:{}][to:{}][title:{}][centent:{}]", fr, to, title, content);
		try {
			Session mailSession = Session.getDefaultInstance(props);
			Message msg = new MimeMessage(mailSession);
			msg.setFrom(new InternetAddress(config.ACCOUNT, fr));
			msg.addRecipients(Message.RecipientType.TO, InternetAddress.parse(to));
			msg.setSubject(title);
			msg.setContent(content, "text/html;charset=UTF-8");
			msg.saveChanges();
			Transport transport = mailSession.getTransport("smtp");
			transport.connect(config.HOST, config.ACCOUNT, config.PASSWORD);
			transport.sendMessage(msg, msg.getAllRecipients());
			transport.close();
		} catch (Exception e) {
			e.printStackTrace();
			return false;
		}

		return true;
	}
	public int getMailQty(){
		int qty = -1;
		Session session = Session.getInstance(props);
		Store store = null;
		Folder folder = null;
		try{
			store = session.getStore("pop3");
			store.connect(config.ACCOUNT, config.PASSWORD);
			// 收件箱
			folder = store.getFolder("INBOX");
			qty = folder.getMessageCount();
		}catch(Exception e){
			e.printStackTrace();
		}finally{
			// 释放资源
			try {
				if(null != folder){
					folder.close(true);
				}
			} catch (MessagingException e) {}
			try {
				if(null != store){
					store.close();
				}
			} catch (MessagingException e) {}
		}
		return qty;
	}
	public boolean send(String to, String title, String content) {
		return send(config.USERNAME, to, title, content);
	}

	public List<Mail> receive(int qty){
		return receive(false, false, qty);
	}
	public List<Mail> receive(boolean read, boolean delete){
		return receive(read, delete,1,-1);
	}
	public List<Mail> receive(boolean read, boolean delete, int qty){
		return receive(read, delete, 1, qty);
	}
	/**
	 * 接收邮件
	 * @param read 是否设置已读
	 * @param delete 是否删除
	 * @param fr 下标从1开始
	 * @param to -1:全部
	 * @return List
	 */
	public List<Mail> receive(boolean read, boolean delete, int fr, int to){
		List<Mail> mails = new ArrayList<Mail>();
		Session session = Session.getInstance(props);
		Store store = null;
		Folder folder = null;
		try{
			store = session.getStore("pop3");
			store.connect(config.ACCOUNT, config.PASSWORD);
			// 收件箱
			folder = store.getFolder("INBOX");
			folder.open(Folder.READ_WRITE);
			// 得到收件箱中的所有邮件,并解析
			int cnt = folder.getMessageCount();
			if(to == -1 || to > cnt){
				to = cnt;
			}
			if(fr == 0){
				fr = 1;
				to = to +1;
			}
			if(to >cnt){
				to = cnt;
			}
			Message[] messages = folder.getMessages(fr, to);
			mails = parse(read, delete, messages);
		}catch(Exception e){
			e.printStackTrace();
		}finally{
			// 释放资源
			try {
				if(null != folder){
					folder.close(true);
				}
			} catch (MessagingException e) {}
			try {
				if(null != store){
					store.close();
				}
			} catch (MessagingException e) {}
		}
		return mails;
	}

	/**
	 * 解析邮件
	 * @param setRead setRead
	 * @param delete delete
	 * @param messages   要解析的邮件列表
	 * @return List
	 */
	public List<Mail> parse( boolean setRead, boolean delete, Message... messages){
		List<Mail> mails = new ArrayList<Mail>();
		try{
		for (Message item:messages) {
			Mail mail = new Mail();
			MimeMessage msg = (MimeMessage) item;
			Date sendTime = msg.getSentDate();
			Date receiveTime = msg.getReceivedDate();
			String subject = msg.getSubject();
			boolean isSeen = isSeen(msg);
			boolean isContainerAttachment = isContainAttachment(msg);
			log.info("[解析邮件][subject:{}][发送时间:{}][是否已读:{}][是否包含附件:{}]",subject,DateUtil.format(sendTime),isSeen,isContainerAttachment);
			mail.setSubject(subject);
			mail.setSendTime(sendTime);
			mail.setReceiveTime(receiveTime);
			if(config.AUTO_DOWNLOAD_ATTACHMENT){
				if (isContainerAttachment) {
					String dir = config.ATTACHMENT_DIR.replace("${ymd}", DateUtil.format(sendTime,"yyyyMMdd"));
					List<File> attachments = downloadAttachment(msg, dir , sendTime, null);
					mail.setAttachments(attachments);
				}
			}
			if(!isSeen && setRead){
				seen(msg);
			}
			if(delete){
				delete(msg);
			}
			mails.add(mail);
		}
		}catch(Exception e){
			e.printStackTrace();
		}
		return mails;
	}

