Editor's Note: The following column first appeared in WIN, Volume 19, Issue 7, and printed March 13, 2013.
Four years ago, while Ed Viera was teaching and coaching at a small country school in Arkansas, he canceled the school's wrestling season.
"They were just kids who didn't want to work hard," he explained.
But what Viera and his assistant coaches have accomplished since then mirrors the rapidly expanding success of Arkansas high school wrestling … in just its fourth year as a sanctioned sport.
After Viera shut down the program, he vowed that the following year — when the rural school closed and the 1,200-student Maumelle High School opened — he'd recruit wrestlers from the ninth-grade honors classes.
His plan paid off in ways which have even Viera shaking his head in disbelief.
That first year, he took his team — all 10 freshmen — to the state tournament in Little Rock. Maumelle finished seventh.
Last year he fielded a full squad which included the 10 frosh returning as sophomores and just one senior. Two of the sophomores and the senior won state titles, and the team finished as Division IA-5A runner-up with 10 medalists.
On Feb. 23 this year, the Maumelle Hornets, who finished the season with a squad of 26, lived up to their No. 1 season-long ranking. They compiled 288.5 points to out-distance its closest competitor by 93 and took home the state hardware.
Wearing T-shirts that declared "Tengo Ganas!" ("I Have the Will to Win!"), a total of 10 Hornets garnered All-State honors, including four champions: junior Justin Butler, winning his second title at 138; juniors Dan Viera (Coach Viera's son), 152, and Keon McVay, 160; and sophomore Malik Singleton, 220.
But there was more: Outstanding Wrestler honors went to Butler, Cole Brainerd received the Pursuing Victory with Honor sportsmanship award and Viera was named Coach of the Year.
"It's great to have those accolades," Viera said of his award, "but it's (the wrestlers) who work hard. They know I give out only one award at our banquet, a 'Mr. Guts' award to someone who has persevered, usually over something major.
"Everyone else gets what they've earned.
Viera is also quick to give credit to his assistants, Tony Brainerd and Blake Butler, both dads of Maumelle wrestlers.
Though the honors have come early in the school's existence, building the wrestling program hasn't come easily.
One of Viera's ideas has been to post his wrestlers' matches on a computer folder called "Teachershare," used by the Maumelle High School staff.
"Whatever you put in there in your classroom, they can see and put up in their classrooms," said Viera, also an assistant varsity football coach.
"The wrestlers love it," Viera said. "Wrestling is not really big in Arkansas, so it's a battle to get people to come (to meets). Slowly but surely maybe we can get them to come to a meet by exposing them to a match.
He even coordinated his team's YouTube version of the "Harlem Shake" to ease their stress the week of the state tournament.
Viera and his wife, Mindy, are also parents of Dalimar, who played on her school's state championship volleyball team and is now a senior at the University of Arkansas, and Mindy, 15, a freshman volleyball player (with the same first name of her mother) at Bentonville High School.
Viera himself knows about battling the odds, having come to the United States from Cuba as a toddler.
"But I've always considered myself a guest in this country, and you always act better at someone else's house than at your own," he said.
As an example, Viera said, the team always takes garbage bags to meets to pick up after themselves. "After the meet, the gym is spotless," he said.


text:
Perast - Preparation for Restoration of the St. Cross Fortress
Experience of the Swedish organization for the care of heritage - Svenska för byggnadsvard föreningen, with which EXPEDITIO has been cooperating since 2001, was an impulse for our organization to try to achieve something siilar in our region. The first in a series of camps was the work action of clearing up the fortress "St. Baptism "in Perast 2002, attended by volunteers from our country and Sweden. The second volunteer work camp in 2003 was related to the preparatory work for the rehabilitation of the fortress in Perast. At this camp participated volunteers from our country and Sweden.
Cultural Heritage - Potential for the Development of Boka Kotorska
Preparation and organization of the one day round table entitled: "Cultural Heritage - Potential for the Development of Boka Kotorska.Round table was accompanied with development of the promotional material - 500 posters and 1000 leaflets promoting the topic of cultural heritage of Boka Bay. Partners: Regional Institute for Protection of Cultural Monuments, Kotor Montenegro. Sponsors: USAID/ORT Montenegro Advocacy Program.
Perast - Restoration Camp of the St. Cross Fortress
Experience of the Swedish organization for the care of heritage - Svenska för byggnadsvard föreningen, with which EXPEDITIO has been cooperating since 2001, was an impulse for our organization to try to achieve something siilar in our region. The first in a series of camps was the work action of clearing up the fortress "St. Baptism "in Perast 2002, attended by volunteers from our country and Sweden. The second volunteer work camp in 2003 was related to the preparatory work for the rehabilitation of the fortress in Perast. At this camp participated volunteers from our country and Sweden. Donor: Republic of Montenegro Assembly.
A New Durmitor House
Public anonymous architectural competition.The reason for launching the architectural competition "A NEW DURMITOR HOUSE" was the occurrence of illegal and inadequate building in the region of Mountain Durmitor which threatens to devastate permanently, both in the form and appearance, this area of exceptional value (protected by UNESCO).The project was aimed at promoting the principles of traditional and ecological/green architecture of Durmitor, as a starting point for future building activities. Donors: UNDP-United Nations Development Programme and Rockefeller Brothers Fund, USA.
Perast – Six BA Theses
The project present BA Theses of 5 students of the Faculty of Architecture and a student of the Faculty of Applied Arts in Cetinje. All the theses have a common topic – the town of Perast. Participants: Aleksandra Kapetanovic, Tatjana Rajic, Radojka Nozica, Ljubomirka Bilenjkij, Biljana Gligoric i Radmila Beca Radulovic. Sponsors: EXPEDITIO and foundation "ZID" (financed the exhibition within the Biennial of Cetinje).
The Secrets of Perast
This project was a part of the CHAIN OF DISCOVERIES project organized by the foundation MM ART from Podgorica. Our activity within project "Chain of Discoveries" was presenting less known places, people and events of Perast. Printing of a leaflet was also included. Sponsor: MM ART Foundation, Podgorica.
Zagora – an architectural workshop
EXPEDITIO workshop "Zagora" was held in August 2000 in this village in Grbalj. That was the second expedition on the territory of Grbalj (the first one was in 1998 in village Sutvara). The participants were 16 students of architecture and civil engineering from Banja Luka and Belgrade. Participants were placed at locals residences which gave a unique experience to our research. Sponsors: Association for the Restoration of the Podlastva Monastery, Grbalj; RESTAURART, Budva; MONTECEP, Kotor and JP MORSKO DOBRO, Budva.
Sutvara - an architectural workshop
Surveying the existing state of the village of Sutvara.The project was initiated by the "Association for the Restoration of the Podlastva Monastery" from Grbalj and included surveying the village and making photo documentation. This is the first documentation ever done for the village of Sutvara situated at the field of Grbalj. Sponsor: "Association for the Restoration of the Podlastva Monastery",Grbalj.
Perast - an architectural workshop '97
This was the first project - expedition - that we have conducted. The choice of the location i.e. Perast proved to have had a decisive role in the further development of EXPEDITIO.Our organization had official support by the UNESCO for this project. Sponsors: OPEN SOCIETY FUND, Belgrade; CEP, Belgrade; Ministry of Construction of Serbia; CIP-Transportation Institute, Belgrade; Nina GRO; Meteor promet; STEM, Belgrade; PAPIR PLAST, Belgrade and Ministry of Environmental Protection and Spatial Planning of Montenegro.
Obed Swamp
A one-day workshop with a topic "The Return of Ibis Bird" within the international project organized by the "Young Researches of Serbia". EXPEDITIO was invited to organize a one-day workshop. Our idea was to make paper birds and place them around the swamp, symbolozing in that way the return of birds in their habitats. Sponsor: EXPEDITIO
An international architectural workshop with the topic "Revitalization of the Town of Perast". The second expedition in Perast made a step further compared to the research conducted in 1997. Based on the collected data the participants gave proposals for the possible revitalization of Perast. Some of the issues that students considered were: the town lighting, public places, reconstruction of ruined objects, seafood production, reconstruction of the waterfront etc. Sponsor: OPEN SOCIETY FUND, Belgrade

