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Abandoned Spaces
The stories behind some of the most popular Star Trek lines
Dec 9, 2017 Stefan Andrews
Undoubtedly, Star Trek is one of the most influential science fiction TV series in history. The first original episodes aired during the 1960's; and since then, during a time span of six decades, the show incarnated in some other memorable series and films.
That has been more than enough time for some lines and catchphrases used in Star Trek, which virtually have gain an iconic status. Even if you have not watched a single episode, the chances are that you already know a line or two.
"To boldly go where no man has gone before…"
By far, Star Trek has one of the most famous opening narrations in the history of filming industry. Resonating a feeling of the 1960's futuristic optimism, the iconic phrase was first spoken by William Shatner who starred as Captain James T. Kirk in the original series.
The full narrative goes: "Space: the final frontier. These are the voyages of the starship Enterprise. Its five-years mission: to explore a strange new world, to seek out new life and new civilizations, to boldly go where no man has gone before."
William Shatner and Sally Kellerman, from Where No Man Has Gone Before, the second pilot of Star Trek: The Original Series (1966)
The narration was used in each episode in the original series, except for the two pilot ones, The Cage and Where No Man Has Gone Before. The phrasing was first introduced by Samuel Peeples, who also authored the second pilot episode, Where No Man Has Gone Before. He had devised the final version of the wording along with creator Gene Roddenberry and the producers John D. F. Black and Bob Justman.
Gene also had a proposal of his own, which reads as follows: "This is the adventure of the United Space Ship Enterprise. Assigned a five-year galaxy patrol, the bold crew of the giant starship explores the excitement of strange new worlds, uncharted civilizations, and exotic people. These are its voyages and its adventures."
Gene Roddenberry in 1976
Gaining tremendous popularity, the opening narration was further used in other reincarnations of the TV series. In the reboot Star Trek: The Next Generation, the phrasing got slightly tweaked and "its five-year mission" was changed into "its continuing mission," as well as the final most famous part was changed to sound gender-neutral, "where no one has gone before."
Some reports suggest that the opening was inspired by a 1958 White House press booklet entitled Introduction to Outer Space that promoted space program in the wake of Sputnik flight. Others suggest that it was devised by a statement given by the 18-th century British explorer, navigator, cartographer and Royal Navy captain, James Cook. Reportedly, Cook had declared, following an early expedition to Newfoundland, that his intentions are not to go "further than any man has ever been before, but as far as I think it is possible for a man to go."
The popular Vulcan greeting "Live long and prosper" that goes along with a finger-separating hand gesture, first appeared in 1967, also during the original series, in an episode called Amok Time. Late actor Leonard Nimo,y who portrayed the mixed human-Vulcan in the show, Mr. Spock, had explained in his biography I Am Not Spock that he had been the one to come up with the greeting and hand gesture. Nimoy had invented the greeting based on a traditional Jewish blessing he remembered from childhood when his grandfather took him to an Orthodox synagogue.
In the Jewish version, the blessing is done in a slightly different manner, allowing the fingers to form the Hebrew letter "Shin." The letter connotes "El Shaddai," referring to "Almighty (God)," but also "Shekinah" and "Shalom."
Nimoy had reinvented the gesture by holding up just one hand instead of both and changing the wording.
"Resistance is futile."
One of the most notorious creatures to be remembered from the Star Trek is the Borg. The line "Resistance is futile" was first uttered by the evil robotic aliens in the grand third-season finale of the Star Trek: The Next Generation. The episode aired in 1990 and went down in history as one of the most epic cliffhangers in television history.
The evil Borg built their wicked image due to the collective audio messages they would submit to their target. An example from the Next Generations is as the following: "We are the Borg. Your biological and technological distinctiveness will be added to our own. Resistance is futile."
NASA astronaut Terry W. Virts performs the Vulcan salute in an homage to Leonard Nimoy from the International Space Station on February 27th, 2015, shortly after hearing of Nimoy's passing; Nimoy's hometown of Boston is seen directly below
Another variant, as used in the film Star Trek: First Contact from 1996 goes as: "We are the Borg. Lower your shields and surrender your ships. We will add your biological and technological distinctiveness to our own. Your culture will adapt to service us. Resistance is futile."
The Trekkies will obviously never forget when Patrick Stewart delivered the line once he was assimilated by the Borg himself in the season three finale. The line has made Stewart entering the top 100 list of greatest TV Quotes and Catchphrases issued by the TV Land. "Resistance is futile" embedded in popular culture and was reused in numerous films, series or songs.
"Make it so."
Last but not least, "make it so" is one of the signature lines of Jean-Luc Picard. The line became memorable since the pilot episode of the Star Trek: The Next Generation, entitled Encounter at Farpoint.