    /**
     * 删除邮件
     * @param messages  messages
     */
    public static void delete(Message ...messages){
        for (int i = 0, count = messages.length; i < count; i++) {
            Message message = messages[i];
            String subject;
			try {
				subject = message.getSubject();
	            message.setFlag(Flags.Flag.DELETED, true);
	            log.warn("[删除邮件][subject:{}]",subject);
			} catch (MessagingException e) {
				e.printStackTrace();
			}
        }
    }

    /**
     * 标记为已读
     * @param messages  messages
     */
    public static void seen(Message ...messages) {
        for (int i = 0, count = messages.length; i < count; i++) {
            Message message = messages[i];
            String subject;
			try {
				subject = message.getSubject();
	            message.setFlag(Flags.Flag.SEEN, true);
	            log.warn("[标记为已读][subject:{}]",subject);
			} catch (MessagingException e) {
				e.printStackTrace();
			}
        }
    }
    /**
     * 获得邮件主题
     * @param msg 邮件内容
     * @return 解码后的邮件主题
     * @throws UnsupportedEncodingException UnsupportedEncodingException
     * @throws MessagingException MessagingException
     */
    public static String getSubject(MimeMessage msg) throws UnsupportedEncodingException, MessagingException {
        return MimeUtility.decodeText(msg.getSubject());
    }

    /**
     * 获得邮件发件人
     * @param msg 邮件内容
     * @return 姓名 <Email地址>
     */
    public static String getFrom(MimeMessage msg){
        String from = "";
        Address[] froms;
		try {
			froms = msg.getFrom();
	        InternetAddress address = (InternetAddress) froms[0];
	        String person = address.getPersonal();
	        if (person != null) {
	            person = MimeUtility.decodeText(person) + " ";
	        } else {
	            person = "";
	        }
	        from = person + "<" + address.getAddress() + ">";
		} catch (Exception e) {
			e.printStackTrace();
		}
        return from;
    }

	/**
	 * 判断邮件是否已读
	 *
	 * @param msg   邮件内容
	 * @return 如果邮件已读返回true,否则返回false
	 */
	public static boolean isSeen(MimeMessage msg){
		try {
			return msg.getFlags().contains(Flags.Flag.SEEN);
		} catch (MessagingException e) {
			e.printStackTrace();
		}
		return false;
	}

	/**
	 * 判断邮件中是否包含附件
	 *
	 * @param part part
	 * @return 邮件中存在附件返回true,不存在返回false
	 * @throws MessagingException MessagingException
	 * @throws IOException IOException
	 * @return boolean
	 */
	public static boolean isContainAttachment(Part part) throws MessagingException, IOException {
		boolean flag = false;
		if (part.isMimeType("multipart/*")) {
			MimeMultipart multipart = (MimeMultipart) part.getContent();
			int partCount = multipart.getCount();
			for (int i = 0; i < partCount; i++) {
				BodyPart bodyPart = multipart.getBodyPart(i);
				String disp = bodyPart.getDisposition();
				if (disp != null
						&& (disp.equalsIgnoreCase(Part.ATTACHMENT) || disp
								.equalsIgnoreCase(Part.INLINE))) {
					flag = true;
				} else if (bodyPart.isMimeType("multipart/*")) {
					flag = isContainAttachment(bodyPart);
				} else {
					String contentType = bodyPart.getContentType();
					if (contentType.indexOf("application") != -1) {
						flag = true;
					}

					if (contentType.indexOf("name") != -1) {
						flag = true;
					}
				}

				if (flag)
					break;
			}
		} else if (part.isMimeType("message/rfc822")) {
			flag = isContainAttachment((Part) part.getContent());
		}
		return flag;
	}