redpajama_set_name: RedPajamaCommonCrawl


text:
Earthquake in Los Angeles – Magnitude 4.4 earthquake felt in San Diego
By Lily Casas | March 16, 2010
Photo from Florian via Flicker
If you felt your bed shake early this morning, you weren't dreaming, a magnitude 4.4 earthquake struck at 4:04 am just 10 miles east of downtown Los Angeles and there were reports of people feeling it all the way here in San Diego county. There were no immediate reports of damage or power outages but about an hour after the quake the California Highway Patrol received reports of damage to the 5 freeway in the city of Downey, south of downtown.
The quake was centered one mile east of Pico Rivera. The damage was minor and only consisted of some broken concrete in a section of the roadway that was already under repair. The damage did cause some backup in traffic when two lanes were closed.
The earthquake mostly affected the downtown LA area, interrupting elevator service in the new police department headquarters across from city hall. Mostly there were reports of pictures falling from walls. Although the earthquake was not very noteworthy, it was felt over a large part of Southern California, south to San Diego, west to Santa Monica and east to San Bernardino county.
San Diego county has had it share of earthquakes recently but many go unnoticed. Last Wednesday, a 3.5 magnitude earthquake shook the Lake Henshaw area in north county at around 5:40 pm. Just this past Saturday morning a 4.2 magnitude earthquake struck about 14 miles east of Julian and yesterday a 1.4 quake struck at 2:00 pm, 4 miles from La Mesa according to data by the U.S. Geological Survey.
Earthquakes happen everyday and are just a part of life here in Southern California. Seismologist, Kate Hutton, stated that today's earthquake was unlikely a precursor to a larger quake and the chances of that diminish over time. According to the USGS, a magnitude 4.4 earthquake is considered a light quake felt mostly by people indoors with only dishes, windows or doors disturbed. The vibrations mostly feel like the passing of a large truck.
Related Itemscalifornia earthquakeearthquakeearthquake los angelesla earthquakepico riverasan diego earthquakeUSGS
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text:
Reading: Shehnaaz and Aditya Shukla remembers Sidharth Shukla on 42nd birth anniversary
Uitvconnect : Breaking News, India News, Sports News and Live Updates > Blog > Entertainment > Bollywood > Shehnaaz and Aditya Shukla remembers Sidharth Shukla on 42nd birth anniversary
EntertainmentBollywood
Shehnaaz and Aditya Shukla remembers Sidharth Shukla on 42nd birth anniversary
Mumbai, Dec 12 (UiTV/IANS) – Bigg Boss 13 contestant and social media sensation Shehnaaz Gill remembered late actor Sidharth Shukla on his birth anniversary on Monday.
Sidharth, who passed away in 2021, would have turned 42. Shehnaaz took to Instagram to share a string of throwback pictures of Sidharth in which he could be seen smiling.
She captioned the images: "i will see you again. 12 12."
The actress, on her Instagram stories, also shared a few pictures of her celebrating his birthday with a few cakes which had Sid written on them.
Popularly known as SidNaaz, Sidharth ad Shehnaaz became friends on the set of Bigg Boss 13. Even after growing close in the show, the two never officially acknowledged being a couple.
Actor Aditya Shukla on Monday recalled the deep bond he shared with his counsin late Sidharth Shukla on the late actor's birthday.
Born on December 12, 1980, Sidharth was known for his stint in 'Bigg Boss 13', besides his perfomance in the daily show 'Balika Vadhu'. The sudden demise of the 40-year-old on September 2, 2021 left his fans and co-stars shocked and saddened.
Aditya, who is currently seen in 'Naagmani' feels Sidharth will always be the undisputed king. Speaking about his greatest takeaway from Siddharth, Aditya says: "He was like a king. No matter what he did, he was ready to face the world and do whatever he felt was right. That is the main quality I have learned from him."
He further adds: "Sidharth and I were always there for each other. It wasn't a relationship where we met everyday or spoke everyday. But we both knew we had each other's back. The last time we've properly met was after he had met with an accident in Andheri. We used to speak over the phone and meet occasionally. Along with my acting career, I am also a certified deep sea diver. Since 2012, I was mostly on the ship for diving. But whenever I felt like talking or meeting him I used to call him up."
"No matter what time it was, I used to call and tell him about wanting to ride his Hayabusa bike and he would refuse and then after a few days out of the blue he would call me and tell say 'neeche aa' and would handover the bike keys to me. Miss him all the more now as he is not there when I am working in a show. He would have been the happiest person to see me facing the camera."
Asked whether he took up acting because of Sidharth? Aditya said, "Not really. I always wanted to be an actor for my mom. She always wanted to see me on the big screen. Yes I always idolize him and he did motivate me in different ways to take up acting."
To a question on a memorable incident with his cousin, he said, "There are a lot actually. In 1993, when my sister was born, I used to stay with him in Bombay central as the hospital was next to his society. So, he used to take me to the market and play with me in the society as well. I have got a lot of good memories with him which I will cherish forever."
At last, he says his name is still alive in his fans' hearts and will always be remembered for his work.
"His name will always be alive. The reason for his fandom is his attitude. Like I said before, he was like a king and the fans love his attitude. There is no other Sidharth Shukla and will never be. I miss him everyday," Aditya added.
Reliance Entertainment celebrates 7 Oscar nominations for 'The Fabelmans'
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Salman's 'Kisi Ka Bhai Kisi Ki Jaan' teaser leaked in SRK's 'Pathaan' screening


text:
Nicolas Petit, né le  à Longjumeau, est un dirigeant d'entreprise français.

Entre 2011 et 2017, il a été directeur général chargé du marketing et des opérations de Microsoft France entre 2011 et 2016 puis vice-président, Global, Marketing & Operations de Microsoft Corporation. Depuis 2018, il dirige un cabinet de conseil spécialisé dans la transformation digitale des organisations.

Il est également professeur affilié à l'Université Paris Sciences et Lettres (PSL), notamment au sein de l'École nationale supérieure des mines de Paris et de l'Université Dauphine-PSL, spécialisé sur les questions de transformation numérique des organisations.

Biographie

Jeunesse et études
Originaire d'Arpajon dans l'Essonne, Nicolas Petit est lauréat du Concours général (section Littérature) en 1993. Ancien élève du Lycée Louis-le-Grand, il est diplômé avec le titre de lauréat de l'Institut d'études politiques de Paris en 1998 (section Service Public) puis intègre HEC Paris en 1998 en tant que major du concours d'entrée en 2ème année. Il poursuit en parallèle des études d'histoire médiévale à l'université Paris-I Sorbonne.

En 2020, il est reçu fellow du Cycle International de l'Institut des Hautes Etudes pour l'Innovation et l'Entreprenariat de l'Ecole Nationale Supérieure des Mines de Paris.

Parcours professionnel et académique
Après un début de carrière dans le conseil en stratégie au sein de cabinets anglo-saxons (McKinsey, Arthur D. Little) aux États-Unis et au Royaume-Uni, il rejoint Microsoft France en 2005. Promu directeur de la division mobilité en 2006, il participe activement à la structuration de l'écosystème applicatif mobile et à la démocratisation du marché du smartphone en France.

En 2010, il est nommé directeur marketing de la division Grand Public et Online. Il apparaît comme le "Mr Internet et Grand Public" du géant de Seattle dans les médias et forums européen et lance notamment le moteur de recherche Bing en France, en nouant plusieurs partenariats stratégiques avec la Bibliothèque nationale de France ou Pages Jaunes valorisant le tissu culturel et économique national.

En 2011, il est nommé au sein du comité de direction de Microsoft France au poste de Directeur Général & Chief Operating Officer de Microsoft France. Il a notamment pour responsabilité la supervision de l'ensemble des activités produits et services de l'organisation, le marketing, la communication, les opérations et le service client.

Partisan d'une transformation profonde de l'organisation et d'une communication plus transparente, Nicolas Petit fait évoluer les pratiques marketing, commerciales et partenariales de l'éditeur de logiciel américain. Il pilote la montée en puissance du cloud computing (Office365, Microsoft Azure, Microsoft Dynamics...) et l'introduction de Windows 10 ou de la gamme Surface positionnant Microsoft sur le marché des ordinateurs hybrides haut de gamme.

Artisan d'une stratégie partenariale avec les clients de l'éditeur de logiciels et d'une relation renouvelée avec l'univers des start-ups et des directions métiers, il conduit entre 2013 et 2016 la direction d'un grand chantier de transformation interne, notamment illustré par une attention renforcée à la numérisation des fonctions métiers et par une politique d'ouverture assumée vers l'open source et de nouvelles communautés techniques.

Il poursuivra la transformation du groupe au niveau international à partir de 2016 en tant que vice-président, Global Marketing & Opérations au siège de Microsoft Corporation à Redmond, États-Unis.

En 2017, il quitte Microsoft pour rejoindre le groupe Altice en tant qu'Executive Vice-President, Marketing, Product & Digital et membre du comité exécutif du groupe de télécoms et média international.

En 2018, il quitte le monde des entreprises pour fonder native, un cabinet de conseil spécialisé sur la transformation digitale des organisations, qui accompagne dirigeants du monde des entreprises et des start-ups dans leur stratégie technologique.

En parallèle, il rejoint l'Université Paris Sciences et Lettres d'abord comme professeur invité au sein de l'Institut des Hautes Etudes pour l'Innovation et l'Entreprenariat, puis fonde le Certificat Exécutif "Digital Native - Transformation Numérique des Organisations" au sein de l'École nationale supérieure des mines de Paris, décliné ensuite au sein de l'Executive MBA de l'Université Paris-Dauphine où il est nommé enseignant en 2020.

Engagements
Militant en faveur d'une collaboration renforcée entre les acteurs technologiques européens pour rivaliser avec les puissances technologiques américaines et chinoises, Nicolas Petit est sélectionné en 2011 dans le programme European Young Leaders - 40 under 40 de la Commission Européenne et rejoint par la suite le conseil d'administration du think tank européen EuropaNova. En 2013, le magazine américain Forbes le sélectionne dans sa liste annuelle "Next Generation CEOs".

En 2015, il rejoint le think tank Les Transformers créé par BPI France pour accélérer la transformation numérique des entreprises françaises. Il est également administrateur de plusieurs start-ups dans le domaine du gaming, de la santé et du logiciel.

Distinctions et prix
•   Choiseul 100 (top 100 French economic leaders) – 2014 to 2017.

•   Council for the US and Italy, Young Leaders Conference – 2015.

•   Forbes "The Next Generation of CEOs" global top 10 list – 2013.

•   European Young Leaders « 40 under 40 » – 2012 (European Commission / Friends of Europe)

Références

Naissance en 1976
Naissance à Longjumeau
Entrepreneur français

redpajama_set_name: RedPajamaWikipedia


As part of a redesign for the Evergreen Railings website I spent a couple hours hanging around the shop while Leif welded up a storm. Since you can't really look at what your shooting, welding is hands down one of the hardest things I've ever tried to photograph - also one of the most rewarding. Took a lot of bad photos before dialing in the proper exposure/timing for the shutter, but once I had it figured out I couldn't get enough. Planning to do another shoot soon to put together a gallery show of just welding.


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text:
\section{Acknowledgements}

\bibliographystyle{ACM-Reference-Format}

\section{Conclusion}
\label{sec:conclusion}

In this article we have introduced \textit{WikiRecNet}, a neural-based model which aims at recommending Wikipedia articles to editors, in order to help them dealing with the sheer volume of potential articles that might need their attention.  Our approach uses representation learning, i.e., finding alternative ways to represent the Wikipedia articles in order to produce a useful recommendation  without requiring more information than the previous articles edited by targeted users. For this purpose, we used Doc2Vec~\cite{doc2vec} for a content-based representation and GraphSage~\cite{graphsage}, a graph convolutional network, for a graph-based representation.