The episode was written by Gene Roddenberry himself, so most probably he was the one to put the line in the script.
Although the phrase resembles a military command, it got very popular thanks to the special way Patrick Stewart pronounces it. Another example of his brilliant catchphrases is also "Engage."
Read another story from us: Geneviève Bujold was the original captain in the Star Trek Voyager series but quit after two days
This certainly adds to the reason why so many Trekkies favor Jean-Luc Picard as one of the best captains who appeared in the Star Trek.
Stefan Andrews
Stefan is a freelance writer and a regular contributor to The Vintage News. He is a graduate in Literature. He also runs a blog – This City Knows.
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Soul Calibur 6 will have a main story and character stories which intertwine with each other — in-game timeline shows chronological order of events
Posted by Nicholas 'MajinTenshinhan' Taylor • August 19, 2018 at 4:13 a.m. PDT
At the Tokyo Tekken Masters event earlier this morning (or last night, depending on where you live), Soul Calibur 6 producer Motohiro Okubo was present.
Before unveiling the Tekken 7 Season 2 news which you can find further down on our frontpage, there was some talk about the upcoming Soul Calibur 6.
Considering how soon after EVO this is, we unsurprisingly did not get a new character reveal (after all, we got two of them at EVO earlier this month), but there was some light shed on other aspects of the upcoming game.
There was talk about how the Soul series was way ahead of the curve as far as voice acting went, and that they paid the voice actors much more than what was customary for games at the time, leading to the high quality voicework that was praised when the early games came out, and that they did their best to try and get back the original voice actors and actresses for this title, though it wasn't possible for all of them due to busy schedules. Such was unfortunately the case for Seong Mi-na, who switched to yet another new voice actress for this game.
The main brunt of the talk, though, was centered around the story mode, and a few images shown give an idea of what the story mode will look like in-game.
Below, you can find some images of the story mode, as well as some artwork and visuals presented during the stream. There's something we need to talk about regarding that story mode image too... But we'll do that further down.
Click images for larger versions
Now, the most notable part here is probably the story mode image, where you can see character's storylines and how they line up chronologically with the main story, and the interesting part which you probably already noticed on your own is that it features unannounced characters as well, but with their names erased.
At first, I was hoping that this was going to give us proper hints to who's left to be announced, but looking closer, that unfortunately seems unlikely.
First of all, Grøh, a brand new character in Soul Calibur 6 seems to start his story before anyone else in the timeline does. Also of note is that Mitsurugi, who's been present since the very first game, has his story predominately take place after the main story ends.
As such, it seems likely to conclude that the main story shows character's journies as part of a bigger picture, while character stories focus on their own, more personal journies — kind of like side stories, if you will.
One thing we can see, though, is the length of character names. This is obviously not conclusive, but given the four-letter length, might that be Rock hiding beneath Grøh's name... ?
Feel free to speculate best you will — the game releases two months from now, so it's likely we'll see reveals ramp up in frequency before then.
More on EventHubs...
Granblue Fantasy Versus' beta left us impressed
Should lag spikes come with steep penalty in fighting games?
Who are the bottom 10 characters in SF5?
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Until very recently South Korea was a very homogeneous society with little ethnic diversity which prided itself on a single ethnic identity. Recently this has begun to change very rapidly and the number of immigrants living in Korea has more than doubled in the past ten years to 1.5 million.
Rapid urbanisation has led to huge numbers of people moving out of rural areas and as a result there has been a huge multi-ethnic baby boom in rural areas as more Korean men are marrying South East Asian women. By 2020 it is estimated that half of all children in rural Korea will come from a multi-ethnic household with 1.6 million people altogether coming from a mixed heritage background.
But with these fast changes in demographics come a lot of challenges to the children of multi-ethnic families as they face a lot of difficulties in the classroom. In a country within one of the highest high school graduation rates in the world, it's estimated that in Seoul 72% of multi-ethnic children have dropped out of high school.
In order to understand more of the issue and to find out more about what is happening in Korea to help and support multi-ethnic children, we recently spoke to Cindy Lou Howe, the director of the documentary 'Even The Rivers' which is currently in production. The documentary explores how schools in Korea are attempting to adapt to the needs of a more and more diverse classroom.
In the interview, we discuss multiculturalism, ethnic identity, Little Psy and Hallyu's potential to influence Korean attitudes towards race and identity as well as much more.
