text:
Paris The City of Undimmed Light
Paris is more vibrant than ever. With a typical Gallic shrug, Parisians have gotten over the terrorist attacks
By James Greer
Most Parisians hate Paris. They complain about the weather, the traffic, the pollution, the dirt, the stress, everything. Mostly the weather. They're inured to its charms and think people who goggle at Belle Époque buildings and hustle through museums are idiots. Given the chance they'd move to Bel Air or Buenos Aires or Barcelona in a heartbeat.
For the most part they're right. The Prado in Madrid is a better museum than the Louvre. Chartres is more impressive than Notre Dame. Milan is more stylish. The weather really is cold and damp and gray most of the time. Even the food isn't as good as it used to be — these days to most Parisians "la gastro" refers to the inevitable yearly outbreak of violent stomach flu and not to anything conventionally gastronomic. But these uncomfortable facts are irrelevant to the Paris that matters to most of us — an imaginary Paris, a Paris of the mind, in which Picasso gambols with Cocteau backstage at a Diaghilev production of a Stravinsky ballet. A Paris that never existed, where art and music and film and literature and fashion and romance commingle in smoke-ringed bliss in dingy basement bars; where wild-eyed poets freeze in garrets, drink absinthe and die a thousand times over for their art. An idea of Paris, rather than a prosaic place.
It's the idea of Paris that a gang of drugged-up thugs tried to destroy nearly two years ago, on Friday, November 13th, 2015. The story of the attacks is as well-known as it is horrific, and requires no synopsis here. The attacks were coordinated and wide-spread within the city. People died eating, drinking, smoking, living. There were the usual hope-sustaining acts of heroism. There was blood and gore and death. There was fear. There was defiance. There was, and still is, the lasting sadness that's the byproduct of inexplicable violence.
The attack people remember most clearly is the one that took place at the Bataclan in the 11th arrondissement. You know the story. The Eagles of Death Metal were playing to a packed house — the Bataclan holds about 1500 people — when three men with AKM assault rifles entered, took up positions in the mezzanine, and began shooting. When they were done, and dead, by their own hand or by police bullets, 89 people lay dead on the floor of the Bataclan, with another 350 or so injured. The full horror of the scene is unimaginable to anyone who wasn't there.
Crime scene: The Bataclan on a more peaceful day
One way of dealing with the unimaginable is to ignore it. A year and three quarters on from the November attacks, it's hard to find anyone in Paris who brings them up unprompted. Completely understandable: after you've processed your grief, you don't want to talk about tragedy unless you have to. On the first anniversary, the mood in the city was a kind of defiant fatalism, which is scarcely distinguishable from the famous Gallic shrug. If you didn't know what had happened a year earlier, you wouldn't know (except for a few hollow official ceremonies held for the benefit of a government whose response to the attacks has ranged from incompetent to Orwellian). It's not that Parisians are possessed of any special powers of composure. It's that Parisians are human beings, and human beings, all of us, are built to survive. When I bring up the attacks, particularly at the Bataclan, a hitherto unremarkable rock club where thousands of bands had played to typically boisterous crowds, everyone has a story. Everyone knows someone who was there, or was supposed to be there themself, or prevented someone else from going there by sheer luck. The nature of horror is that, unlike justice, it's impartial.
I have a tenuous personal connection to the Bataclan. In 1995 a band I was in opened for the Foo Fighters and Beck there. At the time, I was afflicted with panic attacks every time we played, and one of the ways I dealt with my anxiety was to scope the exits before we went on, in case the need to escape overwhelmed the need not to seem like a crazy person during our set. So I know that there is an exit to the street just a few feet past stage right at the Bataclan, and I'm almost certain that that stage right exit is how most of the Eagles of Death Metal (and those fortunate fans and crew that were able to follow them) got out. I've played thousands of shows over the years, and I tend not to remember the names or salient characteristics of any of the venues I've played. But I remembered that exit at the Bataclan, because it was burned into my brain. And now it's burned into my brain for a different, terrible, reason.
I was back in Paris almost exactly a year after the November attacks because I'm in another band, and we were playing in Paris, as most bands who tour Europe have done and still do. I'd already played there in February of 2017, and noticed no particular tension, but we were playing a small basement club and not the Bataclan, so I'm sure if the idea had crossed anyone's mind (it didn't cross mine, neither at the time nor later), it would have been dismissed: we're simply too small and insignificant a target. Which didn't prevent my mother from begging me not to tour Europe this past winter — there had been other incidents, and because she mostly gets her news from American cable networks, her view of Europe — not just Paris, not just France, the whole continent — is that it's a place where people blow themselves and each other up for sport on holidays. I brushed off her concerns — we were far more likely to face danger on the Autobahn than in any concert venue — but there were small signs (border stops where there didn't used to be borders, more requests for my passport at hotels) that not everything was the way it used to be.
An ancient gargoyle keeps watch over modern Paris***Pedro Lastra***
When the attacks happened, like many people I immediately texted or emailed my friends in Paris to find out if they were safe. Everyone I knew and everyone they knew was safe, but their responses varied in tone from scared shitless to defiant. My friend the cinematographer Renato Berta emailed the next day that he spent a "terrifying night," but worried that the days following would be similarly terrifying, but for a different reason — "all this," he said, "is good news for Marine Le Pen" (Leader of the Front National, the far-right nativist French party that had been gaining steady support over the past few years in the face of growing fears over immigration and 'what it means to be French.' See: every other country in the world.) A photographer friend wrote that it had been difficult to sleep the night of the attacks and that she was very sad and shocked, which was more typical of the responses I got. A lot of these people were responding to dozens of texts and emails from friends both in Paris and around the world, so their responses were brief but emotional.
Some of those same friends told more expansive stories about what happened that night: "I saved four people's lives that night, because I was lazy," my friend Eglantine tells me, with offhand candor. "They wanted to meet me at Le Carillon," where attackers shot into the crowd, killing fifteen. "But I said, no, if you go there it's too far from my apartment, come somewhere closer instead, and they did. If not, they'd probably be dead. But we were in the restaurant talking, we didn't know anything had happened, and all of a sudden everyone started getting texts from lots of people, friends and family, some from overseas, asking if we were okay, and I said 'We should probably check the news, guys, I think something happened.'"
"I was asleep," says another friend, Constance, flatly. For her the attacks were more personal, because she grew up two doors down from the Bataclan. The neighborhood is thus a part of her, and it's a part she now has no wish to re-visit. About a month before I arrived in Paris, it was announced that the renovated Bataclan would re-open with a concert by Sting (as if these people haven't suffered enough!). Most Parisians seemed to think the reopening was a good idea, part of a healing process, and that if the Bataclan had simply closed its doors for good "the terrorists would win," ignoring the fact that terrorists never win. But for Constance the Bataclan was "a house of death," and she couldn't understand how anyone could go there ever again.
"Especially to see Sting," I offer.
"Especially to see Sting. But I wouldn't go there to see anyone. I wouldn't. Not to a place haunted by so much suffering and death and blood."
I take her point. I'm agnostic on the subject of the Bataclan. For me, it's just another concert venue, and if offered the chance to play there again, I probably would, without a second thought. I don't believe that in doing so I'd be striking a blow against terrorism, but I'm also not about to let a bunch of drug-addicted maniacs dictate where my band can play. If I wanted that I'd sign with a record label again.
***Getty Images***
The problem with most acts of terror is the same as with most attempts to eradicate acts of terror. It's too fucking easy, and it doesn't work. You can kill people like snapping twigs, and you can bomb the hell out of a desert enclave until it looks like the moon, but these things never accomplish their intended goals (however fuzzy and ill-conceived those goals might be) and the consequences are usually worse and more unpredictable than anyone could have imagined. People should just stop treating each other like inanimate objects and just be kind to everyone, but that would require an act of imagination that is currently beyond humankind's abilities, or at least its will.
We are capable of great things. We are capable of creating a vision of Paris that inspires writers, artists, filmmakers, and Woody Allen. There's no reason we can't create a vision of the world that's inclusive, open, loving, and inspiring. But we haven't done it yet, and the way things are going lately you'd be forgiven for indulging in a little recreational despair.
The counterbalance — and there's always a counterbalance — is to look at Paris without the Proust-tinted glasses, to see it as it is, as a modern city beset with all the problems of a modern city, and dealing just as poorly with them as every other modern city does, a place where the weather is always damp and gray and cold, and the food isn't really that good, and the museums are graveyards and the graveyards museums, and the modern and the post-modern abut the Gothic and the Romanesque in a way that doesn't really work and never will, and Haussmann's famous boulevards are monuments to pre-fascism, and anti-Semitism is still and probably always will be as rampant as it was in the days of Dreyfuss; all of that, and much, much worse. And yet… after suffering one of the most devastating attacks in recent memory, the city — that city, the hugely imperfect one, not the City of Light but the city of lighters (everyone in Paris still smokes, it's disgusting) — continues to pulse, to thrive, to attract starry-eyed tourists from everywhere in the world who believe that putting a padlock on the railings of a bridge over the Seine is a lasting sign of true love (even after the padlocks have been removed and sold off and melted down); to bloom in the imagination of writers and artists and filmmakers and Woody Allen as an idealized example of what the human imagination can achieve when it is unrestricted and volitional. And to see that nothing, no matter how inhumane or horrifying, can reduce or impair that vision, as long as it remains clear-eyed and free of nostalgia. It is an attractive but dangerous fallacy to look at the past and say, "That was better." It wasn't. It never was. You are, right now, at the apex of creation, and neither you nor I nor any preacher or philosopher or poet knows what will happen next. No bomb can destroy the future, and guns can only kill. If Paris holds any lesson for us, it's that change is the most powerful weapon in the world.
10 Best Relais & Chateaux in France
GO AWAY! QUITO, ECUADOR
Is Copenhagen the Coolest City in the World?
Marseille, among many glorious things, is the land of soap!
***Álvaro/flickr***


Well almost two months since my last post and not much progress to report.
Most of my time has been devoted to coordinating improvements to my house.
and new interior wall paint.
Thankfully we're in the home stretch so hope to see a return to normalcy in the near future.
puttying and sanding, more priming, and more sanding, she's got a coat of white primer on her now.
Here she is just after spraying with Testors matte white enamel.
at this point, if you pulled a Mr Burns "Hop in!"
1/1 house model. I get that.
After the yellow coats have dried and been lightly sanded she'll get her final coats of Italian Red.
Thanks for reading and sticking with me for all these months everyone!
Wow, a year in now. This has been a spectacular build. Can't wait to see the finished product.