	/**
	 * 保存附件
	 *
	 * @param part  邮件中多个组合体中的其中一个组合体
	 * @param dir  附件保存目录
	 * @param sendTime sendTime
	 * @param files files
	 * @throws UnsupportedEncodingException UnsupportedEncodingException
	 * @throws MessagingException MessagingException
	 * @throws FileNotFoundException FileNotFoundException
	 * @throws IOException  IOException
	 * @return List
	 */

	public static List<File> downloadAttachment(Part part, String dir, Date sendTime, List<File> files) throws UnsupportedEncodingException, MessagingException, FileNotFoundException, IOException {
		if (BasicUtil.isEmpty(files)) {
			files = new ArrayList<File>();
		}
		dir = dir.replace("${send_date}", DateUtil.format(sendTime,"yyyyMMdd"));
		dir = dir.replace("${send_time}", DateUtil.format(sendTime,"yyyyMMddhhmmss"));
		if (part.isMimeType("multipart/*")) {
			Multipart multipart = (Multipart) part.getContent(); // 复杂体邮件
			int partCount = multipart.getCount();
			for (int i = 0; i < partCount; i++) {
				boolean result = false;
				BodyPart bodyPart = multipart.getBodyPart(i);
				String disp = bodyPart.getDisposition();
				String name = decode(bodyPart.getFileName());
				String path = null;
				if(dir.contains("${file}")){
					path = dir.replace("${file}", name);
				}else{
					path = FileUtil.merge(dir, name);
				}
				File file =  new File(path);
				if (BasicUtil.isNotEmpty(name) && disp != null && (disp.equalsIgnoreCase(Part.ATTACHMENT) || disp.equalsIgnoreCase(Part.INLINE))) {
					result = FileUtil.save(bodyPart.getInputStream(), file);
				} else if (bodyPart.isMimeType("multipart/*")) {
					downloadAttachment(bodyPart, dir, sendTime, files);
				} else if(BasicUtil.isNotEmpty(name)){
					String contentType = bodyPart.getContentType();
					if (contentType.indexOf("name") != -1 || contentType.indexOf("application") != -1) {
						result = FileUtil.save(bodyPart.getInputStream(), file);
					}
				}
				if (result) {
					files.add(file);
				}
			}
		} else if (part.isMimeType("message/rfc822")) {
			downloadAttachment((Part) part.getContent(), dir, sendTime, files);
		}
		return files;
	}

	/**
     * 文本解码
     * @param text 解码MimeUtility.encodeText(String text)方法编码后的文本
     * @return 解码后的文本
     * @throws UnsupportedEncodingException   UnsupportedEncodingException
     */
    public static String decode(String text) throws UnsupportedEncodingException {
        if (text == null || "".equals(text)) {
            return "";
        } else {
            return MimeUtility.decodeText(text);
        }
    }
}