Hi and thank you for agreeing to do this interview with us. Would you be able to briefly introduce yourself and your film to our audience?
My name is Cindy Lou Howe and I primarily describe myself as an educator. I was born in Seoul to a Korean mother and African-American father.
My own mixed heritage is why I focused my masters research on the lack of educational equity for multiracial youth around the world. Part of my research concerned Korea, and naturally, I've always been curious about my birth country. So, in 2008, I returned to South Korea for the first time to work as an international school teacher.
During my four years in Korea, I started an English Program for multi-ethnic youth with the Pearl S. Buck Foundation and eventually became Vice President of the MACK Foundation, where I expanded their educational outreach to multicultural families.
All of these experiences led to the creation of EVEN THE RIVERS, a documentary film that examines how South Korea's schools are educating an increasingly multicultural classroom!
Was there anything in particular that inspired you to start making this documentary?
Well, my academic research was taking me to various conferences and it became obvious that people were very interested in this topic of multiethnic and multiracial children in Korea. However, I felt that sharing stats and figures alone wasn't the most effective way to provide a vivid picture of multicultural youth experiences today. So, I decided to team up with a team of high school students with the goal of recording the unheard voices – on-the-ground social activists, school leaders and multicultural youth – all of whom could share their perspective on education in South Korea to a larger audience.
It's estimated that by 2020 in South Korea half of all children in rural areas will come from multi-ethnic families. What are the reasons for this massive change in demographic?
To put it simply, it's hard for rural Korean farmers to find Korean wives. Due to economic growth and urbanization, there has been a "wife shortage" in Korea's rural areas. As a result, and thanks in part to government support, there's a booming market for foreign brides. In fact, since the 1990s, the rate of intermarriage has increased ten-fold. As you mentioned, about half of marriages in these rural areas now involve a non-Korean wife, and that's why Korea is experiencing a multi-ethnic baby boom.
Your film looks specifically at education for children from multi-ethnic families. What problems do they face specifically when it comes to education?
I think many people know that South Korea has a reputation for having a great education system. In fact, about 97 percent of 25-34 year-olds in South Korea have earned the equivalent of a high school diploma. That's pretty remarkable. However, in 2012, one study found that just 16 percent of immigrant children were attending high school. Another study found that approximately 40 percent of multi-ethnic high school students were dropping out, due almost exclusively to bullying, discrimination and social outcasting.
The Korean government has announced plans to set up schools specifically for these children to try to improve their level of education. Do you think this is the right approach?
In a word, No. In the beginning, when there were no safe places for multicultural children to learn, grassroots schools were set up to provide a basic education for these children. However, I don't think that creating a formal system of segregated schools will remedy the drop out rates. It's my feeling that the government should be responsible for making all schools safe places for all children.
Specifically, if you look at the government sponsored schools, they are too-often focused on superficial aspects of diversity, the so-called "dining, dress, dance" of other cultures. These schools also tend to focus on assimilation, which places the burden on the child and their family, instead of on wider society. There's also a focus on Korean language and culture classes for multi-ethnic youth. However, many of the youth we interviewed for the film are completely fluent in Korean, and grew up in the culture, so remedial language classes or proving they know the varieties of kimchi aren't the answer!
Although EVEN THE RIVERS focuses on Korea's schools, the film also examines broader South Korean society and explores a fundamental question – if Korea's proud people are prepared to redefine what it means to be Korean. Ultimately, South Korea's schools, and larger society, must address attitudes surrounding diversity and discrimination.
Do multi-ethnic families and especially children face any other cultural difficulties outside of the classroom?
Yes, they do. The xenophobia and discrimination that exists in wider Korean society also enters the classroom. In fact, one study found that in 2012, over 41 percent of multicultural families experienced prejudice. That figure was actually up about five percent from just three years earlier. In 2010, the National Human Rights Commission conducted a survey that found several disturbing results. 42 percent of multi-ethnic youth were taunted by their classmates because of their accents, 37 percent said their peers looked down on them due to their mother countries, 25 percent said they were insulted for their appearance, 21% were actually told to leave Korea, and 15 percent were physically assaulted by their peers. These numbers suggest there's a real urgency in addressing school bullying and general attitudes.