Find local bargains in and near Fourpenny (Highland).
The listings below are an automated feed from Ebay for the village "Fourpenny".
View more listed items with "Fourpenny" in the title. (Problem with any of these listings? Report it to us here).


text:
Sebastian Joseph Lettman
Recommend Sebastian's obituary to your friends
Plant a tree in memory of Sebastian
Obituary of Sebastian Joseph Lettman
Please share a memory of Sebastian to include in a keepsake book for family and friends.
Smethport - Sebastian Joseph Lettman, 13, of Crosby, formerly of West Grove, PA, passed away suddenly Tuesday (April 27, 2021) at Oishei Children's Hospital, Buffalo, NY to be with our Heavenly Father.
He was born August 8, 2007 in Chicago, Illinois to his mother, Laura Elizabeth Wells, a grandson of Gary F. and Marie R. Lettman, both of Crosby, PA, formerly of West Grove, PA, who raised him to be the happy and caring young man that he was.
Sebastian attended school in Smethport, where he was currently enrolled in the seventh grade class and where he made many dear friends with both fellow students and faculty.
He enjoyed helping and volunteering at the Norwich Township Fire Department for their Bingo program, but especially for the food and friendship! He loved playing his Xbox online with his friends and his long-distanced brother, Antonio, watching cooking and wildlife shows or cartoons. Frequently, he could be found riding his bike with his cousins, Alexis (Lexi) and Cody Hannan or sledding, often without shoes and socks - even in the snow! Sebastian was currently learning to master the fishing sport with his Great-Uncle Steve and had big fishing plans for this coming season. He enjoyed the outdoors, kicking around a soccer ball or swimming in the farm pond, although farm chores would often wait and would sometimes be done in his teenage timeframe . . . or perhaps even forgotten as he was on to other, more important and interesting things to do.
He truly cared about people and their feelings and always wanted to be everyone's friend, entertaining classmates, sometimes to the chagrin of his teachers during class time or standing up and talking on his school bus rides. Sebastian was bursting with life in his short time here - whether showing you a funny video, a new level on the Xbox, talking about some random fact or telling you a joke with a smile that we will always remember and cherish.
Sebastian would have been the gentleman he was aspiring to be and had intentions of following his grandfather, great-uncles and brother into military service, however, it was to be the Navy for him as he always created his own path.
In addition to his grandparents, Sebastian is survived by:
His Great-Grandmother (GG-ma) Mary T. Tader of Indiana, several Great-Uncles and Great- Aunts, his Aunt Christina Hannan (William Bigley) of Crosby, PA, Uncles John Lettman (Samantha Myrla) of Pittsburgh, PA and Kevin T. Hannan of Port Allegany, PA, Cousins, Alexis M. and Cody J. Hannan of Crosby, PA, as well as Three brothers: Antonio Lettman of Crosby, PA, David and Alex Lynch, both of Las Vegas, NV.
He was preceded in death by his Great-Grandfather, Otto P. Tader and Great-Grandmother Sybil Ernestine McGuire.
The family also wishes to thank the members of the Norwich Township and Smethport Volunteer Fire Departments, Phoenix EMS, the doctors and nurses at Oishei Children's Hospital, Pennsylvania State Police, MedEvac, American Red Cross, The Bigley Family and the community at large who have shown their professionalism, love, caring and support during this most difficult time.
A social gathering for friends in Sebastian's memory will be held on Tuesday, May 4, 2021 at 6 PM in the Norwich Twp. Fire Hall, Crosby.
Memorials, if desired, may be made to the Norwich Twp. Fire Dept. of Crosby, PA. Online condolences may be made at www.hartle-tarboxfuneralhomes.com.
A Memorial Tree was planted for Sebastian
Sebastian Lettman

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: join arrays every x elements without a loop - python I have the following arrays:
from mxnet import nd

A=nd.array([[1,1,1,1],[2,2,2,2]])
B=nd.array([[11,11,11,11],[22,22,22,22]])
Y=nd.array([[91,91,91,91],[92,92,92,92]])

Imagine that each list whithin each array corresponds to a client.
So [1,1,1,1] is the result of operation A to client 1 and [2,2,2,2] is the result of operation A to client 2.
Then I have another array with a diferent operation that is applied to all the clients. [11,11,11,11] is the result of operation B to client 1 and so on.
And I need to get the following result:
D=nd.array( [ [[1,1,1,1],[11,11,11,11]],[[2,2,2,2],[22,22,22,22]] ])
list([D,Y])

This returns:
[
 [[[ 1.  1.  1.  1.]
   [11. 11. 11. 11.]]

  [[ 2.  2.  2.  2.]
   [22. 22. 22. 22.]]]
 <NDArray 2x2x4 @cpu(0)>,
 [[91. 91. 91. 91.]
  [92. 92. 92. 92.]]
 <NDArray 2x4 @cpu(0)>]

As you can see, the operations (A and B) are grouped for each client.
I tried:
list([list(zip(A,B)),Y])

And I get:
  [[(
    [1. 1. 1. 1.]
    <NDArray 4 @cpu(0)>,
    [11. 11. 11. 11.]
    <NDArray 4 @cpu(0)>), (
    [2. 2. 2. 2.]
    <NDArray 4 @cpu(0)>,
    [22. 22. 22. 22.]
    <NDArray 4 @cpu(0)>)],
    [[91. 91. 91. 91.]
     [92. 92. 92. 92.]]
    <NDArray 2x4 @cpu(0)>]

Which is not what I need. Plus, arrays A and B are really big, so I don't want to use a loop or something that will take too long.
Thanks.

A: this is typically an operation you can do with an mxnet.ndarray.concat, yet you need to expand the dimension of the concatenated items before the concat so that they stay in separate arrays.
This command will get exactly the output you ask for:
C = nd.concat(A.expand_dims(axis=1), B.expand_dims(axis=1), dim=1)

print(C)

which returns:
[[[ 1.  1.  1.  1.]
  [11. 11. 11. 11.]]

 [[ 2.  2.  2.  2.]
  [22. 22. 22. 22.]]]
<NDArray 2x2x4 @cpu(0)>

redpajama_set_name: RedPajamaStackExchange


text:
\section{Introduction}
Trends and influence in social media are mediated by the individual behavior of users and organizations embedded in a follower/subscription network. The social media network structure differs from a friendship network in that users are allowed to \textit{follow} any other user and follower links are not necessarily bi-directional. While a link enables a possible influence channel, it is not always an active entity, since a follower is not necessarily interested in all of the content that a \textit{followee} posts. Furthermore, two individuals are likely to regard the same token of information differently. Understanding how information spreads and which links are active requires characterizing the users' individual behavior, and thus going beyond the static network structure. A natural question then arises: \textit{Are social media users consistent in their interest and susceptibility to certain topics?}

In this work, we answer the above question by demonstrating a persistent topic-specific behavior in real-world social media. We propose a user model, termed \textit{genotype}, that summarizes a user's topic-specific footprint in the information dissemination process, based on empirical data. The social media genotype, similar to a biological genotype, captures unique user traits and variations in different genes (topics). Within the genotype model, a node becomes an individual represented by a set of unique invariant properties.

For our particular analysis, the genotypes summarize the propensity and activity level in adoption, transformation, and propagation of information within the context of different topics. We propose a specific set of properties based on adopting topic-specific Twitter hashtags---tokens that annotate messages and allow users to participate in global discussions~\cite{Tsur2012}. The model, however, applies to more general settings capturing, for example, dissemination of urls or sentiment-charged messages.

We construct the genome (collection of user genotypes) of a large social media dataset from Twitter, comprised of both follower structure and associated posts. The observation of stable genotypes (behavior) leads to natural further questions: \textit{Can the consistent user behavior be employed to categorize novel information based on its spread pattern? Can one utilize the genotypes and the topic-specific influence backbone to (i) predict likely adopters/influencers for new information from a known topic and (ii) improve the network utility by reducing latency of disseminated information?} We explore the potential of the genotype model to answer the above questions within the context of Twitter.

To validate the consistency of genotypes, we show that combining genotype-based classifiers into a composite (network-wide) classifier achieves accuracy of $87\%$ in predicting the topic of unobserved hashtags that spread in the network. We extract and analyze topic-specific influence backbone structures and show that they differ from the static follower network. We, then, turn to two important applications: influence prediction and topic-specific latency minimization. We achieve $20\%$ improvement in predicting influencers/adopters for novel hashtags, based on our model, as compared to relying solely on the follower structure. We also demonstrate that knowledge of individual user genotypes allows for effective reduction in the average time for information dissemination (more than 40\% reduction by modifying the behavior of 1\% of the nodes).

Our contributions, in the order they are presented, include: \textit{(i)} proposing a genotype model for social media users' behavior that enables a rich-network analysis; \textit{(ii)} validating the consistency of the individual genotype model; \textit{(iii)} quantifying the differences of behavior-based influence backbones from the static network structure in a large real-world network; and \textit{(iv)} employing genotypes and backbone structure for adopter/influencer prediction and latency minimization of information spread.

\section{Related Work}
The network structure has been central in studying influence and information dissemination in traditional social network research~\cite{Kempe2003,Kimura2010}. Compared to them, large social media systems exhibit a relatively denser follower structure, non-homogeneous participation of nodes, and topic specialization/interest of individual users. Twitter, for example, is known to be structurally different from human social networks~\cite{Kwak2010}, and the intrinsic topics of circulated hashtags are central to their adoption~\cite{Romero2011}.

A diverse body of research has been dedicated to understanding influence and information spread on networks, from theories in sociology~\cite{Friedkin2006} and epidemiology~\cite{Newman2003}, leading to empirical \textit{large-scale} studies enabled by social web systems~\cite{Romero2011,Dodds2011,Yang2011,Bandari12}.
Here, we postulate that the influence structure varies across topics~\cite{Weng2010} and is further personalized for individual node pairs. Lin and colleagues~\cite{Lin2011} also focus on topic-specific diffusion by co-learning latent topics and their evolution in online communities. The diffusion that the authors of \cite{Lin2011} predict is implicit, meaning that nodes are part of the diffusion if they use language corresponding to the latent topics. In contrast, we focus on topic-specific user genotypes and influence structures concerned with passing of observable information tokens and their temporal adoption properties.