\textit{WikiRecNet} architecture is composed of two networks, a candidate generation network and a ranking network, and our implementation is able to deal with larges volumes of data, improving existing implementations that were not capable to work in such scenarios. Also, our approach does not need to be retrained when new items are added, facilitating its application in dynamic environments such as Wikipedia. To best of our knowledge, this is the first recommender system especially designed for Wikipedia editors that takes in account such applications constrains, and therefore, can be applied in real world scenarios.

In order to contribute to the community, we provide our code and the graph embedding of each Wikipedia page used in this experiment\footnote{Embeddings in other languages would be also available under request.} available in a public repository, as well as a working demo that can be tested by the Wikipedia editors community\footnote{\url{https://github.com/digitalTranshumant/WikiRecNet-ComplexRec2020}}. With respect to text embeddings, there have been important progresses in the latest years, so another idea for future work will be testing models like BERT \cite{devlin2018bert} or XLNet \cite{yang2019xlnet}.

\section{Acknowledgments}
The author Denis Parra has been funded by the Millennium Institute for Foundational Research on Data (IMFD) and by the Chilean research agency ANID, FONDECYT grant 1191791.

\section{Introduction}

Wikipedia is edited by hundreds of thousands of volunteers around the world. While the level of expertise, motivations, and time dedicated to that task varies among users, most of them experience challenges in deciding which articles to edit next. For example, many experienced users have huge backlogs\footnote{\url{https://en.wikipedia.org/wiki/Wikipedia:Backlog}} of work with a large number of articles to improve or review. Prioritizing the articles in this backlog, as via a personalized article ranking system, would potentially be of great help for these editors. On the other hand, newcomers might experience difficulties deciding what do to after their first contribution, as evidenced by the many efforts to understand how to improve the retention of newcomers~\cite{newcomers1,newcomers2}.

While previous work on recommendations in Wikipedia has focused on finding articles for translation~\cite{wulczyn2016growing} or content to be added to existing articles~\cite{piccardi2018structuring}, there are still important unsolved problems: i) creating a \textit{scalable} recommender system that can deal efficiently with the large number of Wikipedia editors (over 400K monthly just in the English Wikipedia) and articles~\cite{wikistats2} ii) having good coverage of articles beyond just the most popular articles, and, iii) being able to provide good recommendations for newcomers, facing the classical user cold-start problem~\cite{schein2002methods}.

To address these problems, we have created an efficient and scalable implementation of a state-of-art convolutional graph embedding algorithm~\cite{graphsage} that is able to deal with the large Wikipedia article graph. We combine this with a document embedding model that allows us to learn representations for articles and editors, and does not require retraining when new users are added in the system. With only a few edited articles then, the system is able to produce personalized recommendations, similar to Youtube deep recommendation model~\cite{Covington:2016:DNN:2959100.2959190}. We test our algorithm in English Wikipedia (the largest one with almost 6 million article
showing that we can overcame well-established content-based filtering methods as well as collaborative filtering approaches. Moreover, we evaluate our recommendation measuring the top-100 items, to support a robust evaluation against popularity bias~\cite{valcarce2018robustness}.

In summary, the main contributions of this paper are: \emph{(i)} Introduce a model which learns representations (graph and content-based) of Wikipedia articles and makes personalized recommendations to editors; \emph{(ii)} Evaluate it with a large corpus, comparing with competitive baselines
\emph{(iii)} and release a scalable implementation of GraphSage, a state-of-art graph embedding system, that in previous implementations was unable to deal with the large graph of Wikipedia page\footnote{\url{https://github.com/digitalTranshumant/WikiRecNet-ComplexRec2020}}.

\section{WikiRecNet Description}
\label{sec:wikirec}
Here we introduce \textit{WikiRecNet}, a scalable system for providing personalized article recommendations in Wikipedia,  built on top of GCN and Doc2Vec. The  design of our solution is inspired by a classic \textit{Information Retrieval} architecture. First we represent users by the articles that they edited, then  we  generate a list of candidates from the article pool by comparing that user representation with the article representations. Next, we sort the article candidates accordingly to the user preferences and generate a list of \textit{top-n best candidates} recommendation.

\subsection{Article and user representation} The primary challenge for our system is producing good user and article representations. It is an especially big problem for user representation since most of Wikipedia contributors do not fill any additional information about themselves except their login credentials \footnote{\url{https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_is_anonymous}}, and around 28\% of all revisions in our  English Wikipedia dataset, are done by anonymous users~\cite{wikistats2}. The only useful information that could uniquely characterize the user is the history of his editions. Hence, most of our efforts were dedicated to learning articles' representations, and then representing the user based on the articles edited. One effective approaches to construct good user and item representations is to learn them with recommendation supervisio
~\cite{Covington:2016:DNN:2959100.2959190,Ying2018GraphCN}. However, it is not possible to follow this approach due to the lack of the required comprehensive-enough dataset of previous interactions.  History of users editions in Wikipedia is far from exhaustive (88\% of users of English Wikipedia have done less than 5 major editions~\cite{wikistats2}) and too sparse, in a way that it is hard to model user's area of interest. Therefore, the additional challenge is to conduct representation learning~\cite{bengio2013representation} in an unsupervised way in relation to our final task.

\begin{figure}
	\includegraphics[width=0.9\columnwidth]{figures/Ranking.png}
	\caption{Candidate Ranking: user  history along with candidate are passed through articles' representation database (Embedding Layer) and then through several fully-connected layers to train in the log-regression setup.}
	\label{fig:ranking}
\end{figure}

\begin{table}
	\caption{Performance of different algorithms for K-NN search. All tests were conducted with English Wikipedia articles ($|V|=5,251,875$). Setup is measured in seconds. Secs. req. means seconds per request.}
	\centering
	\setlength\tabcolsep{3pt}.
	\begin{tabular}{l|c|c|c|c}\hline
		Algorithm & Setup & Secs./req. & Recall & MRR  \\
		\hline
		Exact search & 3.91 & 0.81 & 0.224 & 0.0220 \\
		IVF & 207.02 & 0.07 & 0.206 & 0.0212 \\
		HNSW & 232.68 & 0.04 & 0.224 & 0.0220 \\
		LSH & 472.31 & 0.15 & 0.215 & 0.0219\\
	\end{tabular}
	\label{tab:my_label}
\end{table}

\begin{table}
	\caption{Specifications of built Wikipedia Graph}
	\begin{tabular}{lc}
		\hline
		Specification   & English Wikipedia \\
		\hline
		Amount of vertices ($|V|$)      & 5,251,875 \\
		Amount of Edges ($|E|$)       & 458,867,626 \\
		Average Degree ($\overline{d_{all}}$) & 174 \\
		Median Degree ($\widetilde{d_{all}}$) & 60\\
		Approx. Diameter (D) & 23\\
		Amount of labeled nodes & 4,652,604\\
	\end{tabular}
	\label{tbl:graph}
\end{table}

\subsection{Candidate Generation} Similar to YouTube's deep learning recommender~\cite{Covington:2016:DNN:2959100.2959190}, \textit{WikiRecNet} first generates candidates for a final personalized ranking in a second stage. To generate candidates we first calculate representation vectors (content-based and graph-based) for all articles in our dataset, a process conducted off-line which is presented as \textit{Representation Learning} in Figure \ref{fig:candidate-generation}.  Then, for every user we define her representation as an  aggregation of representation vectors of corresponding articles that were edited by this user. Next, we conduct Nearest Neighbors search with user representation as a \textit{query} in the articles' representation database, a procedure we call \textit{Candidate Generation} and which is conducted online, as shown in Figure \ref{fig:ranking}.

\vspace{12pt}
\noindent
\textbf{Content-based articles representation: Doc2Vec.} For learning the content-based article representation, text features are needed to be extracted first. This can be conducted with traditional document vector space model \cite{salton1975vector} or by using word embeddings such as Word2vec \cite{word2vec} and GloVe \cite{pennington2014glove} and performing an additional step of aggregation. Another option is using directly a full text embedding model and with that goal we use Doc2Vec~\cite{doc2vec}. There are two distinct approaches for learning document embedding with this model. One is Paragraph Vector Distributed Bag-of-Words model (PV-DBOW) model, which is based on word2vec's Continuous Bag-of-Words approach~\cite{word2vec} but instead of word input it accepts paragraph vector and predicts context words for this paragraph. In the second approach, Distributed Memory (PV-DM), which is based on word2vec skip-gram model, the model predicts middle word based on context and paragraph vector given as input. Later on this paper (Section \ref{sec:results}) we show that PV-DBOW is the best fit for our task. We train Doc2Vec-DBOW model on the Corpus of all Wikipedia articles in a given language. Output vectors of Doc2Vec are being passed as input features to the GNC.

\vspace{12pt}
\noindent
\textbf{Graph-based article representation: GraphSAGE.} GraphSAGE has been used as GCN due to its ability to learn with an inductive approach and construct embeddings for unseen nodes. During the pre-processing of the input dataset --snapshot of Wikipedia Dataset-- we create a graph $G(V, E)$ where $V$ denotes the set of articles, and $E$ the set of links between them. GraphSAGE utilizes structural knowledge from graph $G$ and produces new vectors that preserve both text and structural representations.  Due to the inductive nature of GraphSAGE architecture, we do not need to retrain the model every time after adding a new article into the database, this is very important for applying \textit{WikiRecNet} in real scenarios, where new articles are  constantly added~\cite{wikistats2}.

After producing the document vector and updating the Graph $G$ structure, we can run GraphSAGE model as is, with already trained weights. GCN is a multi-layer network, where each layer can be formulated as:
$$H^{(l+1)} = \sigma(\tilde{D}^{-\frac{1}{2}}\tilde{A}\tilde{D}^{-\frac{1}{2}}H^{(l)}W^{(l+1)}) $$

\noindent
where $\tilde{A} = A + I$ is the  adjacency matrix with self-connections ($I$), $\tilde{D}=\sum_{j} \tilde{A}_{ij}$, $W$ are trainable weights and $H$ is the output of previous layer or $H^{(0)} = X$ is input, $X$  represents node features. An intuitive explanation of this process is that each node collects features of its neighbors that were propagated through trainable filters (convolutions) so called, message passing. On each step node collects knowledge of its neighborhood and propagates its state further on the next step. Thus, properties of 1st, 2nd, ..., nth proximity are being incorporated into node's state along with preserving original features of node's community.