Many Koreans' idea of national identity seems to be closely tied to ethnic identity. Do you think this is the case? If so, is it a problem and how do you think this mind-set can be changed?
This is definitely the case. Most historians agree that Korean ethnic nationalism or danil minjok (단일민족), in Korean, is a modern response to decades of Japanese colonization. This "pure blood" or "one people" concept probably reached its zenith in the 60s. However, I was shocked to see that school textbooks still taught children this "theory" as recently as a decade ago. Fortunately, as South Korea's economy has become truly global, you increasingly see politicians, academic leaders and policy advisors urging the public to shift away from this nationalistic identity. Furthermore, the nation's low birth rate and rising number of multi-ethnic youth suggest that a multicultural Korea is inevitable. My hope is that the film can play a small part in encouraging Koreans to accept a more inclusive definition of what it means to be Korean.
Child star Hwang Min Woo (also known as 'Little PSY') recently faced a lot of online attacks for having a Vietnamese mother. Do you think this is a symbol of a wider issue in Korea?
As I mentioned earlier, multiculturalism or diversity won't be effective if it's mostly superficial. Multi-ethnic Koreans as models, entertainers or celebrities are people first. What I mean is that they deserve to be fully accepted and included in Korean society, not just as exotic sources of entertainment. While what happened to Hwang Min Woo was very real, I think we have to remember that there will always be Internet trolls vying for attention, and I was heartened that the public's rejection of some of the racist attacks suggests that they don't reflect a larger societal sentiment.
As Hallyu spreads across the globe, do you think Korea is facing more scrutiny in its attitudes to multiculturalism from the rest of the world? Do you think this could have a positive impact?
I do, and there's something very exciting about the way "soft power" can influence fundamental change. While Korea has been very successful at exporting K-pop, arguably a manufactured component of Korean culture, my hope is that the government will invest more in promoting values and policies, particularly as it relates to multiculturalism. If Korea is constantly saying, "Embrace our culture!" or "Visit our country!", it's only natural that many people will do so – some as tourists, but others as immigrants. As Korea widens its cultural influence and reach, I think it's inevitable that it will have to incorporate aspects of other cultures and evolve.
Do you think it's important that media like K-pop and Korean dramas start to reflect their diverse audience and Korea's increasingly diverse population more? Could this have a positive impact on views of multi-ethnic families in Korea?
Well, there have already been several movies and dramas that have touched on multiculturalism. Articles on this topic appear almost daily in South Korean media, so there's definitely interest. I think the important thing is that these portrayals avoid stereotyping. That way, they can have a positive influence on shifting perceptions about multiculturalism in Korea.
And finally, what are your plans for this documentary and does it have a release date yet? When can we expect to see it?
Thank you for asking! I estimate that we have about 80% of the footage to complete the film. Ideally, we will return to Korea to tape a few more interviews, conduct follow-ups and tie up any loose ends. To make this possible, our plan is to launch a Kickstarter fundraising campaign this fall. If all goes well, we are hoping for a spring 2014 release!
On that note, to keep tabs on the film's progress or to get involved or schedule a screening, please check out our website, www.eventherivers.com or "like" us on Facebook. I would love to hear from you!
Finally, thanks to Beyond Hallyu for the opportunity to spread awareness of this important issue facing South Korea!
Thanks again to Cindy Lou for taking the time to talk to us. You can find out all the film's latest developments through their website, Facebook and Twitter pages and let us know what you think in the comments!
A very informative article and great website. These are issues that Korean film and drama fans never get to see or hear about. A discordant dose of reality.
Excellent interview. While I can understand the nationalistic ideals and pride due to Korea's history, that's simply not the way of the world anymore. The world is totally connected. People need to stop looking at the surface and start looking at the heart and mind. That goes for here in the U.S.A too. They are just as guilty. Mixed races and cultures make for beautiful people inside and out, and many that are do not carry on that puffed up attitude that infects a singular race. It's a shame they have to feel so torn and discriminated against all the time.
Excellent interview. While I can understand the nationalistic ideals and pride due to Korea's history, that's simply not the way of the world anymore. The world is totally connected. People need to stop looking at the surface and start looking at the heart and mind. That goes for here in the U.S.A too. They are just as guilty. Mixed races and cultures make for beautiful people inside and out, and many that are do not carry on that puffed up attitude that infects a singular race. It's a shame they have to feel so torn and discriminated against all the time.