Earlier data-centered studies have shown that sentiment~\cite{Dodds2011} and local network structure~\cite{Romero2011} have an effect on the spread of ideas. The novelty of our approach is the focus on content features to which users react. Previous content-based analyses of Tweets have adopted latent topic models~\cite{Suh2010,Ramage2010}. We tie both content and behavioral features to network individuals.

With regards to influence network structure and authoritative sources discovery, Rodriguez and colleagues~\cite{Gomez2013} were able to infer the structure and dynamics of information (influence) pathways, based on the spread of memes or keywords. Bakshy et al.~\cite{Bakshy2011} focus on Twitter influencers who are roots of large cascades and have many followers, while Pal et al~\cite{Pal2011} adopt clustering and ranking based on structural and content characteristics to discover authoritative users. Although the above works are similar to ours in that they focus on influence structures and user summaries, our genotype targets capturing the invariant user behavior and information spread within topics as a whole, involving a collection of topically related information parcels.

\section{Genotype Model}
\begin{table*}[t]
\centering
{\scriptsize
\begin{tabular}{|l|p{.41\linewidth}|p{.44\linewidth}|	} \hline
Metric & Function definition & Notes \\\hline
\textit{Time} & $\textrm{TIME}(u,h)=min_{(u,h)}(t(u,h))-min_{v\in V_u}(t(v,h))$, where $t(u,h)$ is the time $(u,h)$ occurs and $V_u$ is the set of followees of $u$. & The absolute amount of time between a users first exposure to the given hashtag and his first use of that same hashtag.\\\hline
\textit{Number of Uses}& $\textrm{N-USES}(u,h)=\left|\{(u,h)\}\right|$, where $|\cdot |$ is the cardinality function. & The total number of occurrences of the $(u,h)$ pair.\\\hline
\textit{Number of Parents} & $\textrm{N-PAR}(u,h)=\left|\{v\in V_u\;|\;t(v,h)<t(u,h)\}\right|$ & The number of followees to adopt before the given user.\\\hline
\textit{Fraction of Parents} & $\textrm{F-PAR}(u,h)= \left|\{v\in V_u \;| \;t(v,h)<t(u,h)\}\right|/\left|V_u\right|$. & The fraction of a user's followees who have adopted the hashtag prior to the user.\\\hline
\textit{Latency} & $\textrm{LAT}(u,h)= \left(\left|\{h_j\in H_{T_i}\;|\; H_{T_i}\ni h, \textrm{ and } t(u,h_j)<t(u,h)\}\right|\right)^{-1}$. & The inverse of the number of same-topic hashtags posted to the user's time-line between his first exposure to the hashtag and his first use of the hashtag.\\\hline
\textit{Log-latency} & $\textrm{LOG-LAT}(u,h)=log\left(\textrm{LAT}(u,h)/ Avg(\textrm{LAT}(w,h)\right. \textrm{s.t.} \left. w\in U)\right)$. & The logarithm of each latency value after each latency value has been divided by the mean latency value for that hashtag.\\\hline
\end{tabular}
}
\caption{Behavior-based metrics that are components of the topic-specific user genotype.}
\label{tab:metrics}
\vsa
\end{table*}
Here we define our genotype model that captures the topic-specific behavior of a single user (node) within a social media network. Our main premise is that, based on observed network behavior, we can derive a unique signature of a user. Hence, the genotype model is a user model, by definition, in the sense that it is an abstract representation of a social network user. For our analysis, this signature captures adoption and reposting of new information, activity levels, and latency of reaction to new information and influential neighbors. Although other behavior traits can be incorporated as well, we seek to summarize user behavior with respect to a set of predefined topics.

A social media network $N(U,E)$ is a set of users (nodes) $U$ and a set of follow links $E$. A directed follow link $e=(u,v),e \in E$ is connects a source user $u$ (\textit{followee}) to a destination user $v$ (\textit{follower}). The network structure determines how users get exposed to information posted by their followees. The static network does not necessarily capture influence as users do not react to all information to which they are exposed. To account for the latter, we model the behavior of individual users within the follower network within their genotypes.

In its most general form, a user's genotype $G_u$ is an entity embedded in a multi-dimensional feature space that summarizes the \textit{observable behavior} of user $u$ with respect to different topics.
It is up to the practitioner to define the different dimensions of the topic feature space, and an observable behavior in the network locality of a node. Each genotype value can be viewed as an allele that the user introduces to the process of message propagation through a network.

In our study, we focus on hashtag usage within Twitter, since hashtags are simple user-generated tokens that annotate tweets generated by either a social group or a specific social phenomenon, and are often ``learned'' from others on the social network~\cite{Tsur2012}. In this context, a hashtag serves as a genetic parcel of cultural information, just like alleles of a gene within a biological context. Hashtags can be associated with topics such that an individual's response to a collection of hashtags within a topic indicates a user's propensity to respond to other hashtags within that same topic.

We consider a set of predefined hashtags $H=\left\{h\right\}$, each associated with a topic $T_i\in T$. To obtain the genotype, we analyze the social media message (tweet) stream produced by a user $u$, with respect to $H$. Let us define $m(\cdot)$ to be a function that maps each occurrence of $(u,h)$ to a real values $m:\{(u,h)\}\mapsto \mathbf{R}$. Let $H_{(u,T_i)}:=\{h\}_{T_i} \cap \{h\}_u$, then the $i^{th}$ element of the user genotype $G_u$ is the set of $\{m(u,h)\; | \;h\in H_{(u,T_i)}\}$ values. We remark that this set of values may also be reduced to their average value or some approximated distribution function if one wishes to have a coarser representation of the data.

To construct each user's topic-genotype from empirical data, we consider a variety of metrics $m(\cdot)$ for $(u,h)$ pairs, listed in Table~\ref{tab:metrics}.
These metrics serve the purpose of quantifying a user's response to a hashtag by defining the data values that are used to estimate the topic distributions. While TIME and N-USES are intuitively obvious metric choices, LAT and LOG-LAT are novel to this manuscript. N-PAR and F-PAR have been previously studied in a different context~\cite{Romero2011}, and are included here for comparison.

\section{Datasets}
We chose Twitter to analyze user behavior via our genotype model, since Twitter has millions of active users and messages have a known source, audience, time stamp, and content. Similar analysis can be performed in other social media networks with a known follower structure and knowledge of the shared content (memes, urls and buzz words) in time.

\begin{table}[t]
\centering
{\scriptsize
\begin{tabular}{|l|c|c|c||c|c|c|} \hline
             & \multicolumn{3}{|c|}{SNAP (users=42M,tweets=467M)} & \multicolumn{3}{|c|}{CRAWL (users=9K,tweets=14.5M)} \\ \hline
 Topic       & Hashtags & Users & Uses/HT & Hashtags & Users & Uses/HT \\ \hline
 Business    & 27       & 20k   & 1,155   & 19       & 1,493 & 88   \\ \hline
 Celebrities & 32       & 26k   & 1,009   & -        & -     & -    \\ \hline
 Politics    & 485      & 349k  & 2,020   & 121      & 5,480 & 49   \\ \hline
 Sci/Tech    & 33       & 415k  & 6,889   & 63       & 4,982 & 100  \\ \hline
 Sports      & 98       & 76k   & 3,274   & 24       & 320   & 14   \\ \hline
\end{tabular}
}
\caption{Statistics of the SNAP and CRAWL data sets.}
\label{tab:hastag_topic}
\vsa
\end{table}

\subsection{Twitter follower structure and messages}

We use two datasets from Twitter: a large dataset \textit{SNAP}~\cite{Yang2011} including a $20\%$ sample of all tweets over a six-month period and the complete follower structure~\cite{Kwak2010}; and a smaller CRAWL dataset containing all messages of included users that we collected using Twitter's public API in 2012, where we started from initial seed nodes (members of the authors' labs) and crawled the follower structure and related posts. SNAP includes a network-wide view for a 6 month period, while CRAWL provides longitudinal completeness for a smaller subnetwork of users. Statistics of the two datasets are summarized in Table~\ref{tab:hastag_topic} and further discussed in the Supplement~\cite{appendix}.

\subsection{Grouping hashtags into topics}
While hashtags present a concise vocabulary to annotate content, they are free-text user-defined entities. Hence, we need to group them into topics in order to summarize user behavior at the topic level. In this work we assume a 1:1 mapping of topics to hashtags, while in a more general framework disseminated hastags (urls, memes, etc.) can be ``softly'' assigned to more than one topic. We work with five general topics as dimensions for our user genotypes: Sports, Politics, Celebrities, Business and Science/Technology. We obtain a set of $100$ high-confidence hashtag annotations from a recent work by Romero and colleagues~\cite{Romero2011}, further augmented by a set of curated business-related hashtags~\cite{Ribiero2012}.
We combine this initial set of annotated hashtags with a larger set based on text classification

To increase the number of considered hastags, we adopt a systematic approach for annotating more hashtags based on urls within the tweets. We pair non-annotated hashtags with web urls, based on co-occurrence within posts. We extract relevant text content from each url destination (most commonly news articles from foxnews.com, cnn.com, bbc.co.uk) and build a corpus of texts related to each hashtag. We then classify the url texts in one of our 5 topics using the MALLET~\cite{McCallum2002} text classification framework trained for our topics of interest.
As a result, we get a frequency distribution of topic classification for frequent (associated with at least $5$ texts) hashtags. The topic annotation of the hashtag is the topic of highest frequency. The number of hashtags and their usage statistics in our final topic-annotated set are presented in Table~\ref{tab:hastag_topic} (columns Users and Uses/HT). The Celebrities hashtags do not occur frequently enough in the CRAWL dataset and hence we exclude them from our analysis.

\section{Genotype model validation in Twitter}
To qualify the genotype model as a meaningful representation of social network users, we demonstrate that the genotype model is capable of capturing stable individual user behavior for a given topic. We seek to evaluate the stability of configuration of multiple users' genotype values within a topic, and use a classification task and the obtained (training/testing) accuracy as a measure of consistency for our genotype model. Within this context, we compare different genotype dimensions and evaluate the level to which each of them captures characteristic invariant properties of a social media user.