\noindent
\textbf{Optimizing candidate retrieval}. In serving time, recommendation candidates will be produced by applying K-Nearest Neighbors (K-NN) search to find the most similar articles to the user representation vector in the pre-computed database of all articles' representations. K-NN search is one of the main parts of candidate article generation, since its performance in terms of time and resource consumption is very critical for online recommendation in a high-load system. We conducted experiments with different optimizations for K-NN candidate search using FAISS library~\cite{JDH17} : Locality-Sensitive Hashing (LSH), Inverted file with exact post-verification (IVF), Hierarchical Navigable Small World graph exploration (HNSW). Our tests showed that HNSW gives the best speed along with exactly the same recall and MRR as exact search, so with no trade-off in performance we achieved 20x times improvement in speed. Results of these experiments are shown in Table \ref{tab:my_label}.

\subsection{Ranking of Candidate Articles}

After learning content and graph-based representations for Wikipedia articles, in the second part of our system  we are trying to model user preferences based on the previous edit history of Wikipedia contributors. With given previous editions and articles, we produce  a relevant a list of candidates, ranked by its relevance for a given user. Our model is  trained on binary labels - \textit{relevant / not relevant} (logistic regression), as shown in Figure \ref{fig:candidate-generation},  but on serving time it will produce probabilities of user interest, which are used as a preference ranking score.

This approach is inspired by Pointwise ranking~\cite{Liu:2009:LRI:1618303.1618304} and is implemented in many similar recommender systems: YouTube\cite{Covington:2016:DNN:2959100.2959190}, eBay\cite{Brovman:2016:OSI:2959100.2959166}. The model is shown on Figure \ref{fig:ranking} and consists of several fully-connected layers with Batch Normalization and ReLU activation after each layer except for the last layer, where sigmoid activation is used. The final model's architecture was selected as follows:
$ 1024 \text{ ReLU -> }  512 \text{ ReLU -> } 256 \text{ ReLU} $.
As input model accept a concatenated vector of user and candidate representations.

\textbf{Preference score} We define our preference ranking score as the probability that a user $u$ finds a wikipedia article $a_i$ relevant:
\begin{equation}
score(u,a_i) = P(a_i = relevant | u ) = \frac{1}{ 1+ e^{-\Phi(a_i, u) }}    \label{eq:preference score}
\end{equation}
where $u$ represents the user, $a_i$ a candidate wikipedia article, $A$ is the set of all articles to be ranked, and $\Phi(\cdot)$ a weighted sum of the values in the last network layer of the \textit{Candidate ranking} neural network, shown in Figure \ref{fig:ranking}. We train the model with a traditional loss for a binary logistic regression.

\section{Related work}
\label{sec:ref}

There are several projects trying to solve the task of recommending items to users at real-world scales of millions of users and millions of items. For instance, Ying et al. for Pinterest ~\cite{Ying2018GraphCN} created an extension of GraphSAGE~\cite{graphsage}, a type of Graph Convolutional Network~\cite{gcn} (GCN); researchers at YouTube~\cite{Covington:2016:DNN:2959100.2959190} built a system based on regular deep neural networks that jointly learns users' and items' representations from users' previous history of views. However, in both examples, the model  learns in a supervised setup, whereas we lack a sufficiently comprehensive dataset of previous interactions because 94\% of Wikipedia contributors are associated with less that 10 interactions in last 3 years~\cite{wikistats2}. eBay's recommendation system covers a similar gap by using TF-IDF for similar item search, which does not require training~\cite{Brovman:2016:OSI:2959100.2959166}.

On the document representation task, we can highlight several approaches: Doc2Vec\cite{doc2vec} is method for obtaining content-based representations of paragraph or longer text in vector space. However, one main advantage of our dataset is the availability of structural knowledge~\cite{consonni2019wikilinkgraphs} - i.e. links among articles that could potentially tell more about the article beyond its content. Those links can be represented as a graph, where nodes are articles and edges are links between them. Thus, the task of learning document representations can be transformed into learning the representation of a node in the graph. Node2vec~\cite{GroverL16} is a recent approach to learn such a representation. However, its scalability is still limited~\cite{fastnode2vec} and the main drawback for our use case is the necessity of full retraining after changes in the structure of the graph. Node2vec also omit the content part of articles (node features), which is a huge part of our dataset.

GCN~\cite{gcn, NIPS2015_5954} are a recent approach to solve many machine learning tasks like classification or clustering of a graph's nodes via a message-passing architecture that uses shared filters on each pass. It combines initial node features and structural knowledge to learn comprehensive representations of the nodes. However, the original GCN  architecture is still not applicable to large-scale graphs because it implies operations with a full adjacency matrix of the graph. To tackle these limitations, GraphSAGE model was introduced~\cite{graphsage} in a way that only some fixed-sized sample of neighbors is utilized on the convolutional Layer. Because of the fixed-size samples, we also have fixed-sized weights that are generalized and could be applied to a new, unknown part of the graph or even completely different graph. Thus, with inductive learning, we can train the model on a sub-graph, which means less computation resources are required, and evaluate generalization on the full graph.

\section{Results}
\label{sec:results}

Results of the evaluation are presented in Table \ref{tbl:results}. We first describe the competing methods:

\textbf{Baselines}. We  used two well established methods. The first one is BM25\cite{Robertson:2009:PRF:1704809.1704810}, a probabilistic method used on information retrieval but also applied for content-based filtering in the area of recommendation~\cite{parra2009collaborative}. A second baseline is implicit feedback collaborative filtering optimized with Alternative Least Squares (ALS)~\cite{Hu08collaborativefiltering}.

\textbf{K-NN recommender}. In addition, we implemented a simple K-NN recommender where the Wikipedia articles are represented by the Doc2vec vector embeddings. Each user $u$ is represented by the articles she has edited, and we test two forms of aggregation to represent the user model: merging the user-edited articles (\textit{merge}) and calculating the mean at each dimension of the document (\textit{mean-pool}). We rank recommended articles by cosine similarity.

\textbf{Aggregations}. Finally,\textit{WikiRecNet} is presented in 5 versions by varying the type of aggregation of articles to represent the user model (merge, mean-pool, max-pool), as well as the method for ranking (cosine similarity and Deep-Rank).

The results in Table \ref{tbl:results} show that WikiRecNet,   using \textit{merge} aggregation and \textit{Deep-Rank} ranking, outperforms the other methods in all metrics. We highlight the following the aspects in the evaluation:

\begin{itemize}
    \item ALS implicit feedback collaborative filtering performs the worst among all methods. This result must be due to the extreme high sparsity of the dataset.
    \item BM25, despite being a simple and traditional content-based filtering method, performs well and remains very competitive.
    \item The simple K-NN based on Doc2Vec representation performs better than ALS, and mean-pool reports better results than merge but only at higher ranking positions (MAP@50, nDCG@50, Recall@50).
    \item Among the WikiRecNet variations, the max-pool aggregation seems to be the least helpful. In terms of nDCG@50 and nDCG@100 (the metric most robust to popularity bias ~\cite{valcarce2018robustness}), merge aggregation seems more effective than mean-pool, and then the combination with DeepRank produce the best performance, with a 100\% increase compared to the Doc2vec mean-pool reference method.
\end{itemize}

\section{Experiments}
\label{sec:Experiments}
We worked with the English version of Wikipedia not only because is the most popular one. In addition, is the most challenging in terms of data processing, and if our system is able to deal with the largest Wikipedia it would be easy to apply later in smaller projects.

\subsection{Dataset}

All data used  has been downloaded from the official  Wikimedia Dumps~\cite{wikidumps} which  are snapshots of the full Wikipedia.  Some of the objects in the dump (like articles' links) are stored in SQL format, others, with  deeper structure (like articles' text) are stored in XML.

First of all, for representation learning we built a graph $G(V, E)$, where the set of nodes $V$ is the set of all Wikipedia pages belonging to article namespace\footnote{https://en.wikipedia.org/wiki/Wikipedia:Namespace} and $E$ is the set of directed links between them. The SQL dumps of \emph{page}, \emph{pagelinks}, and \emph{redirects} tables were parsed to organize this data. During pre-processing stage, all links to redirect pages\footnote{https://en.wikipedia.org/wiki/Wikipedia:Redirect} were replaced by their actual destinations. "Category pages", that consists only of links to other pages and do not have their own content, were detected and filtered out.
We used Apache Spark and GraphX for parallel parsing of SQL dumps and discovering and cleaning Article Graph respectively. The output Graph was converted into binary format with graph-tool~\cite{peixoto_graph-tool_2014} to achieve fast processing (see Table \ref{tbl:graph}).
For extracting the articles' texts we took the latest revision\footnote{Article's revision is a specific version of article's content after each  \textit{modification}} per each article from XML dump.  We used \textit{Gensim}~\cite{rehurek_lrec} to tokenize and lemmatize text and prepare for the Doc2vec training.

\begin{comment}
\begin{figure}[t]
\centering
\begin{subfigure}
\includegraphics[scale=0.6]{figures/edition-hist-en.png}
\caption{Amount (logarithmic) of contributors by count of edited articles since 1 January of 2015}
\label{fig:users-editions}
\end{subfigure}

\begin{subfigure}
\includegraphics[scale=0.6]{figures/users-diversity-en.png}
\caption{Distribution of contributors' diversity\cite{diversity} with amount of modified articles > 5 calculated based on content vectors obtained with Doc2Vec}
\label{fig:users-div}
\end{subfigure}
\end{figure}

\end{comment}

To the facilitate the evaluation in an end-to-end fashion we reorganized the data into a \textit{revisions-per-user} dataset. Only revisions that were created after Jan. 2015 were kept in this dataset, so our recommendations that are based on the latest snapshot of article graph (Oct. 2018) will not recommend too many articles that did not exists on that moment.