FORMAT International Photography Festival is back with exhibitions, talks, photobook market, workshops and more.
The festival was established by QUAD in 2004 and is the UK's leading festival of photography and related media. FORMAT organises a year-round programme of international commissions, open calls, residencies, conferences and collaborations in the UK and Internationally. Previous festival editions have welcomed over 100,000 visitors from all over the world.
FORMAT is the place to engage with an incredible range of new work alongside some of the best archives and established practitioners in the world. With comprehensive professional practice programmes and a yearly International Photography Portfolio Review, FORMAT is focused on developing opportunities for audiences to see, debate, develop, contribute and participate in the best of what photography is and can be.
The biennale edition incorporates Derby's most beautiful buildings and key landmarks including: QUAD, University of Derby, Derby Museum & Art Gallery, Déda, Derwent Valley World Heritage Sites, Market Place and satellite venues in nearby cities. FORMAT is organised by QUAD and the University of Derby.


text:
Tu verras est un album de Claude Nougaro ; il sort en avril 1978 sous le label Barclay.

Autour de l'album
 Référence originale : Barclay 91 004

L'album est réédité en 2009 (référence Mercury-Universal 5314484) ; Cette édition propose en bonus le titre Nous n'avons pas de passeport (bande originale du film L'Ordre et la sécurité du monde, sorti en 45 tours en 1978).

Titres

 Titre bonus de la réédition CD :

Musiciens

 Charles Bellonzi : batterie

Album de Claude Nougaro
Album musical sorti en 1978
Album numéro un en France

redpajama_set_name: RedPajamaWikipedia


text:
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  w.add_workspace('Apps', pull_default_tasks: true)
end

redpajama_set_name: RedPajamaGithub


Malware is finding its' way on people's Android devices through apps that are downloaded from the Google Play Store. Google does a pretty good job of tracking these apps down, but sometimes it is to late and the app has already made its mark. Many of these apps had strong reviews. The battery draw occurs due to the app being on a constant run time of reporting back with information and possible grabs of your data.
On Thursday, anti-virus provider Sophos published a report describing its discovery of 22 Android apps that contained a variety of malware the company has named "Andr/Clickr-ad." The apps come from a variety of small developers, and Sophos said that Google removed them from its Play store at the end of November. One of the offending apps, Sparkle Flashlight, had been downloaded more than a million times and many of them had strong reviews, according to Sophos.


text:
\section{Introduction}
Since Generative Adversarial Network (GAN) was presented by Goodfellow in 2014\cite{goodfellow2014generative}, GAN is proved to be very efficient in image generation tasks in many research fields\cite{zhu2017unpaired}\cite{zhao2016energy}\cite{mirza2014conditional}\cite{press2017language}. Specially, many researchers use GAN for face images generation. Researchers show that the extension of GAN can not only generate face images with different poses\cite{yin2017towards}\cite{tran2017representation}, but also with different accessories\cite{chen2016infogan}. However, when the target images are too complex, GAN is still insufficient to achieve objects generation precisely.
In the other hand, different facial expression face images are always required to provide samples and labels for expression recognition\cite{elfenbein2002universality}. And multi-view face images can also be used for both pose and facial expression analysis\cite{lee2006generating}\cite{calvo2008facial}. However, insufficient facial images with different pose and facial expression bring us difficulty when using supervised machine learning methods. Although human face image datasets are not uncommon, a lot of datasets only include one frontal neutral face image for each subject\cite{LFWTech}. In order to solve this problem, we aim to synthesize different facial expression images through limited neutral images\cite{antipov2017face}. Besides, image with different pose can enrich the diversity of the face samples and could be applied to the pose recognition. It is not easy to consider both pose and facial expressions simultaneously during image translation. We need a desired generative model to comprehend the current image as well as capturing the underlying data distribution. This is often a very difficult task, since a collection of image samples on one attribute may lie on a very complex manifold. Images with multiple attributes would be further more sophisticated to be modeled. As described in Figure~\ref{fig:emotionl}, the image on the left is the input image and all the right images are the target images with 2 kinds of attributes. In order to handle this task, the model should be able to generate the target images based on the input image with the appointed attributes.