\subsection{Topic consistency for individual users}
Our hypothesis is that individual users exhibit consistent behavior of adopting and using hashtags (stable genotype) within a known topic. If we are able to capture such invariant user characteristics in our genotype metrics then we can turn to employing the genotypes for applications.
\begin{figure}[t]
\centering
 \includegraphics[width=0.4\textwidth] {classification.eps}
\caption{Training and testing accuracy of hashtag classification in a leave-one-out Linear Discriminant classification.}
\label{fig:SNAP_traintest}
\vsa
\end{figure}
We compute genotype values according to our collection of hashtags with known topics by training a per-user Linear Discriminant (LD) topic classifier to learn the separation among topics. Consider, for example, the LOG-LAT genotype metric: for a user $u$, we have a set of observed LOG-LAT values (based on multiple hashtags) that are associated with the corresponding topics. If the user $u$ is consistent in her reaction to all topics, then the LOG-LAT values per topic will allow the construction of a classifier with low training and testing error. It is also noted that each hashtag does end up having a topic distribution, but for the scope of this study, a sufficient hashtag classification should at least agree in the topic of greatest probability/likelihood, which is what is presented here.

The consistency of user responses is evaluated using a leave-one-hashtag-out validation: given the full set of $(u,h)$ response values, we withhold all pairs including a validation hashtag $h$ and employ the rest of the pairs involving hashtags of known topic to estimate the individual user's topic genotype. We repeat this for all genotype metrics. The training and testing error rate for this experiment are presented in Fig.~\ref{fig:SNAP_traintest}, and their similar error rates demonstrate how consistent users are at classifying hashtags into topics. In both cases, our genotype metrics enable significantly lower error rates as compared to a Random model (i.e. random prediction based on number of hashtags within a topic), demonstrating that, in general, genotype metrics capture consistent topic-wise behavior. One exception is the Politics topic as it has comparatively many more hashtags than other topics, skewing the random topic distribution resulting in slightly lower error. Across genotype metrics, we observe that normalized latency of adoption (LOG-LAT) is more consistent per user than alternatives.

\begin{table}[t]
\centering
{\scriptsize
\begin{tabular}{|l|c|c|c|c|c||c|}
\hline
	& Bus. & Celeb. & Poli. & Sci./Tech. & Sport & E[x]\\ [0.5ex]
\hline
Random Error	& 0.96 & 0.95 & 0.28 & 0.85 & 0.95 & 0.45 \\ \hline
F-PAR 			& 0.50 & 0.88 & 0.61 & 0.15 & 0.09 & 0.41 \\\hline
LAT 			& 0.09 & 0.46 & 0.18 & 0.19 & 0.25 & 0.21 \\\hline
LOG-LAT 		& 0.05 & 0.13 & 0.19 & 0.12 & 0.03 & 0.13 \\\hline
N-PAR 			& 0.09 & 0.50 & 0.88 & 0.09 & 0.03 & 0.40 \\\hline
N-USES 			& 0.45 & 0.42 & 0.90 & 0.22 & 0.56 & 0.54 \\\hline
TIME 			& 1.0	& 1.0 & 0.01 & 0.92 & 0.88 & 0.61 \\\hline
\end{tabular}
}
\caption{Error rates of the NB consensus topic classification. $E[x]$ is the expected error across topics.}
\label{tab:snap_performance}
\vsa
\end{table}

\subsection{Topic consistency within the network}
While individual users may exhibit some inconsistencies in how they behave w.r.t. hashtags within a topic, an ensemble of users' genotypes remain more consistent overall. To demonstrate this effect, we extend our classification-based evaluation to the the network level. We implement a network-wide ensemble-based Naive Bayes (NB) classifier that combines output of individual user classifiers to achieve network-wide consensus on the topic classification of each validation hashtag. Details on the network level classifier are available in the Supplement~\cite{appendix}.

Table~\ref{tab:snap_performance} summarizes the testing error rate of our NB scheme for classifying hashtags into topics in a leave-one-hashtag-out validation. The consensus error rate decreases compared to local classifiers (Fig.~\ref{fig:SNAP_traintest}), demonstrating that the genotypes, as a complex, are more stable and consistent than individual users. The lowest error rate of $0.13$ is achieved when using the LOG-LAT metric.

The latency genotype metrics that are most invariant (LAT and LOG-LAT) implicitly normalize their time scales of response with respect to the user's own frequency of activity, which is a feature not captured by the absolute TIME metric, or any of the other metrics. Furthermore, both of these metrics incorporate the network structure, measuring the message offset since the earliest exposure to the hashtag via a followee. LOG-LAT has a slight advantage over LAT because it suppresses the background noise of each hashtag measurement. However, LOG-LAT has the disadvantage that it is dependent on a network-wide latency measurement for the same hashtag, which might be harder to obtain in practice. In this sense, LAT is a more practical genotype dimension when summarizing individual user behavior in real time.

\begin{figure}[t]
\centering
\subfloat[LAT Net Classifier]{\label{Fig:SNAP_all_latency_LD_NB_logfit}
 \includegraphics[width=0.23\textwidth] {SNAP-hist-lat-lda-nb.eps}}
\subfloat[LOG-LAT Net Classifier]{\label{Fig:SNAP_all_loglat_LD_NB_logfit}
 \includegraphics[width=0.23\textwidth] {SNAP-hist-loglat-lda-nb.eps}}
\caption{Accuracy of the network classification as a function of the number of local classifiers (SNAP). Logistic function is fit to each topics accuracy.}
\label{Fig:SNAP_local}
\vsa
\end{figure}
While the system of all user genotypes exhibits significant consistency (high classification accuracy), it is interesting to understand how many user genotypes are needed to obtain a good classification (i.e. detect a network-wide topic-specific spread). We observe an increasing classification accuracy with the number of users included in the NB scheme. Figures~\ref{Fig:SNAP_all_latency_LD_NB_logfit} and \ref{Fig:SNAP_all_loglat_LD_NB_logfit} show the dependence of accuracy on number of local LD classifiers included per topic. All curves increase sharply, indicating that variability within individuals is easily overcome by considering a small subset of users within the network. The accuracy of LOG-LAT increases ``faster'' to its optimal level for increasing number of local classifiers, since the LOG-LAT metric features a network wide normalization and thus contains global information.

\section{Topic-specific influence backbones}
As we demonstrate in the previous section, user behavior remains consistent within a topic. A natural question inspired by this observation is whether topics propagate within similar regions of the shared medium that is the follower network structure. By observing the behavior of agents (adoption, reposting, etc.) one can reveal the underlying backbones along which topic-specific information is disseminated. In this section, we study the propagation of hashtags within Twitter to identify \textit{topical influence backbones} --- sub-networks that correspond to the dynamic user behavior. We superimpose the latter over the static follower structure and perform a thorough comparative analysis to understand their differences. The topical backbones in combination with the individual user genotypes will then enable various applications as we show in the subsequent section.

\begin{figure}[t]
  \centering
  \includegraphics[width=0.35\textwidth]{SNAP_NET_OVERLAP.eps}
  \caption{Overlap among topic influence and corresponding follower subnetworks (in SNAP). Each network is represented as a node, with every topic represented by an influence (encircled in the middle) and a follower network. Node sizes are proportional to the size of the network (ranging from $120k$ for Celebrities to $42m$ for Politics Follower). Edge width is proportional to the Jaccard similarity of the networks (ranging from $10^{-3}$ inter-topic edges to $10^{-1}$ between corresponding influence-follower networks).}\label{fig:net_overlap_snap}
\vsa
\end{figure}

An \textit{influence edge} $e_{i}(u,v)$ connects a followee $u$ who has adopted at least one hashtag $h$ within a topic $T_i$ before the corresponding follower $v$. Hence, the influence network $N_{i}(U,E_{i})$ for topic $T_i$ is a subnetwork of the follower network $N(U,E)$ (including the same set of nodes $U$ and a subset of the follower edges $E_{i}\in E$). We weight the edges of the influence network by the number of hashtags adopted by the followee after the corresponding follower within the same topic.

First, we seek to understand the differences between the influence backbones and the static follower network. Figure~\ref{fig:net_overlap_snap} presents the overlap among influence backbones and their corresponding follower network. For this comparison, we augment an influence network with all follower edges among the same nodes to obtain the corresponding follower network.
In the figure, each network is represented by a node whose size is proportional to the network size (in edges). Connection width is proportional to the \textit{Jaccard Similarity (JS)} (measured as the relative overlap $|E_i\bigcap E_j|/|E_i \bigcup E_j|$) of the edge sets of the networks. The Jaccard similarity for influence and follower networks varies between $0.16$ for Sports to $0.3$ for Celebrities. The influence networks across topics do not have high overlap (JS values not exceeding $0.01$), with the exception of Sci/Tech and Politics with $JS=0.07$. This may be explained partially by the fact that these are the largest influence networks ($5$ and $11$ million edges respectively). Another reason could be that there are some ``expert'' nodes who are influential and active in both topics. The degree distribution within the topic backbones also changes (w.r.t. the static structure) with highest impact on low degree nodes and significantly lower fraction of reciprocal links between users (see Supplement~\cite{appendix}).

Beyond network sizes and overlap, we also quantify the structural differences of the influence backbone in terms of connected components. A \textit{strongly connected component (SCC)} is a set of nodes with directed paths among every pair, while in a \textit{weakly connected component (WCC)} connectivity via edges regardless of their direction is sufficient. Figure~\ref{fig:cc_snap} compares the sizes of the largest SCC and WCC in the topic-specific networks as a fraction of the whole network size. When ignoring the direction (i.e. considering WCC), both the influence and follower structures have a single large component amounting to about $99\%$ of the network. The communities that are active within a topic are connected, showing a network effect in the spread of hashtags, as opposed to multiple disjoint groups which would suggest a more network-agnostic adoption. When, however, one takes direction into consideration (SCC bars in Fig.~\ref{fig:cc_snap}), the size of the SCC reduces drastically in the influence backbones. Less directed cycles remain in the influence backbone, resulting in a structure that is close to a directed acyclic graph with designated root sources (first adopters), middlemen (transmitters) and leaf consumers. The reduction in the size of the SCC is most drastic in the Celebrities topic, indicative of a more explicit traditional media structure: sources (celebrity outlets or profiles) with a large audience of followers and lacking feedback or cyclic influence.
\begin{figure}[t]
  \centering
  \includegraphics[width=0.42\textwidth]{backbones.eps}
  \caption{Largest weakly and strongly connected component (WCC and SCC) sizes as a fraction of the network size (top); and Kendall $\tau$ rank correlation of node importance measures for the influence and follower networks (bottom) (SNAP). }\label{fig:cc_snap}
\vsa
\end{figure}

\textit{How does a user's importance change when comparing influence to following?} In Figure~\ref{fig:cc_snap} (bottom) we show the correlation of node ranking based on number of followers, followees and PageRank~\cite{PageRank} in the influence and follower networks. The correlation of each pair of rankings is computed according to the \textit{Kendall $\tau$} rank correlation measure. The correlation is below $0.5$ for all measures and topics. Global network importance (PageRank) is the most distorted when retaining only influence edges ($0.4$ versus $0.5$ on average), while locally nodes with many followers (or followees) tend to retain proportional degrees in the influence network.