We found that 88\% of contributors are not regular users, since they edited fewer than 5 different articles for selected dates. We also calculated diversity ~\cite{diversity} of users' contribution based on vector representations obtained from Doc2vec. The set of contributors that fits to our needs has mostly edited from 5 to 40 different articles, though diversity of those articles is rather high. That is the main cause our representations cannot be trained against this data like it was done in previous work~\cite{Covington:2016:DNN:2959100.2959190}. Unlike the work by Covington et al.~\cite{Covington:2016:DNN:2959100.2959190}, our training dataset is small (around 60K users) and users' areas of interest are very diverse.

\subsection{Training}
For all training experiments with GraphSAGE we generated a sampled adjacency matrix based on Articles' graph $G$. The width of the adjacency matrix was determined by our experiments, based available memory resources as well as on graph statistics (Table \ref{tbl:graph}). We selected $128$ as maximum amount of neighbors in this matrix. If a node had more than that, then we used random subsampling.
Our GCN architecture consists of two convolutional layers.
On each convolutional step we picked a random sample of $25$ neighbors from this adjacency matrix. This 25-neighbors sample is being resampled on each new batch. For better generalization we used a batch size of 512, since experiments with dropout between convolutional layers led to no improvement in generalization. We set the size for all output vectors to 512 considering a balance between better resolution and available memory.

Document representations from Doc2Vec-DBOW, trained with vector size $300$ and window size $8$, were passed as initial node states and graph edges played the role of labels when the model was trying to predict those edges. We utilized max-margin loss~\cite{Ying2018GraphCN}, as target for training GraphSAGE in link-prediction setup. Model parameters were tuned with the Adam optimizer\cite{DBLP:journals/corr/KingmaB14}.
 \begin{align}
 J(z_u z_i) = E_{v_n \sim P_n(u)} max \{ 0,  z_u \cdot z_{v_u} - z_u \cdot z_i + \Delta \}
 \label{eq:max-margin}
 \end{align}

 For training the ranking model, a dataset from users' history was constructed. As input this model takes 5 articles edited by a user ( representing users' preferences) and 1 candidate that might interest the user. The model tries to predict the probability of relevance of this candidate to the current user. Those 6 input articles are passed through an \textit{Embedding Layer} populated with representations received from GraphSAGE and then concatenated into one vector. We chose positive candidates from actual user history and generated negative candidates with kNN search on constructed articles' representations. Logistic (binary cross-entropy) regression with class-weights (due to high class imbalance) was used as loss function.

 \subsection{Evaluation}

 To prepare the evaluation dataset, we subsampled windows of size 10 from user's history (from users that were not previously used for training or testing the Deep Ranking model). Our assumption if that the first 5 articles denoted users' area of interest. To compute a single user vector we took element-wise average of representations from the first 5 articles (GraphSAGE representations). We were trying to predict the rest 5. Algorithm can be expressed as follows:
(i) take first 5 articles per user. Calculate average of their embeddings vectors, output this as the user vector representation, (ii) generate candidates by nearest neighbors search of user representation, (iii) sort candidates according to ranking algorithm and select the top $K$. In our evaluation we compare two ranking techniques: sort by cosine similarity, and sort by probability from Deep Ranking model, and (iv) compare Top-K recommendations with the 5 articles in the test set (from second half of the sampled window).

To measure the results we used several metrics: mean average precision (MAP), normalized discounted cumulative gain (nDCG)\cite{Baltrunas:2010:GRR:1864708.1864733} and Recall@k~\cite{cremonesi2010performance}. We calculate these metrics at high \textit{k} values, $k=50$ an $k=100$. Unlike traditional research on top-k recommendation systems usually focusing on small \textit{k} values (\textit{k}=10,20,30), we are specially interested in preventing popularity bias, i.e., having WikiRecNet biased to recommend mostly popular items. Valcarce et al.~\cite{valcarce2018robustness} showed recently that usual top-k ranking metrics measured at higher values of \textit{k} (50, 100) are specially robust to popularity bias, and that is why we use them here.

redpajama_set_name: RedPajamaArXiv


text:
A-Z List of Dishonest Business/Companies »
Dishonest clinics in Singapore [Certified Dishonest]
Author Topic: Dishonest clinics in Singapore [Certified Dishonest] (Read 6505 times)
More clinics under probe for possible cheating
MOH has asked the police to look into more questionable subsidy claims under Chas
Jul 4, 2016, 5:00 am SGT
Salma Khalik
Senior Health Correspondent
More clinics are under probe for possibly cheating the Ministry of Health (MOH) when claiming subsidies for patients under the Community Health Assist Scheme (Chas).
Two dental clinics have already been suspended from the scheme. The suspension will start on Friday.
MOH told The Straits Times that it has asked the police to look into more questionable claims, made by an unspecified number of other clinics, under Chas.
The scheme lets private clinics treat patients who are eligible for a government subsidy, and claim the subsidy from the ministry.
Last week, MOH announced the suspension of the two dental clinics - Phoenix Dental Surgery clinics in Ang Mo Kio and Marine Parade - from Chas. It had filed a police report against them for possible fraud on April 22.
Under Chas, MOH has to give a clinic 15 days' notice of termination, so the clinics facing suspension are on Chas until this Friday.
The ministry told The Straits Times it has "also referred other clinics to the police for further investigation". But it would not say if they are dental or general practice (GP) establishments. About 1,500 clinics are on the Chas scheme.
The possible cheating cases surfaced via regular audits by MOH and a patient's complaints.
In the case of the two dental clinics, the MOH spokesman said: "While we were auditing the clinics, we also received a patient complaint that Phoenix Dental had submitted claims for procedures which had not been done for the said patient."
Associate Professor Patrick Tseng, Singapore's chief dental officer, said: "MOH takes a serious view of fraudulent claims and unlawful practice behaviour, and we will take necessary action if we suspect any such activity."
The audits have turned up cases of non-compliance, but many are unintentional or administrative errors, such as putting down the wrong date for a procedure. They have also turned up more questionable "errors", such as:
Doing a simple procedure but making a claim for a more complex, and hence more expensive, treatment.
Making claims for procedures that are not eligible for subsidy, by classifying it as a different procedure that is subsidised.
Making a full claim although the treatment has not been completed.
Claiming for a procedure that was never done.
The MOH spokesman said the ministry will recover any subsidies paid out through incorrect claims. Last year, Chas paid out $167 million in subsidies to GPs and dental clinics for treating 650,000 Singaporean patients.
Source: http://www.straitstimes.com/singapore/more-clinics-under-probe-for-possible-cheating


text:
Ferrari F12tdf Limited Edition, Developed by Three Focus Points
F12tdf Ferrari is the ultimate expression of the F12 Berlinetta which will be built in a limited run of 799 units. F12tdf built in honor of the Tour de France, the legendary endurance road race that Ferrari dominated in the 1950s and 1960s, particularly with the 1956 250 GT Berlinetta which won four consecutive editions.
Ferrari F12tdf developed with a focus on three areas including the engine, aerodynamics and vehicle dynamics. As a result, the car has a captivating performance in terms of acceleration, road holding and agility.
Captivating performance of Ferrari F12tdf is powered by a 6.3-liter naturally-aspirated V12 engine derived from the F12 Berlinetta which delivers 770hp. Ferrari also increase the ratio of front tires of this car is 8 percent larger than the rear tires. This is to get a more dynamic performance. This car is also equipped with an innovative rear-wheel steering system called Virtual Short Wheelbase.
This system is integrated with the other vehicle dynamic control systems, so as to guarantee the steering wheel response times and turn-in of a competition car while increasing stability at high speed. Ferrari F12tdf can also increase the speed when cornering, because the increase in downforce.
With light weight, this car is Able to sprint from 0 to 100 km/h in 2.9 seconds and from 0 to 200 km/h in just 7.9 seconds. This light weight is obtained from a radical redesign of the bodywork, interior, engine, transmission and running gear.
By using the 6.3-liter V12 engine can generate power of 770hp at 8,500 rpm. And maximum torque reaches 705 Nm at 6,750 rpm. In terms of aerodynamics, the F12tdf has an aerodynamic efficiency figure of 1.6, almost double that of the F12 Berlinetta.
The car has been styled by aerodynamics, all of the bodywork panels have been revised. Beside that, wider front and rear tracks give the car an even more aggressive look. Inside, the Ferrari F12tdf features a driver-focused cockpit with carbon-fiber housings for the instruments and satellite pods, single carbon-fiber shell doors, Alcantara trim, technical fabric for the seats and patterned aluminum for the floor.
FerrariFerrari F12tdf Limited Editionlimited edition
Aston Martin V8 Vantage S, Impressive and Powerful Supercar
Lyonheart K, Modern Interpretation in the Form of Gorgeous Speedster
2019 Mercedes-AMG G63 Comes With High Performance and Stunning Look