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{figure0.pdf}
\end{center}
\caption{The images in the first column are the neutral images and the other column images mean the different facial expression images synthesized by our model.}
\label{fig:emotionl}
\end{figure}

\begin{figure*}
\begin{center}
\includegraphics[width=1.0\linewidth]{figure1.pdf}
\end{center}
\caption{The framework of our model.}
\label{fig:architecture}
\end{figure*}

Many research show that the extension of GAN is able to disentangle image information encoded by vector z and by condition y making them independent \cite{isola2016image}\cite{yi2017dualgan}. We observe that vector z is able to encode persons' facial feature such as facial pose and hair styles with traditional GAN technologies. However, the traditional GAN based image-to-image methods meet difficulty when we try to translate a facial image into an image with appointed expression and pose.

Inspired by other image translation concepts, we proposed an end-to-end image translation framework that includes two generators and two discriminators for facial images generation with multiple attributes. These generators and discriminators make up a pipeline architecture. The detail of our work is shown in Figure.~\ref{fig:architecture}.

The overview of our model can be found in Figure~\ref{fig:architecture}.In consideration of the difficulty of generating images with multiple attributes at the same time, we divided the synthesizing process into two stages. We assign the two different attributes: facial expression and head pose, at the two different stages respectively. We denote two image generators as the expression generator $G_{e}$ and the pose generator $G_{p}$ for the two stages separately. Each generator has its respective discriminator. We denote the expression discriminator $D_{e}$ and the pose discriminator $D_{p}$. Similar to the idea of \cite{isola2016image}, the $G_{e}$ and the $D_{e}$ is a simple image-to-image generative adversarial network and so do $G_{p}$ and $G_{e}$. And the $X_{e}$ means the expression images that are synthesized by the expression generator and so do $X_{p}$. At the first stage. We use one generators for the pose image synthesizing. The output image $X_{p}$ and real pose images are evaluated by the pose discriminator to improve the image output quality. And then we take $X_{p}$ as the input of the expression generator $G_{e}$ for the next stage. The output images from the expression generator $G_{e}$ are the final outputs of our model. Through this pipeline operation, we can break a difficult problem into several easy steps.

It's proved that the conditional vector can represent the extension information when synthesizing images using GANs\cite{lu2017conditional}\cite{mirza2014conditional}\cite{odena2016conditional}. Zhang et al. and Reed et al.'s work also show that GANs with information are able to synthesize images conditioned on text descriptions and on spatial constraints such as bounding boxes or key points\cite{reed2016generative}\cite{zhang2016stackgan}. Following this idea, we added two conditional vectors on the coded layer of two GANs respectively. It's believed that the coded layer includes high dimensional information. By adding conditional vectors on the coded layer, we can control the facial attribute and generate the appointed synthesized images. These additional information from latent space\cite{wu2016learning} can provides the generator additional constrains and force it generates the appointed images rather than generating casually. In order to make the encoder network focus on how to select the useful features, we used an additional discriminator on the bottom neck of the encoder-decoder network for parallel classfication task to enhance the feature extraction ability of the encoder network. The detail of this conditional adversarial architecture is described in section \ref{section3.1} and \ref{section3.2}. Inspired by Chen et al.'s work\cite{chen2017photographic} and Gulrajani et al.'s work\cite{gulrajani2017improved}, we include the cascade loss and gradient penalty to improve the image generation quality \ref{section3.3} and \ref{section3.4}. The full loss function of our framework is described in section \ref{section3.5}.

Please note that there is another possible pipeline sequence of Figure~\ref{fig:architecture}. We define the sequence described in Figure~\ref{fig:architecture} as PE (pose generator at first), and we define EP (expression generator at first) as its inverse sequence structure. We evaluated these two structures in section \ref{section4}.