Our comparative analysis of the influence and follower structure demonstrates that the influence backbone is quantitatively different from the overall follower network. The explanation for this lies in the fact that the influence backbone is based on the dynamic behavior of users (information dissemination on specific topics), while the follower structure represents the static topic-agnostic media channels among users. Not all followees tend to exert the same amount of influence over their audiences in the actual information dissemination process, giving rise to distinct topic-specific influence backbones. We obtain similar behavior in the smaller Twitter data set CRAWL (omitted due to space limitation).

\section{Applications of genotypes and backbones}

In this section, we employ the user genotypes and the topic-specific backbones for two important applications: (i) prediction of hashtag adopters and influencers and (ii) latency minimization of topical information spread. In both applications knowledge of individual genotypes and influence backbones enables superior performance compared to the static network structure on its own.

\noindent{\bf Topic-specific influence prediction.} We employ the influence structure and the user genotypes to predict likely influencers/adopters for a hashtag. We aim to answer the following question: \textit{Which followees are likely to influence a given user to adopt a hashtag of a certain topic and analogously which followers are likely to adopt a hashtag?} This question is of paramount importance from both research and practical perspectives. On one hand, uncovering the provider-seeker influence will further our understanding of the global network information dynamics. On the other hand, the question has practical implications for social media users offering guidelines on following high-utility sources or keeping the follower audience engaged.

In this experiment, we consider \textit{(h,u)} pairs, for users who have at least $10$ followees and have used the hashtag at least once. The goal is to predict the subset of all followees who have used the hashtag prior to the user in question and similarly all adopting followers who are likely to use the hashtag later.
We construct three predictors utilizing the follower structure that rank influencers/adopters by \textit{Followees}, \textit{Followers} and \textit{Reciprocal} links. We also construct three activity-based predictors utilizing genotypes and influence edges and ranking influencers/adopters by their activity \textit{Act}, topic-specific activity \textit{Topic Act} and activity combined with centrality in the corresponding backbone \textit{RW+Act}. All predictors do not have information about the spread of the specific hashtag. More details on the predictors are available in the Suppplement~\cite{appendix}.

A prediction instance is defined by a user $u$ and an adopted hashtag $h$. Only a subset $I(u,h)$ of all structural followees/followers of the user are true influencers/adopters (positives for the prediction task). Our goal is to predict the subset of true influence neighbors using their features and local influence structure (excluding information about the same hashtag $h$). A good predictor ranks the true neighbors first. In order to overcome the effect of sparsity in the data, we consider prediction of instances for which at least one candidate followee is not isolated in the influence network after removing the links associated with the target hashtag. We measure true positive and false positive rates for increasing value of $k$ (the maximal rank of predicted influencers/adopters) and compute the average area under the curve (AUC) as a measure of the predictor quality. We report this measure within each topic in Figure~\ref{fig:influencers} for the SNAP (top) and CRAWL (bottom) datasets and for influence followees (left) and adopter (right) prediction.
\begin{figure}[t]
  \centering
    \includegraphics[width=0.48\textwidth]{influence.eps}
  \caption{Influential followee and adopter prediction accuracy. We consider several predictors of a user's influencers by a hashtag in a known topic. Genotype-based predictors (Act, Topic Act and RW+Act) perform better than follower structure-only counterparts (Follower, Followee and Reciprocal).}\label{fig:influencers}
\vsa
\end{figure}
Overall, in both datasets, the genotype-based predictors outperform the structure-only counterparts. The existence of a reciprocal follow link is the best structure-only predictor implying the importance of bi-directional links which often may correspond to a friendship relationship~\cite{Romero2011}.
The genotype-based predictors relying on topic specific activity, overall activity and the influence structure allow over $20\%$ improvement with respect to the reciprocity predictor and above two-fold improvement compared to number of followees/followers predictors. Although node information alone (\textit{Act} and \textit{Topic Act}) provides a good accuracy, this effect is even stronger when combining them with the knowledge of the topic influence network in the composite \textit{RW+Act} predictor. The RW+Act increases the rank of followees who have influenced the same user or other users within the same topic for different hashtags.

The predictor performance is similar in the CRAWL dataset (Fig.~\ref{fig:influencers}), showing the generalization of our models to different types of data. The smaller improvement in CRAWL (compared to SNAP) can be explained partially by sparser usage of our analysis hashtags or due to possibly evolving genotypes of users over longer time frames, a hypothesis we are planning to evaluate as future work.

\noindent{\bf Network latency minimization.} Another important problem that can be addressed given knowledge of topic-specific user behavior is that of improving the speed of information dissemination. Fast information dissemination is critical for social-media-aided disaster relief, large social movement coordination (such as the Arab Spring of 2010), as well as time-critical health information distribution in developing regions. In such scenarios, genotypes and the influence structure among users are critical for improving the overall ``latency'' of the social media network. In this subsection, we demonstrate the utility of our individual user models for latency minimization.

Consider a directed path in a topic-specific influence backbone $N$, defined by a sequence of nodes $P=(u_1,u_2...u_k)$. The \textit{path latency} $l(P)$ is defined as the sum of topic-specific latencies (\textit{Time} measure of the genotype) $l(P)=\sum_{j=1...k-1}Time(u_j),u_j \in P$ of all nodes except the destination. The \textit{source-destination latency} (or just latency) $l(u_1,u_k)=\min_{P:u_1\rightarrow u_k}l(P)$ is defined as the minimum path latency considering all directed paths between the target nodes. The concept of latency is similar to that of shortest path length, except that ``length'' is measured according to the responsiveness of traversed nodes (i.e., minimal time until $u_k$'s adoption of a hashtag introduced by $u_1$). The \textit{average network latency} is defined as the mean of all node pair latencies.
\begin{figure}[t]
  \label{fig:minlat}
  \centering
  \includegraphics[width=0.4\textwidth]{latmin.eps}
  \caption{Comparison of three heuristics for Latency Minimization in the SNAP dataset. The traces show the relative (w.r.t. the original) average network latency as a function of the number of targeted nodes $k$.}\label{fig:minlat}
\vsa
\end{figure}
Given a directed network $N(V,E)$ and latency for every node, we define the problem of \textit{$k$ Latency Minimization ($k$-LatMin)} as finding the $k$ best target nodes, whose latency reduction leads to the largest average network latency decrease. We assume that specific nodes could be targeted to reduce their individual latency. In real application scenarios, node latency can be reduced by timely and relevant content recommendation to target nodes and/or financial incentives. For our analysis we optimistically assume that every node's latency could be reduced to $0$, however, node-wise constraints can be incorporated according to known limitations of users.

One can show (via a reduction from the \textit{Set cover} problem) that $k$-LatMin is NP-hard.
We consider three heuristics: \textit{Max Lat} targets nodes in descending order of their latency values; \textit{Max BC} targets nodes in decreasing order of their structural node betweeness-centrality measure; and \textit{Greedy} targets nodes based on their maximal decrease of average latency combining both structural (centrality) and genotype (latency) information.

Figure~\ref{fig:minlat} shows the performance of the three heuristics in minimizing the average latency in subgraphs (of size 500 nodes) of the largest strongly connected components within the influence backbones of our SNAP dataset. Considering the node genotypes (Max Lat) or the influence backbone (Max BC) on their own is less effective than jointly employing both (Greedy) across all topics. The Greedy heuristic enables about 2-fold reduction of the overall network latency by targeting as few as 1\% (5 out of 500 nodes) of the user population. It is interesting to note that in Sports and Celebrities, since there are central nodes of large degrees, the betweeness-centrality criterion performs almost as good as Greedy.

\balance

\section{Conclusion}
We introduced the social media genotype---a genetically-inspired framework for modeling user participation in social media. Features captured by the user genotypes define the \textit{actual topic-specific} user behavior in the network, while the traditionally analyzed follower network defines only \textit{what is possible} in the information dissemination process. Within our genotype model, each network user becomes an individual with a unique and invariant behavioral signature within the topic-specific content dissemination. In addition, we demonstrated that users are embedded in topic-specific influence backbones that differ structurally from the follower network.

We instantiated our topic-based genotype and backbone framework within a large real-world network of Twitter and employed it for the tasks of \textit{(i)}  discovering topic-specific influencers and adopters, and \textit{(ii)} minimizing the network-wide information dissemination latency. The genotype framework, when combined with the topic-specific influence backbones, enabled good influence predictive power, achieving improvement by more than $20\%$ over using the follower structure alone. In the latency minimization application, we demonstrated that the knowledge of topic backbones and genotypes can enable 2-fold reduction of the overall network latency by reducing the latency of appropriately selected 1\% of the user population.

\noindent{\bf Acknowledgements.} This work was supported by the Institute for Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office and by the Army Research Laboratory under cooperative agreement W911NF-09-2-0053 (NS-CTA). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notice herein.