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text:
non military drones only
Tag Archive | logistics
in General, Laws and Regulations, Transport
Amazon asks FAA for permission to test delivery drones
In April this year, Amazon.com issued a shareholder letter that stated: "The Prime Air team is already flight testing our 5th and 6th generation aerial vehicles…″. Three months fast forward, first half of July, the company is on its 9th generation of drones, that can fly up to 50 mph (~80 km/h) and carry up to 5 pounds (~2kg) of payload, which is enough for 86% of the sold products.
Rapid development of the Amazon drones was facilitated by intense indoor testing, including test flights in their research lab in Seattle. Among features tested are agility, flight duration and redundancy. Most importantly, the company claims to have developed sense-and-avoid hardware and software that will allow its drones to automatically avoid collisions.
In order to progress further with development, outdoor testing, in more realistic conditions is necessary. That is why Amazon.com asked to be exempted from the lengthy and complex approval process, citing innovation as a driving factor, since the Congress gave the FAA power to grant innovators "expedited operational authorization".
If the exemption is granted, that would allow the company to test Prime Air drones in its own backyard, "with additional safeguards that go far beyond those that of FAA". One of the safeguards is the Geo-fencing, a technology that defines geographical boundaries within which drone flight can be confined and beyond which the drone gets automatically deactivated. That technology is already available and used on many commercial drones, DJI Phantom being one of the first, which was already posted at dronologista earlier this year. Exemption would also allow Amazon.com to test drones outside of six testing sites where FAA allows unmanned aerial vehicles to be used, in order to assess their safety, communication, air traffic control etc.
If exemption is not granted, however, it is quite obvious what will happen: the company will simply move its drone operations abroad. Canada is already very hospitable to commercial drone operators.
Full text of the Amazon Petition for Exemption can be found here.
Very detailed articles about the topic can be found at Forbes and Cnet.
Videos courtesy of Amazon and DJI Innovations
in Transport
HorseFly – Unmanned Aerial Parcel Delivery System
Parcel delivery UAVs are a simple idea that requires a complex technology and great deal of vision. Matternet, Amazon.com and DHL (with their Paketkopter) are actively developing their drone delivery designs, and despite restrictive regulations, it is reasonable to expect that it will become reality sooner rather than later.
There is one common thing for all above mentioned systems: they are being developed to deliver package from a fixed location, the warehouse. The fact is that there are not a lot of warehouses in any given metropolitan area, and that they are almost exclusively located on the outskirts of the city. Despite of the developing endurance and range of multirotors, it is easy to see that even with the optimally positioned warehouses around the urban area, large parts of the city will remain outside of delivery drones operational range.
That seems to be a vision that has driven guys from AMP Holding to work together with the University of Cincinnati to develop UAV that will be coupled with a delivery truck.
AMP Workhorse delivery vehicle
A remarkably simple and brilliant idea of combined truck-UAV delivery method, should work something like this: The HorseFly will be positioned atop a delivery truck, awaiting a package from the driver. When loaded, the HorseFly will scan the barcode on the package, determine the path to the delivery address via GPS and fly away – completely self-guided – to the appropriate destination. Meanwhile, the delivery truck will continue on its rounds. After successful delivery, the HorseFly will zoom back to the truck for its next delivery run and, if needed, a roughly two-minute wireless recharge.
This system will require a more complex route optimization solution, one for the delivery truck and one for the UAV, and it is not clear yet how will that part of the delivery process be sorted out. But with the delivery vehicles conveniently scattered all over the urban area, no neighborhood will be out of range and reach.
HorseFly octocopter and AMP Workhorse
Essential part of this system is the safety. Steve Burns, AMP CEO says that "An important part of the HorseFly project is that we make a vehicle that will not drop out of the sky". In addition to the sophisticated autonomous controller system, the HorseFly will have multiple built-in hardware redundancies (rotors, onboard computers, battery packs). So if, for example, multiple rotors were to fail, the HorseFly and its payload still could be retrieved safely.
It seems that we got two emerging UAV delivery technologies: one from the fixed location, warehouse (Amazon.com and DHL) and the other from the moving vehicle. It will be interesting to see which one of them will prevail.
Dronologista bets that the vehicle-UAV system is the winning combination, because it offers great flexibility and contains a potential for further development (think of automation).
Interesting articles about the HorseFLy could be found at Gizmag, DroneLife and University of Cincinnati news page.
Nice picture gallery can be found in Fast Company Magazine.
Pictures courtesy of PluginCars.com and Fast Company Magazine.
in Agriculture, Events & Competitions, General, Safety, Transport
Drones For Good Award
First and largest governmental award for civilian drone application is offered by the Government of United Arab Emirates.
The 'UAE Drones For Good Award' was launched under the direction of His Highness Sheikh Mohammed bin Rashid Al Maktoum, UAV Vice President and Ruler of Dubai in February 2014. The official webpage of the award, www.dronesforgood.ae became online on 10th of May.
The Award has two parts: an international prize offering $1 million USD and a local prize of 1 million AED (approximately $275,000 USD). The National competition is dedicated to rewarding the best, most practical ideas for using UAV technologies today to improve government services in the UAE. The International competition is dedicated to rewarding the most promising prototypes of future services that may benefit humanity at large. Submissions must be able to demonstrate a working prototype that could conceivably be developed into a working system within the next 1 to 3 years.
Dronologista already mentioned in one of previous posts, that UAE is planning to deliver personal documents using drones. The Drones For Good Award is just another logical step that Government of UAE is taking toward systematic application of UAS for the benefit of humanity. In a bit cheesy video below you can get the picture of how it ought to work.
More information about the award and the rules can be found here.
Dronologista will be following development of this competition, and wishes all applicants good luck.
Drone Startups part 4: Garuda Robotics
In every drone startups post up to now, dronologista presented US based companies. That reflects the fact that majority of the drone industry and drone interest comes from the US (more than 50% – all three 😉 of the visitors of this blog as well). But UAVs are global phenomenon, and the development in this domain is happening around the world. To support that, in this post, dronologista presents a Singapore based startup, Garuda Robotics.
Garuda Robotics Logo
Targeting primarily enterprises that are using a fleet of drones for surveillance, inspection, agriculture or logistics, Garuda Robotics offers both hardware (autonomous drones) and software (basically drone fleet management system).
The software called Garuda Cloud consists of:
dashboard – status of drone fleet and history of missions
multi mode flight path generator – creates flight path by selecting starting point, finishing point and waypoints in between
cloud storage – for creating, editing and saving mission packages
flight simulator – enables drone's eye view from along the actual flight path
Garuda Cloud also features point and click user interface and enables a seamless transition from autonomous to semi-autonomous mode of flight and back.
What makes this platform interesting is that it allows developers to create their own add-ons extending the basic functionality provided by the company. Also, there is a possibility to connect Garuda Cloud to existing hardware and software systems.
Garuda Robotics mission is to build internet of things, where drones are used as carriers for all physical matter. This all sounds very ambitious, and how it will be converted into reality, remains to be seen in months and years to come.
Dronologista will bring you an update on this story as soon as it happens.
Logo is courtesy of Garuda Robotics.
The city and the drones
Skies of the cities in near future will be full of drones. They will be used for surveillance, mapping, infrastructure inspection, delivery, you name it. But how will UAV be incorporated in the existing fabric of urbanized areas? What kind of safety, legal, technical, liability, privacy etc. framework needs to be set up so that the potential of such vehicles can be fully utilized.
One of the first cities that will start experimenting with drone delivery system is Dubai. Officials of the United Arab Emirates want to introduce such system to deliver documents e.g. identification cards and driving licenses.
It will be interesting to see what will be the results of this experiment, because there are many questions to be answered:
What routes will drones take?
Will they fly over the existing street network, or above private property as well?
How will they be vertically and horizontally separated?
What kind of fail safe mechanism will be used?
How will the whole network be controlled etc.
Service provider that wants to use drones, will need to have some kind of "dronodrome" or station where UAV will land and take off, be serviced, recharged and loaded. Due to the limits of the operational range, several such stations need to exist throughout the city in order to cover required area. What kind of standards will be used to assess such station? Can it be privately owned?
City leaders need to start planning for the impact that drones will have on city services. New transport and delivery options may also open previously unknown opportunities in cities. But if those options are randomly embraced, without proper planning and preparation, they will create additional problems, and may harm a development of the city.
Because, no one will want to live in a city where drones are raining.
Drone Startups part 1: Matternet
Just like the internet, but for matter. Set up by a group of students from Singularity University around the idea of leapfrogging expensive and inflexible road infrastructure in 2011, Matternet envisions system that can reach anyone, anywhere a system that creates opportunities and unlocks access.
Aiming to leapfrog limits of the existing surface transportation infrastructure, Matternet offers an innovative solution: a network that will use drones to deliver goods from and to communities that don't have access to roads.
Taking into account present boundaries of drone technology, people behind Matternet designed a system that consists of three components:
Drones – custom-built autonomous electric quadcopters with GPS and sensors, capable of carrying a few kilos up to 10 kilometers (which will improve, as the technology advances)
Ground stations – solar powered charging stations where a drone can swap dead batteries for a set of charged ones
Operating system – to organize fleet operations around the clock
The team has already conducted first autonomous point to point test flights in the Dominican Republic, Haiti, the UK, and at NASA's Moffett Field in the US.
Although there are difficulties to be overcame (e.g. adverse weather conditions), those are not insoluble problems, and Matternet team is working on solutions.
Although initially targeting rural areas of developing countries without road access, such system can be also used in megacities, carrying goods over congested roads.
Video and pictures courtesy of Matternet.


Children's Home & Aid's Early Start is a community-based program designed to help low-income families with infants better raise their children. The program provides family support in a group setting, educating parents on child development, positive discipline techniques and parenting skills. The program also helps transition children into a school setting through a prekindergarten program.
The Early Start program recognizes the unique role of parents as their child's primary nurturers and advocates. For this reason, parents are active participants in the Early Start program. The program also makes a special effort to encourage and support the role of fathers in parenting activities. Early Start is free of charge and provides a number of services including: personal home visits, group meetings, screenings and access to a resource network.
The Early Start program is offered in the Central Region.


Bears startling resemblance to W African Merops breweri in some aspects of plumage and long, attenuated central rectrices, but bill shape and beardedness differ, and there is no good reason to suppose that the two are closely related. Monotypic.
Locally in N, C & SE Sulawesi.
Fry, H. & Boesman, P. (2019). Purple-bearded Bee-eater (Meropogon forsteni). In: del Hoyo, J., Elliott, A., Sargatal, J., Christie, D.A. & de Juana, E. (eds.). Handbook of the Birds of the World Alive. Lynx Edicions, Barcelona. (retrieved from https://www.hbw.com/node/55830 on 25 April 2019).