redpajama_set_name: RedPajamaGithub


text:
1994, a small town in central Scotland. Best mates Johnno and Spanner, despite being total opposites, have a deep bond. Now on the cusp of adulthood, life is destined to take them in different directions – Johnno's family are moving him to a new town and a better life, leaving Spanner behind to face a precarious future. But this summer is going to be different for them, and for the country. The explosion of the free party scene and the largest counter-cultural youth movement in recent history is happening across the UK.
Director: Brian Welsh
Actors: Amy Manson, Cristian Ortega, Gemma McElhinney, Laura Fraser, Lorn Macdonald, Rachel Jackson, Stephen McCole
Debbie Taylor is a former 1980s pop star bent on making a comeback and returning to the Billboard charts. As she prepares to once again take the music industry by…
Genre: Drama, Family, TV Movie
Hello Destroyer
A young junior hockey player's life is shattered by an in-game act of violence. In an instant his life is abruptly turned upside down; torn from the fraternity of the…
Andrea Marr is a bright, straight-A, mature, 18-year-old high school senior on the verge of womanhood who decides to abandon her sheltered, boring lifestyle and her bookish friend Darcy for…
Genre: Comedy, Drama, Music, Romance
Joel Barish, heartbroken that his girlfriend underwent a procedure to erase him from her memory, decides to do the same. However, as he watches his memories of her fade away,…
The Illusionist
With his eye on a lovely aristocrat, a gifted illusionist named Eisenheim uses his powers to win her away from her betrothed, a crowned prince. But Eisenheim's scheme creates tumult…
Country: Czech Republic, USA
Genre: Drama, Fantasy, Romance, Thriller
Tiger Orange
In the small Central California town where they grew up, two estranged gay brothers struggle to reconnect after the recent death of their father.
The Grand Budapest Hotel tells of a legendary concierge at a famous European hotel between the wars and his friendship with a young employee who becomes his trusted protégé. The…
Outlaws and Angels
A gang of cold-blooded outlaws narrowly escapes a blood-soaked bank robbery in a grimy frontier town. With a notorious bounty hunter hot on their trail, these nefarious criminals desperately need…
Genre: Drama, Thriller, Western
They Call Me Jeeg Robot
Enzo Ceccotti comes into contact with a radioactive substance, then accidently discovers he has superpowers. A touchy, navel-gazing introvert, he's sure his new capabilities will do wonders for his life…
Genre: Action, Comedy, Drama, Science Fiction, Thriller
Marie's Story
Marie Heurtin is born both blind and deaf. Sister Marguerette wins her trust and teaches her how to express herself.
Low Fidelity
A dramedy about relationships and fidelity, or the lack thereof. A group of old high school friends, now in their late thirties, get together for the weekend to celebrate the…
Guns of the Magnificent Seven
In this third remake of legendary Japanese director Akira Kurosawa's hugely influential The Seven Samurai, the seven gunslingers (George Kennedy, Michael Ansara, Joe Don Baker, Bernie Casey, Monte Markham, Fernando…
Genre: Action, Adventure, Drama, Western
Trailer: Beats


text:
High School Musical 2 — саундтрек к фильму Классный мюзикл: Каникулы. Это второй самый продаваемый сингл 2007 года после альбома Джоша Гробана Noël в США.

Дебютировав 1 строкой в чарте Billboard 200, , Amazon.com и iTunes Store продали альбом 615,000 копиями на первой неделе продаж. В начале сентября 2007 это число дошло до четвёртого места самых больших продаж на первой недели в год. Это первый саундтрек с телефильма, который дебютировал на верхушке Billboard. Альбом также распродался дважды платиновыми (2,000,000) копиями в США на первой неделе релиза. В начале декабря 2007 альбом разошёлся 3 миллионами копиями в США и больше, чем 5 миллионами в мировом масштабе.

«Wal-Mart Exclusive» альбома был выпущен 14 августа 2007, и состоял из оригинального саундтрека (хотя и в немного другом порядке) и дополнительного DVD, который, по-видимому, состоит из большинства (если не из всех) эпизодов "Road to High School Musical. The «2-Disc Collector's Edition», версии альбома, выпущенной в Сингапуре 3 декабря 2007 года.

Список композиций

Wal-Mart Exclusive: Классный Мюзикл: Каникулы 2-х дисковый коллекционный саундтрек
На ограниченный срок розничная сеть Wal-Mart продавала только выпущенное эксклюзивное двух-дисковое коллекционное издание Классный Мюзикл: Каникулы. Оно включает саундтрек и бонус DVD. Коллекционное издание сейчас доступно на Филиппинах в то же время, когда и вышел саундтрек  Классный Мюзикл: Выпускной  после того, как Universal Music Limited обновил лицензию Walt Disney Records в выше указанной стране. Он включает:

Диск 2

Бонус DVD с:
 С эксклюзивным материалом об отборе актёров и прослушивания.
(Время прогона: 45 минут)' Автографами актёров Классный Мюзикл: Каникулы Специальная упаковка из фольги с специально вложенным буклетом со словами

 Примечания
 * Олеся Рулин принимала участие в исполнении «You Are the Music In Me», но её имя не включено в титры.
 Лукас Грейбил записал песню «You Got It», которая играет в фильме. Песня играла, когда Шарпей и Райан знакомятся в сельском клубе. Песню можно купить на iTunes. Однако, она никогда не была выпущена физически. Песня была впервые услышана на странице MySpace Лукаса Грейбила, но это демо.
 18 ноября 2007, Классный Мюзикл: Каникулы был награждён «Самый Лучший Саундтрек» на 35th Annual American Music Awards.