{\footnotesize

redpajama_set_name: RedPajamaArXiv


Care2 Causes | First Environmentalism - Then Socialism!
First Environmentalism – Then Socialism!
Klein's essay is well worth reading for anyone with an environmental consciousness who's trying to understand why saving the planet sounds so damn scary to some people. I would say it undermines everything they believe in, but as Klein makes abundantly clear, they don't believe in much of anything except preserving their own privileged, comfortable lifestyles.
I call the book Watermelons because they're green on the outside but red on the inside. After the Berlin Wall came down, the communist movement, the global leftist movement, was left in a bit of a quandary. They pretty much lost the economic argument. They needed somewhere else to go, and global warming has become the great proxy issue. It enables them to achieve many of the same aims as before but under a cloak of green righteousness. This book, although it is about global warming, is about something in fact much, much bigger than that. It is about a global takeover by fascism, communism, call it what you will; their aims are much the same. It is about control.
So, let's review. If you're concerned about the future of humanity and the natural world, and you accept the scientific experts' consensus that we're rapidly degrading the planet, and you believe we need to take immediate corrective steps, you're basically a control freak trying to resurrect communism. Wow. I'm going to go for a walk in the woods and try to wrap my head around this one. Care to join me, comrade?
This post was originally published by the Utne Reader.
Who's Afraid of Saul Alinsky?
Has the GOP Become a Cult?
I'd rather be a Socialist than a Fascist Conservative. I hate Conservatism/Conservatives.
I would much rather have a very left of centre government giving the people in a country some chance of democracy than a neo-con right wing facist government which sells out the country and its people like the slaves of yesteryear. I think it's time to put the proverbial banana peel under the proverbial corporate feet and watch them slip and fall beneath themselves. The neo-cons love getting government hand-outs but then immedialtely turn right around and call said the government meddling liberal elitists if they put forth a bill to protect the environment for the great good of humankind.
We should fear all multinational corporations because they are like leeches on the backs of the very people who really need some charitable grace from their own government.
While corporations may be necessary, fascism is not the kind of government any countries peoples should aspire to be ruled by. America is a Republic ('power' is the 'people' who Vote for political leaders to legislate). That has been lost in this country. Corporations have become far too powerful and as we've seen with the U.S. Supreme Court Justices; the golden rule has been passed into law (those who have the gold, rule). Employees have the ability to contribute as individuals without a second, much more influential power, the corporation 'itself' entering into a political foray. Now a corporation is considered an individual who can exert as much influence as money will buy; and they're doing just that. This is not only a vile threat to Democracy, but may be the undoing of America and what this freedom loving country has represented throughout the world.
First problem: If the excerpt here is representative of Klein's essay, then her analysis of conservatives is, as usual, totally wrong. It's not a fear of addressing environmental issues, but the belief that addressing them does not require that we "break every rule in the free-market playbook". They see attempts to address environmental issues specifically in the manner that Klein advocates as doomed to fail the environment, but effectively support socialism.
Second problem: The real meat of the original Climategate was ignored by most media. Forget the emails. I didn't even bother with them after seeing the programmer's log, "HARRY_READ_ME.txt". The guy who wrote the software used to make the predictions used by the IPCC was apparently shocked by the dreadful record-keeping and untrustworthy data he was told to use.
Corporations, even though they as a collective get blamed for everything, they are necessary. Go to any country that doesn't have corporations to rival the power of the national government and you will see real oppression, extreme corruption and a lack of concern for citizen's rights.
Sorry, this is more tangential to the conversation.


Dave Swallow "Custom Tackle" Columbia Road, Bournemouth. It was shop policy not to wear waders in the shop as light fingered anglers were known to drop floats inside of them. The main attraction as a thirteen-year-old was to see his wife Thelma sat on a bar stool behind the counter in her mini skirt and black knee high boots. Happy days.
Reids tackle just outside Wilton in Wiltshire,a small space ,part of a removal firms premises,he had more stuff than you could shake a stick at,float making materials,diy rod making ,second hand section,and the place just smelled amazing with the ground baits,i can still smell it to this day.the man was always happy to see us kids,he didnt mind selling us a half pint of maggots,but then he knew that when we were flush after some oat picking or something we would be making a beeline to his shop to spend the lot!
I now use Homestores whenever I can, but only for around 10 years or so, a mere youngster!
First proper tackle shop would've been Bowlers on the Merry Fiddlers roundabout in Dagenham, tackle shop on one side, that was run by Mr Bowler, and a 'knick=knack' shop on the other that was run by his wife. Shops were combined into one after old Mr Bowler died, Keith Bowler then took over and was still running the shop when I moved to Hampshire in '96. I think Keith died around 2007 and the shop closed in 2015. I used to buy all my bait and tckle there for the weekly outings with the White Hart Dagenham Angling Society.
I wish I could remember which tackle shop I used as a youngster. It would have been in Grantham where I was st school. I do remember buying bits in Woolworths but usually when shopping with my mum and I could drop bits into her basket!
We used to fish at Denton Reservoir a few miles from the village where we lived. We strapped our rods to our cross bars, filled our saddle bags with tackle and lunch and off we went on our great adventures! Happy days indeed!!


Dartmouth College uses a system called the Dartmouth Name Directory to handle centralized authentication and to serve as an email directory. This system is closely tied to the rather odd BlitzMail system which is used for all students and staff to do email. The BlitzMail system is compatible to send and recieve regular email, however, it is not a regular sendmail or postfix server like is normally used. The specalized servers can accept a name, say "Ryan Speers" in the "to" field, and can translate that into sending it to me. It can also accept "rms" and "rmspeers" as pointing to me as well as I have defined these aliases. This functionality is great, but is only avalible within the BlitzMail client. Other email programs, like Thunderbird, will not allow you to address an email to only "rms". The LDAP connection to the DND is a step in the right direction, but only works for full names, not the aliases. An ideal system would allow a client like Thunderbird or Apple Mail to fully use the power of the DND. For now, this doesn't seem to exist. Any thoughts on creating this are welcome.
For now, I use a DND search plugin for Firefox (should also work in IE, etc). This has the full functionality and I suggest installing it if you are a Dartmouth user. You can my implementation here.
I am currently in my eighth year of studying German, and I want to include some of the most useful resources which I use here.
When I develop for the web, my primary browser is Firefox. It is my main browser overall, and has merits such as being standards-complaint, but there are additional bonuses. Add-ons. I will explore some of these today that I regularly use. Some of these are for web developers, while others I believe to be productive for any person using the web in every-day life.


text:
Q: Как динамически создать n Buttons произвольной формы Необходимо на форме создать произвольное количество кнопок, такой формы, что бы все они сходились в центре(). Я так понимаю нужно создать свой класс кнопок а потом уже пользоваться им? Помогите. Пример на картинке

A: Можно попробовать так:
// Load your bitmap for the button
private Bitmap bmpButton_06 = Properties.Resources.button_06;
    private void Form1_Load(object sender, EventArgs e)
    {
        Button button;

        int countButton = 7;
        float startAngle = (float)(-30F  );
        float sweepAngle = (float)(360F / countButton);
        PointF rectPoint = new PointF(50, 50);
        float R = 200;
        SizeF rectSize = new SizeF(2 * R, 2 * R);
        RectangleF rect = new RectangleF(rectPoint, rectSize);
        PointF center = new PointF(rectPoint.X + (rectSize.Width / 2), rectPoint.Y + (rectSize.Height / 2));

        Graphics gr = this.CreateGraphics();

        for (int i = 0; i < countButton; i++)
        {
            float wx1 = (float)(center.X + R * Math.Cos((double)startAngle * 2 * Math.PI / 360));
            float wy1 = (float)(center.Y + R * Math.Sin((double)startAngle * 2 * Math.PI / 360));
            float wx2 = (float)(center.X + R * Math.Cos((double)(startAngle + sweepAngle) * 2 * Math.PI / 360));
            float wy2 = (float)(center.Y + R * Math.Sin((double)(startAngle + sweepAngle) * 2 * Math.PI / 360));

            float xM = (wx1 + wx2 + center.X) / 3;
            float yM = (wy1 + wy2 + center.Y) / 3;

            GraphicsPath path;
            path = new GraphicsPath();
            path.StartFigure();
            path.AddLine(center.X, center.Y, wx1, wy1);
            path.AddArc(rect, startAngle, sweepAngle);
            path.AddLine(wx2, wy2, center.X, center.Y);
            RectangleF rectF = path.GetBounds();
            path.AddString(i.ToString(), FontFamily.GenericSansSerif, 20, 20, new PointF(xM,yM), StringFormat.GenericDefault);
            path.CloseFigure();

            gr.FillPath(Brushes.Red, path);
            gr.DrawPath(Pens.Black, path);
            button = new Button()
            {
                Name = "button_" + (i + 1).ToString(),
                Region = new Region(path),
            //    Text = "Function_" + (i + 1).ToString(),
            //    TextAlign = ContentAlignment.MiddleCenter,
                Visible = true,
                AutoSize = true,
            //    BackgroundImage = bmpButton_06,
                Size = new Size((int)(rectSize.Width+rectPoint.X + 10), (int)(rectSize.Height+rectPoint.Y + 10))
            };
            button.Click += Button_Click;
            this.Controls.Add(button);

            startAngle += sweepAngle;
        }

        this.Invalidate();
    }

    private void Button_Click(object sender, EventArgs e)
    {
        if(sender is Button button)
        MessageBox.Show(button.Name);
    }


text:
The School of Peace & Counter-Terrorism Studies, Minhaj University Lahore (MUL) is marking its importance by making students innovative and enabling them to sort solutions out of difficult capacities and issues like the syndrome of war and terror, which has entangled and entwined the world badly. Moreover, MUL shares this pride of launching various programs like ADP, BS, MPhil, PGD Diploma, certificates in School of Peace & Counter-Terrorism Studies from Spring Semester 2021. A renowned Political Scientist and an expert on International Politics and Foreign Policy, Prof. Dongsoo Kim acknowledges the effort of Minhaj University Lahore of launching the School of Peace & Counter-Terrorism Studies which will surely bridge the gap between ethnic and religious communities.
School of Food and Nutrition
School of Islamic Economics, Banking & Finance


text:
Eduardo Michelle Núñez Méndez (ur. 15 czerwca 1987) – dominikański baseballista występujący głównie na pozycji trzeciobazowego i łącznika w Boston Red Sox.

Przebieg kariery

New York Yankees
W lutym 2004 podpisał kontrakt jako wolny agent z New York Yankees. Zawodową karierę rozpoczął w 2005 roku w Staten Island Yankees (poziom Class A-Short Season), następnie w 2006 i 2007 grał w Charlestown RiverDogs (Class A) oraz w Tampa Yankees (Class A-Advanced). Sezon 2008 spędził w Tampa Yankees. W 2009 występował w Trenton Thunder (Double-A), gdzie rozegrał 123 mecze, w których uzyskał średnią 0,322.