The AirLive SmartLife Plus is the APP with user friendly interface to let you in full control of your smart home. It includes device control, scene creation, and the IFTTT macro rule which creates many Automation Possibilities for your smart home operation.
Open your APP, then scan the gateway's QR code. The APP automatically display all your devices. Then you can view the IP camera, check the room temperature, see how much power is used, or turn on the alarm. Everything is clearly visible and easy to use.
Create different combination of activities using the scene tools. You can create a scene base on a location such as living room. On the other hand, you can also create a scene base on a occasion such as party mode, theater mode, or welcome home schemes. You can even set automatic activities when you are away from home.
The SmartLife Plus supports ITFFF(If this then that) protocol. Therefore, you can setup certain conditions to trigger some events. So whether it is for home security, temperature control, or home automation, the APP has a solution for you.
In the Setting page, you can back up the Scene or Macro's applications which you had set up. Besides, you can lock those settings then no one can change it randomly. Moreover, if you want to include/exclude any device, it also can be down at here.
Supports Android 4.2 or Up and iOS 10.0 or later. Compatible with iPhone, iPad, and iPod touch.
How to use the OFF Mode function in Macro Setting ?
How to use the Timer and Interval function in Scene and Macro Setting ?
How to Automatically update the Firmware of the Gateway ?
How to setup Alexa and Google Voice Control ?
What is the Maximum Resolution of the SmartCube 300W Camera in the SmartLife Plus APP ?
How to add AirLive Smart Cube SC-300W to AirLive Smart Home IoT SmartLife Plus APP ?
How to select your Gateway when you have added multiple ones ?
How to operate the Airlive Smart Life APP?
Please make sure the sensors and/or actuators are included to the Gateway.
By default all SK-101/102/103/104 packages will already have the sensors and/or actuators included to the Gateway.
When a factory reset was done or all sensors/actuators were cleared from the APP.
Or you want to add an extra sensor/ actuator, then please follow the below QIG guide for the including settings.
How to add my SmartCube 300W to the Gateway and APP?


Combine the seasoning and corn flakes. Dip chicken in buttermilk and then roll in corn flakes. Put chicken in baking dish and bake at 375 degrees for 1 hour.
This entry was posted in Recipes &Cooking and tagged low fat chicken recipe, simple chicken recipe by Charla. Bookmark the permalink.


text:
Enter the Anthropocene: 'Climate change is political, so should be art around it'
Artist Vibha Galhotra talks about her gender and her art before her upcoming show at the Chandigarh Lalit Kala Akademi in January.
| The Castaways | 9-minute read | 01-01-2019
Chinki Sinha
@chinkis
It's an upstairs room in a Delhi housing society — one of those where the view from the window is cut short by smog. On the table is a book, Žižek's Jokes: (Did You Hear the One about Hegel and Negation?), which she found on her trip to Germany.
The small book is a collection of "published jokes" by the contemporary Slovenian philosopher Slavoj Zizek.
"In an old joke from the defunct German Democratic Republic, a German worker gets a job in Siberia. Aware of how all mail will be read by censors, he tells his friends: 'Let's establish a code: if a letter you get from me is written in ordinary blue ink, it is true; if it is written in red ink, it is false.' After a month, his friends get the first letter, written in blue ink. 'Everything is wonderful here: stores are full, food is abundant, apartments are large and properly heated, movie theaters show films from the West, there are many beautiful girls ready for an affair — the only thing unavailable is red ink.'"
"And is this not our situation till now? We have all the freedom one wants — the only thing missing is 'red ink'. We 'feel free' because we lack the very language to articulate our unfreedom... The task today is to give the protesters red ink," Zizek writes in the commentary.
Vibha Galhotra grapples with the questions of origin, climate change and the purpose of art as a healing mechanism. (Photo: Yasir Iqbal)
The book being there is not a co-incidence.
Artists know where to look for truth.
And more than anything, the metaphor of the unavailable red ink is what characterises the work of this important artist.
At first, she denies the gender question.
"Gender doesn't matter," she says. "My work is non-gender."
But Vibha Galhotra, a New Delhi-based conceptual artist, says her large-scale sculptures are often referred to as "very manly". The denial, then, becomes a complex case of artists who are women trying to free themselves of gendered tags, and become more abstract.
In the era of MeToo, Galhotra's work is distinctly political. She grapples with questions of origin, climate change and the purpose of art as a healing mechanism.
While endless debates on women's status in society go on, the Indian art world has been witnessing its own revolution — in terms of women artists who are using the "feminist aesthetic" to explore their social responsibility, and finding vocabulary that is both political and personal.
This year, the Kunstmuseum Wolfsburg in Germany curated an exhibition called "Facing India" that featured six women artists from India. It explored the past, present and the future from the female perspective. Galhotra was one of the participating artists.
As she delves into the question of colonial politics for her upcoming work — to be showcased at the Lalit Kala Akedemi in Chandigarh and the Jack Shainman Gallery in New York the next year — she says she picked up the threads from the research of various space agencies, especially NASA's work since 2012 to find water beyond earth. She talks of the politics of wealth, and how the poor suffer the most because the rich can always go to other planets. It is a joke — but a cruel one.
Go around Delhi and the poor are huddled under flyovers inhaling toxic air, while the wealthy breathe purified air.
"The eccentric tech big-shot Elon Musk, the CEO of SpaceX, decides to give an option of living on another planet with the proposal of making life multi-planetary. He is selling one-way tickets to Mars," she says. "This is how we go about conquering. The question of environment is political, as claims to inhabit another planet — in this case, Mars by 2024 — with Musk's proposal for a 'spacefaring civilization, with a multi-planetary species' only hints at a new, scary form of colonisation."
And, like the legendary artist Joseph Beuys, she uses absurdism and tools of deconstruction and reconstruction to question the utopian idea of Mars being turned into a self-sustaining human colony to escape the crisis on earth.
Galhotra's work has been described as 'too manly' — showing how tightly an artist's gender gets tied to art. (Photo: Vibha Galhotra/Facebook)
I ask her what she sees outside her window in the city.
"Smog and advertised fears," she says.
It wasn't always that she wanted to be an artist — but then, she says, you grow up and try to find meaning. That's how she thought her work could make the environment its focal point. That's how a restructuring of her social and political beliefs took place.
Climate change is a political thing, a collateral damage of capitalist ideas, she says. Perhaps this is why we have a city enveloped in smog. It is like walking in Gotham City, where the sky doesn't meet the eye.
That's why we have a black river foaming at its mouth. That's we are dying every day.
Her work is an exploration of the state of urban development in India and stems from the fact that she was an "unhealthy child" and felt weak in Delhi, where she came from Chandigarh to practise as an artist.
At the level of art, she says, there is a disproportionately low representation of women.
"There is scarcely any written or visual archive or any form of documentation on the works and lives of women artists from the past. The representation of women artists in museum spaces would be limited to about a meagre five per cent. Even within the realm of galleries, the limited numbers of buyers for art created by women further excludes them from gallery representation. Women, as artists, have to constantly compete for space in the world of art — to display, to sell, to prove their worth at every step," she says.
Her earlier work was about migration and Metropia — the word she invented to express her situation as a migrant trying to find utopia.
In 2010, when she was invited by NGO Sweccha and Khoj, a Delhi-based art organisation, to participate in their Greenathon project, she became interested in environmental damage in the urban area.
Post-that event, she ended up working on a project, Sediment. Another untitled one was around the Yamuna, where she documented the river for two years by traversing it in a boat, taking pictures. It was on a Sunday there that she saw a family doing an ancestral pooja at the ghat. In all the muck and dirt, the family was trying to take a bath. She tried to stop them — only to be scolded for wearing shoes on the banks of a holy river — and 'how dare she call it dirty'?
"I was standing in this absurd theatrical space suspended between belief and reality," she says.
That's when she decided to get canvases and start painting with the filth.
It was also a performance where she took one canvas every day and later froze the kichar on them with the help of resin. "That body of work changed my practice," she says.
Galhotra's work raises the question whether art can become more relevant as we face the destruction of ecology, and is a critical take on the social, economic and political implications of climate change.
Her work could be defined as entering an Anthropocene, where one is faced with the damage one has wrought upon the environment.
Don't expect pretty things.
Galhotra received her bachelor's degree in graphics from the Government College of Arts, Chandigarh in 1999, and her master's from Kala Bhavan, Santiniketan, in 2001. Chandigarh, she says, is a 'nowhere place', where she was at a loss to find her footing as an artist. Shantiniketan freed her, she says. In her 365 days, she maintained a daily diary of events, thoughts, behaviours, emotions, philosophies and actions. She made works to reflect her own observations that could be the framework of Theatre of the Absurd.
It is this theatre of the absurd that characterises her experience of being an artist.
And while the concerns are not gendered, the approach is.
"I look at the environment with a motherly concern. And of course you have felt the gender bias. You know it stops you from many things, but you break the wheel," she says.
Galhotra is also working on her dream project, titled 'Food For Thought'. It revolves around the theme of 'panchabhuta' or the five elements (water, air, fire, air and ether). She has been working on it for almost 30 months now. It is a public participatory performance, including photographic content, video, research and installation, designed to question issues around ecology, economy, politics, and behavior.
The project is inspired by Judy Chicago's The Dinner Party and Rirkrit Tiravanija's Untitled (Free/Still).
Her latest is Judy Chicago's The Dinner Party. (Photo: http://www.judychicago.com/gallery/the-dinner-party/dp-artwork/)
"Don't you feel that you are living in a plastic and unrealistic socio-political environment?," she says.
That's why, like Zizek, she thinks political correctness gets in the way of things. And perhaps that's how the future of art should be — honest and political.
"This is an emergency and if my work can contribute in any way in correcting the way we see or relate to the environment, it would be my way of giving back," she says.
From her terrace, the city looks hazy. Visibility is low. This is how you enter the Anthropocene. You stumble through it, coughing while your eyes burn. She looks up at the sky and shrugs.
No stars shine here, she says.
And as she traverses the patriarchal world, her art becomes more pronounced. In her last work that she showcased at an art gallery as part of a group exhibition in Gurugram in December, she cast her own silhouette in bronze, facing a mountain. The inspiration came from Maya Angelou's Still I Rise.
In her last work, she cast her own silhouette in bronze, facing a mountain. (Photo: Vibha Galhotra/Facebook)
"I'm a black ocean, leaping and wide,
Welling and swelling I bear in the tide," she recites.
And then, she says she knows she likes endlessness, uninterrupted views from where she stands.
"I want to dance to the songs of freedom. I want to smash the mountains with my gaze. I want to say to everyone I am armed with the courage of a woman who has taken up the hammer and the chisel. I can bury the thousand unfreedoms and grow flowers on the ashes," Galhotra says.
And the gray of her world suddenly seems not composed of bleakness, but of hope and courage.
Also read: Anyone to whom equality is integral is feminist': Artist Sonia Khurana talks about her aesthetic
#Gender, #Art, #Anthropocene, #Vibha galhotra
Chinki Sinha @chinkis
Rover in the driftless area of the outcastes. Writing is a way of deleting.
More from Chinki Sinha |