Our main contributions are summarized as follows:
\begin{itemize}
\item We present a new pipeline architecture that can synthesize human face images with multiple attributes. With this framework, we are able to break a tough image generation task into several easy ones.
\item We propose a parallel classification task in the bottom neck of the encoder-decoder structure to force the encoder network focus on image feature selection.
\item We merge the cascade loss into the discriminator of our model to improve the image generation performance. An independent pre-trained cascade network is deployed in the discriminator to control the generated image quality layer by layer.
\item We combine the gradient penalty with our model for the training process to make the training more stable.
\end{itemize}
Experimental results demonstrate the combination of these methods lead to convincing performance.

\section{Related work}
Recently, there have been remarkable progress in this field with the development of generative models that do not explicitly require this integration and can be trained using back-propagation algorithm. Two famous examples of such models are Generative Adversarial Networks (GANs)\cite{goodfellow2014generative} and Variational Autoencoders(VAE)\cite{KingmaW13}. These models are able to produce convincing image samples but not flexible enough to handle an image-to-image translation task with multiple attributes. Recent research related with GANs are mostly based on the work of DCGAN (deep convolutional generative adversarial network)\cite{radford2015unsupervised}. DCGAN has been proved to learn good feature representation from image pixels in many research\cite{zhu2017unpaired}\cite{isola2016image}. And the deep architectures have also shown the effectiveness of synthesizing photorealistic images in the adversarial networks\cite{chen2017photographic}.

Image generation, especially face image generation, is still a hot research topic. Some early research focus on how to recover face images using incomplete face images with stacked Autoencoders and Boltzmann Machines\cite{Hinton504}. Nowadays, many researchers focus on image generation research after GANs are proposed by Goodfellow et al \cite{goodfellow2014generative}. GAN simultaneously train two models: a generative models for generating images and a discriminative model to differentiate between natural images and generated images. The key to the success of GANs is that they proposed an adversarial loss that can both optimize the generative model and discriminative model. The two-player game aims to force the generative model to synthesize more realistic images and discriminative model to differentiate between synthesized images and natural images. In the original work of Goodfellow et al. \cite{goodfellow2014generative}, GANs were used to synthesize MNIST digits and 32*32 images that aimed to reproduce the appearance of different classes in the CIFAR-10 dataset. Denton et al. \cite{denton2015deep} proposed training multiple separate GANs, one for each level in a Laplacian pyramid. Each model is trained independently to synthesize details at its scale. Assembling separately trained models in this fashion enabled the authors to synthesize smoother images and to push resolution up to 96*96. Zhao et al. \cite{mirza2014conditional} propose the conditional GANs and combine the conditional vectors with GAN to produce the images of appointed classes. In these works, researchers focus on how to convert a noise vector $z$ into an image $G(z|y)$ with a condition $y$ based on the adversarial frameworks. Reed et al.'s work further explore this field \cite{reed2016generative}. They proposed a text-to-image framework and try to convert a noise vector $z$ under a text condition $\varphi(t)$ to generate an image $G(z,\varphi(t))$ according to the text meaning.

The recent work called InfoGAN\cite{chen2016infogan} proposed an information-theoretic extension to GANs to explore the potential of the noise vector . In their work, they decompose the input noise vector into two parts: incompressible noise $z$ and latent code $c$. And they try to make use of latent code $c$ based on the mutual information. Meanwhile, Isola et al. use a composite loss and provide an image-to-image translation solution that combines a GAN and a regression term\cite{isola2016image}. Instead of a one-dimensional conditional vector, they use a two-dimensional image as the input condition to control the input and the output performance. The authors applied their model on various datasets and demonstrate that their model is able to synthesize 256*256 images for given semantic layouts.

Due to the development of GANs, image translation successfully drawn researchers' attention. The key research of this topic is to find the mapping function from one image domain to another image domain\cite{kim2017learning}\cite{yi2017dualgan}, which can be used for image painting and the image style conversion. Zhu et al. proposed a method which contains two mapping functions, and relatively there are two adversarial discriminators\cite{zhu2017unpaired}. They introduced two cycle consistency losses that can capture the image domain distribution and the translation from one image domain to another image domain on unpaired image samples. Although we can collect unpaired images more easily than paired samples, we need paired samples with multiple attributes to design a precise image translation system. That's why we choose Isola et al.'s model for our research\cite{isola2016image}.