Sezon 2010 rozpoczął od występów w Scranton/Wilkes-Barre Yankees (Triple-A), a 19 sierpnia 2010 został powołany do 40-osobowego składu New York Yankees i tego samego dnia zadebiutował w Major League Baseball w meczu przeciwko Detroit Tigers jako pinch hitter. Dwa dni później w spotkaniu ze Seattle Mariners zaliczył pierwsze uderzenie w MLB (RBI single). 28 sierpnia 2010 w meczu z Chicago White Sox zdobył pierwszego home runa w MLB. W latach 2011–2013 występował głównie zastępując Dereka Jetera lub Aleksa Rodrigueza.

Minnesota Twins
W kwietniu 2014 w ramach wymiany zawodników przeszedł do Minnesota Twins. Sezon 2014 rozpoczął od występów w Rochester Red Wings (Triple-A), a w MLB wystąpił ponownie 17 kwietnia w drugim meczu doubleheader przeciwko Toronto Blue Jays, w którym zaliczył single'a. Dzień później powrócił do Rochester, a ponowne powołanie do składu Twins otrzymał 8 maja. W 2015 grał na czterech pozycjach. W lipcu 2016, do przerwy spowodowanej Meczem Gwiazd, zanotował średnią 0,313, zdobył 11 home runów, zaliczył 34 RBI i został po raz pierwszy powołany do AL All-Star Team.

San Francisco Giants
28 lipca 2016 w ramach wymiany zawodników przeszedł do San Francisco Giants.

Boston Red Sox
26 lipca 2017 w ramach wymiany zawodników przeszedł do Boston Red Sox. Cztery dni później w meczu przeciwko Kansas City Royals zdobył dwa home runy i dające zwycięstwo RBI single w drugiej połowie dziesiątej zmiany. 18 lutego 2018 podpisał nowy roczny z opcją przedłużenia o rok kontrakt z Red Sox.

Nagrody i wyróżnienia

Przypisy

Dominikańscy baseballiści
Baseballiści New York Yankees
Baseballiści Minnesota Twins
Baseballiści San Francisco Giants
Baseballiści Boston Red Sox
Urodzeni w 1987

redpajama_set_name: RedPajamaWikipedia


text:
Daily Post Ghana
Daily Post Nigeria
Fuel hike: Buhari insensitive to plights of Nigerians – Group
Sikiru Obarayese
A Non-governmental organization has declared the President Muhammadu Buhari-led administration as a government that has no remorse for the hardship citizen are facing in the country.
The organization says that the recent fuel hike in the country has shown that the Buhari-led administration and the ruling All Progressives Congress are insensitive to the plights of Nigerians.
The NGO, Afri-Goal Foundation in a message sent to DAILY POST on Thursday made this assertion.
The Pipelines and Product Marketing Company (PPMC), a subsidiary of the Nigerian National Petroleum Corporation, NNPC, had earlier announced an increment in the pump price of petrol to N151.56 per litre.
Afrigoal, however, demanded that government reverses the pump price to its original N130 and also reverse other anti-human taxes and tariffs increase.
According to the NGO, the latest increments should not have been thought of as it is coming at a time when the people are yet to get over the hardship and bite of COVID-19.
"While battling the impact of COVID-19, the government not only increase electricity tariff but also raised taxes and levies on the informal sector.
"This fuel hike appears to be a slap on the faces of Nigerians who are merely striving to provide for themselves what the government has failed to do," the NGO said.
It, however, urged the government to empathize with Nigerians on what they are going through and put a halt to all policies and hikes that will further compound the woes of Nigerians.
Related Topics:buhariFuel hikeNigeria
CAN under attack for declaring Fani-Kayode as future Nigeria's President
APC crisis: Don't return to trenches – Science Minister Onu, tells Enugu members
Buhari reacts to death of Abubakar, Sultan of Sokoto's younger brother
EFCC clears air on 2021 recruitment
Don Silas
The Economic and Financial Crimes Commission (EFCC) has denied reports that the commission is currently recruiting.
EFCC made this known in series of tweets via its Twitter handle on Saturday.
The commission tweed, "EFCC wishes to alert the public about fake EFCC Recruitment Form 2021 circulating on the social media, and to warn that the Commission is currently not recruiting.
"Fraudsters are circulating forged Offer of Employment Letters, purporting same to be from the EFCC, and extorting members of the public.
"The public should note that, there is no ongoing recruitment in the EFCC. The purported 'EFCC Recruitment Form 2021' as well as the 'official recruitment portal' and 'Offer of Employment Letters' are non -existent.
"For the avoidance of doubt, recruitment into the EFCC is a structured, transparent and merit-driven process which is always heavily advertised through the mass media and the Commission's social media platforms. It is highly automated, with no place for the so-called Employment Form.
"The EFCC is on the trail of the scammers behind this devious scheme as no efforts will be spared to bring them to justice.
"The Commission urges the public to cross check any doubtful information with the agency through: [email protected]"
Ifreke Inyang
President Muhammadu Buhari has expressed his sadness over the death of Hajiya Fatima (Fanta) Garba Mohammed, the immediate younger sister of late military Head of State General Sani Abacha.
In a statement by Buhari's Senior Special Assistant to the President on Media and Publicity, Garba Shehu, the president condoled with the Abacha family.
Hajia Fanta is the mother of Senator Basheer Mohammed (Lado), Federal Commissioner, National Commission for Refugees, Migrants and Internally Displaced Persons (IDPs).
Buhari also said he sympathises with Lado and his siblings as well as the people of Kano State, noting that Hajia Fanta devoted her time on earth to care for the less-privileged and godly upbringing of her children.
President Buhari prayed that Allah will console all those who mourn and grant Hajiya Fanta Aljannatul Firdaus.
She was aged 75.
Copyright © Daily Post - Nigeria News


text:
Preservation of the Former Vistoso Golf Course in Oro Valley, Arizona
Preserving the Former Vistoso Golf Course in Oro Valley, Arizona
With the help of many dedicated residents, The Conservation Fund will acquire and preserve 202 acres of open space in Oro Valley, Arizona to enhance the area's natural, cultural and recreational resources.
Donate to the VisToSO Project
The town of Oro Valley, Arizona is nestled between mountain ranges within the Sonoran Desert, just a few miles north of Tucson. The Vistoso Golf Course in Oro Valley ceased operations in 2018, leaving area residents to wonder what would become of the 208-acre property that weaves it way through a residential area called Rancho Vistoso. One potential fate for the property would have been further development into more homes and buildings. However, many Oro Valley residents envisioned preserving this open space and turning it into a nature preserve with trails open to the community. These residents soon organized and rallied around the town's motto, "It's in our nature," to bring their vision to reality, contacting The Conservation Fund for assistance along the way.
Photo by Bill Murray and Preserve Vistoso
After a successful second round of negotiations with the seller, we have reached an agreement for The Conservation Fund to purchase 202 acres of recreational open space that was once the fairways of the former Vistoso Golf Course (outlined in green on the map). A 6-acre parcel, a parking lot zoned for high -density residential use (outlined in brown on the map), will be sold separately to an outside developer.
Credit: The Conservation Fund
Once the 202 acres of the former Vistoso Golf Course is purchased, The Conservation Fund will protect the land with a conservation easement. While the Town of Oro Valley will become the eventual owner of the property, a qualified land trust will be named as the long-term property steward who will ensure it maintains adherence to the terms of the conservation easement.
Preserving the Vistoso property provides an opportunity to save open space woven throughout several neighborhoods in Oro Valley. It boasts spectacular mountain scenery, Sonoran Desert vegetation, Native American petroglyphs, and habitat for local wildlife. It already contains more than six miles of paved trails, three restrooms and trail underpasses for major roads, which will all be immediately useful as it transitions from golf course to public park.
We have launched a $1.8 million fundraising effort to make this critical conservation effort a reality by the end of December 2021. Your donation today will directly support the Vistoso preservation project in Oro Valley, Arizona.
Tax-deductible charitable contributions may be made online, by check, wire transfer, securities transfer, and qualified charitable distribution.
Online - To donate online to the Vistoso project, please click here.
Check - Checks should be made payable to The Conservation Fund. Please designate your gift by including "Vistoso" on the reference line and mail to The Conservation Fund's headquarters: 1655 N. Fort Myer Drive, Suite 1300, Arlington, VA 22209.
Wire - Please contact Scott Tison at stison@conservationfund.org to make a donation via wire.
Pledge Form - Download the Pledge Form here.
In the unlikely event that the Vistoso project does not come to fruition, you can redirect your gift to one of The Conservation Fund's other conservation initiatives or your gift can be refunded. We will contact you directly should this unlikely event occur.
Blog: Preserving Open Space Is Par for the Course in Oro Valley by Mike Ford
Preserve Vistoso official website
Photo by Rosa Dailey
Project Experts
Arizona Field Representative, Conservation Acquisition
Regional Director of Fundraising, Gulf Coast & Southwest
Project Programs


The world has seen other so-called flying carpet chairs before. But the Carpet Chair, released in 2016 by breakout Cyprus design brand Mousarris in collaboration with artist Jan Blythe, flies above them all.
Made from an actual Persian carpet, the limited-edition chair utilizes steel reinforcements to appear to float gracefully above the ground. Its delicate form is design-conscious and sacrifices not an ounce of style for its conceptual gimmick. It can even can be customized for your interior by the designer with bespoke colorways and patterns suited to your décor.