 Подарочное издание
Подарочное издание Классный Мюзикл: Полная Коллекция был выпущен 20 ноября 2007. Он включает 6 дисков. Они включают оригинальный саундтрек Классный Мюзикл, Классный Мюзикл: Каникулы оригинальный саундтрек, Классный Мюзикл Караоке Vol. 1, Классный Мюзикл: Каникулы Караоке Vol. 2 и Классный Мюзикл: Концерт CD/DVD.

 «Классный Мюзикл: Каникулы»: Непрекращающаяся Танцевальная Вечеринка

Walt Disney Records выпустил альбом-ремикс треков Классный Мюзикл. Он был выпущен 26 декабря 2007 года в США и 24 декабря 2007 года в Великобритании и Южно-восточной Азии. На все песни сделаны ремиксы Джейсоном Невисом. «Классный Мюзикл: Каникулы»: Непрекращающаяся Танцевальная Вечеринка достигла 1 строки американском чарте Top Electronic Albums в январе 2008.

 Появления в чарте

Альбом был самым скачиваемым альбомом на iTunes и Amazon.com на первой неделе релиза, и оставался на следующей неделе.

Альбом дебютировал 1 строкой в американском . Billboard 200 с продажами 615,000 копий, став четвёртым по продажам на первой недели в 2007 году (следом за Minutes Minutes to Midnight группы Linkin Park, Curtis рэпера 50 Cent и Graduation Канье Уэста). Издание также имело самые большие продажи на первой неделе за телевизионный саундтрек. Он оставался на 1 строке до 4-х недель, продав 367,000 копий на второй неделе, 210,000 на третьей и 165,000 на четвёртой.Jonathan Cohen, «'High School Musical 2' Starts Third Week At No. 1» , Billboard.com. 5 сентября 2007. Саундтрек — это первый альбом за предшествующие 2 года, который провел 4 недели подряд на 1 строке в Billboard 200.

После проведения 4 недель подряд на 1 строке в Billboard 200, альбом скатился до 4 строки, идя после рэпера 50 Cent с Curtis, Канье Уэста с Graduation и Кенни Чесни с Just Who I Am: Poets & Pirates.

На 15 неделе в Billboard 200, в ноябре 2007 High School Musical 2 вернулся в топ-10 с продажами, выросшими на 130 % (183,000 копий), выдвинув его на 6 строку самых продаваемых альбомов 2007 года, во главе с Daughtry. Месяц спустя, однако, рождественский альбом Джоша Гробана Noël вытеснил Классный Мюзикл: Каникулы, став самым продаваемым альбомом года.

* В Великобритании сборники из нескольких артистов не попали в чарт Top 200 Artist Albums''.

«Классный Мюзикл: Каникулы»: Версия хинди

Times Music из Индии запустил специальный 2-дисковый саундтрек на хинди с оригинального саундтрека «Классный Мюзикл: Каникулы». Он состоит из дополнительного специального диска с тремя специальными вдохновленными песнями от известного музыкального режиссёрского трио Shankar Ehsaan Loy. Они включают «All for One» («Aaaja Nachle»), «Ud Chale» and «Chhoti Si». Эти песни были также ремиксованы ДиДжеем Suketu и аранжированы Aks. Саундтрек был выпущен (коллекцией на 2-х дисках) 26 октября 2007 года, а фильм (дублированный на хинди был выпущен на Disney Channel India 7 декабря 2007. 2 клипа с специального диска вышли в эфир на Disney Channel India. Это Ud Chale и «All for One» («Aaja Nachle»). В клипе Ud Chale 3 друзей вместе исследуют небо. В All for One толпа людей переносит свои эмоции в танец.

Примечания

Ссылки

Саундтреки 2007 года
Классный мюзикл
Альбомы, возглавлявшие Billboard 200
Альбомы, возглавлявшие Canadian Albums
Альбомы, сертифицированные как мультиплатиновые Американской ассоциацией звукозаписывающих компаний

redpajama_set_name: RedPajamaWikipedia