Welcome to my cupboard. I write weird things and enjoy odd art, books, films and fashion so have a look through my blog and share the joy.
Categories are on the right but flick through Bizarre Book Club for other people's odd scribblings and Tales of the Slightly Unexpected for weird personal stories.
Hello you this is me, your site is nicer than mine!! How unexpected is that.
I think that the possibilities within this site are limitless. It is just like the author – interesting, amusing and downright good.
Could you wait til after my dinner?
There's ice cream but no jelly, is that okay with you?
Will have to find my way through the maze of shops, blue green or red jelly?
Ffank yhat four writtanS haye eHntertainmontS wobsit!
I envy the fact you have a pipe and I love the fact you have the moxie to stand in a bucket.
Yay! I shall make your artistic brain a nice cup of tea.
My favourite part was the nice lady talking.
She is nice, and she is a lady.
Like your style! Will follow. Thanks for following mine.
Yeah, like your lobster phone line and just had a look at Little Grimton – very funny and full of possibilities! Next door, I bet, to my fictional town of Bafflesby: next instalment the tourist guide! Look forward to getting into your site, cheers!
Yay nice to meet you!
Thank you, and me yours!
I just wanted to thank you for taking time to read my poem "The Greatest Quest"! It means the world to me that you appreciated it! Especially considering you are such a distinguished writer. I love your blog by the way and look forward to reading more of it! I'd be honored if you might follow me. I'll follow your page as well for sure! Thanks again!
Distinguished, wow! Of course I'll follow you, I like your blog. Thanks!
Please give mine a look.


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Social reach – Your blog, social media and press releases can all be used to publicise your involvement.
Network – a great networking opportunity both to meet new b2b suppliers, or to become one yourself.
As proud partners of Radio City's own charity, Cash for Kids, with our sponsors help, we aim to raise more funds for charity than ever before whilst at the same time, helping you to grow your business.
There are multiple sponsorship opportunities available, (including feather flags, monsoon banners, golf gloves, starter podium sponsor and registration tent sponsor) with season sponsorship packages starting from as little as £250.
We would be delighted to tailor a bespoke package that perfectly reflects your specific requirements and budget and once agreed, we'll work hard to ensure that you squeeze every last drop of value from your marketing spend.
Playfair Events design all marketing materials to your specific requirements, ensuring your company name, logo and advertising message are clearly visible on each item, and due to our enhanced purchasing power, we guarantee the cost will be lower than you could find elsewhere for the same products. Once the golfing season is over any materials we create are yours to keep.
Nearest the pin markers and longest drive markers from GMS are designed with a fully waterproof resin. The backs are a laminated allowing golfers to write on them, while keeping them protected in the rain. Simply write and rub out, with no worries about the weather or readability in the wet. We've put a handy handle for carrying and a hole for the pencil in the top.
For an informal chat about how Playfair could help take your business message to an elite audience in a unique way, please feel free to contact us.
Interested in working with us? Find out more about our sponsorship packages.


text:
San Jose Giants named Minor League Baseball's…
San Jose Giants named Minor League Baseball's top franchise
By Wire Services and Beau Yarbrough |
Minor League Baseball presented the San Jose Giants with the 2009 John H. Johnson President's Trophy, presented annually to honor the complete baseball franchise. The criteria is based on franchise stability, contributions to League stability, contributions to baseball in the community and promotion of the baseball industry.
The San Jose Giants experienced a record breaking season for the fourth consecutive year, setting all-time attendance and revenue records, completing the regular season with a total attendance figure of 211,054, an average of 3,015 fans per game. It the first time in franchise history that the team drew over 200,000 fans for the regular season.
The team also drew a record postseason crowd of 12,053 in four games. The Giants' combined regular and postseason total attendance was 223,107 fans. The 2009 season eclipsed all revenue numbers in the history of the franchise, a record 21% increase in total revenue based on an attendance increase of 16% over the previous season.
Evergreen Valley sophomore Hannah Suh won the NorCal golf championship Monday shooting a 2-under par 70 at the 6,046 yard Almaden Country Club. The 15-year-old Suh edged her close friend Mariko Tumangan of Presentation and Grace Na of Alameda by a stroke.
Suh got hot on the back nine with three birdies, including a four on the par-5 18th hole to win the tournament.
"I wasn't playing well on the front nine, but I heard about the scores being posted and thought I might be able to win this," Suh said. "I started to stick my irons on the back nine — my iron play really improved."
The State Tournament will be held at Poppy Hills Nov. 19.
Suh and Tumangan qualified along with three other Central Coast Section golfers: Taylor Camany (72) of Salinas, Haley Andreas (74) of Pacific Grove and St. Ignatius' Alexandra Wong (75).
Olympic silver medalist Sasha Cohen withdrew from Skate America on Monday, saying she is still battling the tendinitis in her right calf that forced her to drop out of last month's Trophee Eric Bompard before the event.
The Pac-10 has approved the request from Oregon to reinstate running back LeGarrette Blount, who was suspended in September after he punched a Boise State player. Blount will be eligible to play in Saturday's home game against Arizona State.
Arizona starting tailback Nic Grigsby is questionable for Saturday's game at California with a sprained right shoulder. He did not play in the Wildcats' 48-7 victory over Washington State last weekend.
UCLA quarterback Kevin Prince is expected to play Saturday against Washington State after showing no complications from a concussion he suffered on a helmet-to-helmet hit from Washington's Donald Butler while Prince scrambled downfield in the Bruins' 24-23 win over the Huskies last weekend. Prince sat out the second half, and said he didn't remember the hit after the game.
Deon Thompson scored 20 points and Ed Davis added 13 points to help No. 6 North Carolina spoil Isiah Thomas' college coaching debut and beat Florida International 88-72 in the 2K Sports Classic.
Evan Turner recorded only the second triple-double ever for Ohio State with 14 points, 17 rebounds and 10 assists in the 16th-ranked Buckeyes' 100-60 victory over Alcorn State in the 2K Sports Classic.
Marat Safin extended his career by at least one more round, saving three match points Monday to beat French qualifier Thierry Ascione 6-4, 4-6, 7-6 (3) at the Paris Masters. The 29-year-old Russian, who plans to retire after this tournament, will face U.S. Open champion Juan Martin Del Potro of Argentina in the second round.
The Tampa Bay Rays have exercised their $10 million option on 2009 All-Star MVP Carl Crawford. He hit .305 with 15 homers, 68 RBIs and a career-high 60 steals this year.
The Red Sox exercised their $7.7 million option on Victor Martinez and declined options on Jason Varitek and Alex Gonzalez on Monday.
Boston also agreed to a $5 million, two-year contract with 43-year-old knuckleballer Tim Wakefield, replacing a perpetual $4 million annual club option.
Los Angeles Galaxy forward Landon Donovan will be among those missing when the United States plays Slovakia in an exhibition game Saturday. U.S. coach Bob Bradley also bypassed starting goalkeeper Tim Howard. He selected Brad Guzan, Marcus Hahnemann and Troy Perkins for his 22-man roster Monday. Hahnemann hasn't made an international appearance since October 2007 against Switzerland.
Wire Services
Beau Yarbrough


text:
package cz.tul.entities;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import javax.persistence.*;
import java.io.Serializable;
import java.util.HashSet;
import java.util.Set;
import java.util.UUID;

/**
 * Created by Bc. Marek Jindrák on 01.11.2016.
 */
@Entity
@Table(name = "operation")
public class Operation implements Serializable, CustomEntity {
    private static final Logger logger = LoggerFactory.getLogger(Operation.class);

    @Id
    @Column(name = "OPERATION_ID")
    private String operationId;

    @ManyToOne(cascade = CascadeType.ALL)
    @JoinColumn(name = "METHOD_ID")
    private Method method;

    @OneToMany(mappedBy = "operation")
    private Set<OperationAttributes> operationAttributes = new HashSet<>();

    @OneToMany(mappedBy = "allowoperationId")
    private Set<AllowStep> allowStepss = new HashSet<>();

    @OneToMany(mappedBy = "operation")
    private Set<AllowStep> allowSteps = new HashSet<>();

    @Column(name = "NAME")
    private String name;

    public Operation() {
        operationId = UUID.randomUUID().toString();
    }

    public void setOperationId(String operationId) {
        this.operationId = operationId;
    }

    public Method getMethod() {
        return method;
    }

    public void setMethod(Method method) {
        this.method = method;
    }

    public void setName(String name) {
        this.name = name;
    }

    public Set<OperationAttributes> getOperationAttributes() {
        return operationAttributes;
    }

    public void setOperationAttributes(Set<OperationAttributes> operationAttributes) {
        this.operationAttributes = operationAttributes;
    }

    public String getOperationId() {
        return operationId;
    }

    public String getName() {
        return name;
    }

    public Set<AllowStep> getAllowSteps() {
        return allowSteps;
    }

    public void setAllowSteps(Set<AllowStep> allowSteps) {
        this.allowSteps = allowSteps;
    }

    public Set<AllowStep> getAllowStepss() {
        return allowStepss;
    }

    public void setAllowStepss(Set<AllowStep> allowStepss) {
        this.allowStepss = allowStepss;
    }
}

redpajama_set_name: RedPajamaGithub


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