text:
Charting the road return of rec hockey: 'I believe we've found a path back'
The Jacksonville Ice & Sportsplex was one of the first arenas in North America to reopen when it reconvened its adult league this past weekend. Players couldn't keep from getting into fights, but they did seem to refrain from spitting.
By Ken Campbell
A couple of things happened this weekend that made Mark Scheff believe that, when it comes to the return of grassroots hockey from the COVID-19 pandemic, things are maybe, just maybe starting to get back to normal.
The first thing was the first group to occupy the ice at the Jacksonville (Fla.) Ice & Sportsplex when it reopened last Friday was a group of firefighters who have a regular time slot. You'd think that if anyone would be reticent about getting on the ice first, it would be a group of first responders. But Scheff reported there were about 20 of them out on the ice Friday morning. The second was that there were even a couple of fights, not including the pay-per-view UFC card that was held in Jacksonville over the weekend. We're talking on-ice fights and suspensions in the Jacksonville Adult Winter Hockey League. "So I guess we're officially back," Scheff said.
The Jacksonville rink was one of the first to re-open in North America after arenas were shuttered in the wake of the COVID-19 pandemic. When Florida Gov. Ron DeSantis declared Phase I of the state's reopening plan in effect last week, Scheff set about to ready his facility to get players back on the ice. He estimates that this past weekend between 400 and 500 people came through the facility and things went smoothly. Players had their temperatures taken when they arrived at the rink, they didn't shower at the facility and had to leave within 15 minutes of their games ending, spectators were kept to a minimum and referees wore masks and used electronic whistles.
"I really believe we have found a safe path back," Scheff said. "That is my hope."
As a result, Scheff said the rink will open up a few more programs this week, including offering ice time to elite players for group workouts, stick and puck shinny and the adult development program, which Scheff said sold out in an hour. Other rinks in the U.S., many of whom reached out to Scheff to get protocol guidelines, will be opening their doors in the coming weeks. "If we continue to be successful without any incidents, this is the path back," Scheff said.
Teams were given two dressing rooms each to allow for social distancing and those rooms were disinfected before, during and after each game. The time lapse between games was 45 minutes, which gave players who had just played ample time to leave the rink before players arrived for the next game, which limited interaction and crowds in the building. Including staff, there were never more than 50 or 60 people in the building at one time. After TheHockeyNews.com did a blog last week on the facility opening, Scheff said he received a host of inquiries from Canada and USA asking about protocols and safety measures. He said that by far, any facility wants to reopen should keep paramount in its mind that cleanliness is next to godliness.
"The thing of uppermost importance is that when you walk into any facility, it needs to feel clean and sanitized," Scheff said. "The minute you walk in the door, if it feels like it used to, they're going to say, 'Oh, I don't know.' But when you walk in this building, it smells like Pine-Sol."
Scheff and his employees were actually surprised at how compliant the players were. Almost all of them waited in their cars if they arrived at the rink too early and were mindful about leaving the rink as soon after their games as possible. (And as you can see by the rather bizarre picture that accompanies this story, at least one team even took social distancing to heart on the ice. Who lines up beside a goalie for a faceoff at center ice?) The one thing that could have become a contentious issue was spitting. Players were asked to refrain from doing so, which is much easier said than done. Anyone who has played knows spitting in hockey can be as instinctual as skating and shooting.
"That was a big thing for us," Scheff said. "We made it known in our protocols that we wanted people to refrain from spitting on the ice and in the locker rooms and I heard nothing from my departments about it. That was a biggie, in the top three. I got no reports of it, I didn't see it. Maybe the past six weeks in quarantine changes behaviors."


Under the JCT suite of contracts, a Relevant Matter is a matter for which the employer is responsible that materially affects the progress of the works and may entitle the contractor to make a financial claim for the direct loss and/or expense that it has incurred. Kara Price, a solicitor within Womble Bond Dickinson's specialist construction team, gives some pointers.
A contractor can often claim loss and/or expense at the same time as an extension of time. The Hot Topics article in September on 'Relevant Events' dealt with extensions of time.
That the employer has breached the contract.
Disruption caused by work carried out by the employer.
Amending the contract to ensure no entitlement for loss and/or expense for the contractor's own error, omission, negligence, breach or default on behalf of the contractor or any contractor's persons.
Ordinarily, a subcontract will mirror the terms of the main building contract or contain a deemed awareness provision so that any employer amendments or deletions will be passed down the supply chain.
Review the contract – have any amendments been made which could limit your ability to claim for direct loss and/or expense?
Review the contract mechanisms in respect of notification of a Relevant Matter.
Ensure you have a good record-keeping system – if a claim is made, an assessment of the loss and/or expense already incurred and any further amounts likely to be incurred will be required.


The girth gear is the major component used in rotary kiln and ball mill which is required to be operated in a long time. So, the quality requirements during the actual production for the big Girth Gear are very high.
1. The particular heat treatment technology is used for the big gear ring manufactured by Chaeng which makes the improvement in the structure optimization and the hardness of the product. The wear-resistant and anti-impact performance is also enhanced greatly.
2. The high strength steel was used by us in manufacturing the girth gear. We also take the optimization for the product against the operation characteristics of the rotary kiln to ensure the stability of the component during the long time operation and extend the service life of the component.
3. Our company has rich production capability in steel castings. For the components such as the girth gear ring, we can provide them in large production quantity with short cast period and large amount.


River Falls, Wis. – AMS Spectral UV – A Baldwin Technology Company announced its Platinum Sponsorship of PRINT UV 2019 (March 27-29), the world's leading conference for printers who employ UV-based curing technologies as part of the commercial and packaging printing process. AMS Spectral UV also confirmed it will unveil new LED-UV curing technology products at the event.
To learn more about registering for PRINT UV 2019, visit printuv.com. For more information about AMS Spectral UV, visit amsspectraluv.com.


Today would have been Hildegard's 77th birthday. Few singers have influenced my life and love of singing as much as this great lady. It's hard to believe that this August she will have been gone five years from us.
But this is not a mournful post, but rather a celebration of her birth of one of those singers who became a polarizing force in the world of opera. People loved her, people loathed her and, often there was not much room in between.
For me, Behrens' voice was one-of-a-kind; instantly recognizable and, as with the most committed of singers, always in search of how best to serve the composer. It's interesting to me how, a few years now after her death, whenever I play her recordings for friends, the almost universal comment is, "I don't remember her voice being this beautiful," a sentiment I, who have always found that voice so beautiful, have difficulty fathoming. But, I'm just glad they do.
There were so many roles I adored her in, but none so much as the one that introduced me to her: Salome. While I grew up on other singers of the role - great ones to be sure - Behrens was the very first who made me see and hear the depraved Judean princess as a girl, and that, my friends, changed everything. There were so many touches I'd never before heard, and I recall anticipating how she would belt out that first great phrase when her bloody prize emerged from the cistern. "Du wolltest mich nicht deinen Mund," - here, most sopranos deliver the moment with either a sense of exaltation or horror movie terror . . . effective either way but with Behrens you get both . . . each one simultaneously in an explosion of sound that, naturally, changes the course of the rest of the opera. Throughout Strauss' remarkable music Behrens sweeps through combining exquisite, silvery lyricism then ramping it back up with dramatic explosions of near volcanic proportion.
I'm ranting on (as usual) wanted something up here today to honor the birthday of this amazing singer who, right up until the day she was taken from us, was still filled with the joy of music, singing, working and teaching young singers.
You may be gone, but Happy Birthday, Hildegard . . . and danke danke schön, dear lady.


text:
<!DOCTYPE html>

    <meta charset="UTF-8">
    <title>Salem Witch Trials</title>
    <link href='http://fonts.googleapis.com/css?family=Oswald:300' rel='stylesheet' type='text/css'>
    <link rel="stylesheet" href="css/reset.css">
    <link rel='stylesheet prefetch' href='http://ilt-insightdlp-static.s3.amazonaws.com/css/default.css'>
    <link rel="stylesheet" href="css/style.css">
    <link rel="stylesheet" href="css/shea_style.css">

Your father recently passed away due to an unknown sickness. He was a farmer on a small farm in the outskirts of Salem. Your mother spent most of her time taking care of the house and cooking for the family. Whenever anyone in the household got sick, it was your mother's responsibility to care for them. You grew up as the oldest of four siblings, but over the years, each of them has died, leaving you as the last child in the family. Your father resented you for surviving while your brothers fell ill and passed away. You are saddened by his death, but have learned to deal with grief from the death of all of your siblings. Many townsfolk are beginning to worry that they will be infected with whatever killed your father and brothers. Your friend comes over to help out now that you have fewer people in the house. She mentions that her parents are concerned about her spending time with you because of the suspicious circumstance of your father's death. Do you...

Option 1:

Mention how much your mother worked on the medications she had made to make your father better, but there was nothing she could do.

Option 2:

Mention how your mother was faithful to your father 'til the end, how lucky she was to have not contracted his horrible illness, and how well you felt.

Option 3:

Shrug and change the subject.

    <button class="ctrl-standard typ-subhed fx-bubbleUp">Option 1</button>

    <button class="ctrl-standard typ-subhed fx-bubbleUp">Option 2</button>

    <button class="ctrl-standard typ-subhed fx-bubbleUp">Option 3</button>

redpajama_set_name: RedPajamaGithub


What does it mean, this good, kind loving young man,-barely in his thirties- dying for no crime at all. What does it mean and what is it for?
What it means is that God loves us so much that God will withhold from us absolutely nothing – not even God's own dear Son. What it means is that no matter what, God will always be there for us, with All God's love and power, comfort and grace.
This Passion Sunday is, in one way, a very sad day. Walking with Jesus on this day can break your heart. But it's also the brightest of days, because it tells how very much we are loved, and because it reminds us who view it from the vantage point of the resurrection that, despite all appearances, failure, death, rejection, ALL WILL BE WELL!
This entry was posted on Saturday, April 13th, 2019 at 10:45 pm	and is filed under Cycle C, Palm Sunday. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.


text:
Upcoming Justin Bieber Atlanta Tickets & Tour Dates 2023
Justin Bieber Tickets - Atlanta
Justin Bieber concert in the Atlanta
Justin Bieber at Mercedes-Benz Stadium Atlanta on 18.07.2020
If you desire to hear the latest hits of your favorite singer Justin Bieber his Atlanta tour 2023 is especially for you! The concerts of the pop idol of puberty will last a propos North America from May to August.
The career of the singer started at his beforehand teens when the album My World, which became platinum in 2009. It was created in such genres as Pop, R&B and dance-pop. You must have heard his first songs One become old and One Less single-handedly woman that brought him nod in US. The single Baby from the adjacent album was in fact a realization. It has been known to millions of lovers of pop music. The behind album below the Mistlete recorded in 2011 was upon the top of Pops. The Boyfriend from the album Believe(2012) became number one in Canada. The artist has got a great number of awards, including American Music honor for artiste of the Year in 2010 and Grammy for Best Dance Recording in 2012 for the flavor Where Are U Now.
suitably, if you desire to hear such singles as Sorry, love Yourself and What complete You goal? visit one of the Justin Bieber concerts and get explosion of emotions of the music from the other album performed by conscious musicians. His songs won't leave you indifferent. You won't forgive yourself if you miss this star situation! see at the Justin Bieber dates and LP the Justin Bieber Atlanta tickets rudely!
Vip tickets and premium seating tickets for Justin Bieber Atlanta tour upon sale! See the dates below.
More concert locations:
LOCATION:Atlanta, GA, US
VENUE:Mercedes-Benz Stadium
ADDRESS:Martin Luther King Jr Dr SW & Northside Dr NW