\section{Architecture\label{section3}}
Similar to Isola et al.'s work, our network includes six convolutional layers with stride-2 and a residual block. Both generator and discriminator use modules of the form convolution-BatchNorm-Relu which is mentioned in\cite{ronneberger2015u}. All Relus in the encoder are leaky.
\subsection{Conditional Adversarial Loss\label{section3.1}}
This objective loss with different attributes can be expressed as
\begin{equation}
\label{eq1}
\begin{split}
L_{CGAN}(G,D)=E_{x,y\sim p_{data}(x,y)}\left[ logD\left(x,y\right)\right] \\
+ E_{x\sim p_{data}(x),z\sim p_{z}(z)}\left[log(1-D(x,G(x,z)) \right]
\end{split}
\end{equation}
As an extension of Conditional GAN, the adversarial loss is a necessary term to our model. In Eq.~\ref{eq1}, the vector $z$ is a random noise vector following a prior noise distribution $p_{z}(z)$ and $x$ presents the observed image following the distribution $p_{data}(x)$. Here $x$ is also a 2-dimensional condition to the adversarial network. The adversarial framework try to learn a mapping function from $\{x,z\}$ to the target image $y$. The binary discriminator D try to classify between the real image pair $\{x,y\}$ and the synthesized pair $\{x, G(x,z)\}$. The detail of the conditional adversarial loss is shown in Figure.~\ref{fig:fig25}. Following Isola et al. and Mirza et al.'s work\cite{isola2016image}\cite{mirza2014conditional}, the condition $x$, which is required in both generator and discriminator sides, can force the generator to generate image $G(x,z)$ according to the observed x. The conditional advesarial loss is a basic requirement in a conditional adversarial network. We inherit this term as a part of our hybrid discriminator in our adversarial system.

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{figure333.pdf}
\end{center}
\caption{The conditional adversarial loss.}
\label{fig:fig25}
\end{figure}

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{figure2.pdf}
\end{center}
\caption{The parallel classification task and the conditional biases.}
\label{fig:fig2}
\end{figure}
\subsection{Parallel Classification and Conditional Biases\label{section3.2}}
We apply a parallel classification (PC) task in the coded layer for the generator as shown in Figure. \ref{fig:fig2}. We use the cross entropy as the objective function for the classification task:
\begin{equation}
L_{PC}=\sum_{k}^{K}y_{k}log{P(y=k)}
\end{equation}
Suppose we have $K$ classes ($K$ poses for example), the generator need to generate facial images with $K$ different poses based on the conditional biases $C$ from the coded layer 2. We introduce an additional classification task in the coded layer 1 to help the encoder network focus on how to extract the useful features from the raw images for encoding. After that, our model includes a conditional vector which indicates the appointed label we want. Please note that the conditional vector is inserted after we calculate the classification outputs and cross entropy error propagation to avoid short circuit. The pseudo code for training is listed in Algorithm \ref{algorithm1}.

\begin{algorithm}[t]
\caption{Pseudo code for parallel classification training.}
\label{algorithm1}
\begin{algorithmic}[1]
\STATE $i=p$
\FOR{$i=1$ to $N steps$}
\STATE Use $x'$ to get $D'(x')$
\STATE Calculate loss for encoder network
\STATE Use $x$ and $C$ to get $G(x,C)$
\STATE Calculate loss for encoder and decoder
\STATE Update the weights of the generator
\ENDFOR
\end{algorithmic}
\end{algorithm}
The classification task is implemented alternates with the image generation task. During one step, weights are updated after all the loss calcualtion of the generator are finished.

There is a copy operation between encoder and decoder networks. The classification targets are the same as the conditional biases. But the weights $w_{c1}$ from the coded layer of the encoder network to parallel classification is different with the weights $w_{c2}$ from the conditional vector to the coded layer of the decoder network. The activation value of coded layer 1 and 2 are designed as following:
\begin{equation}
y_{c1}=f(x_{c1}+b_{c1})
\end{equation}
\begin{equation}
y_{c2}=f(x_{c1}+w_{c2}C+b_{c2})
\end{equation}
where $y_{c1}$ denotes the outputs of coded layer 1 and $y_{c2}$ means the outputs of coded layer 2; $x_{c1}$ is the input of coded layer 1; $b_{c1}$ and $b_{c2}$ are the layer biases; $C$ is the conditional vector which uses one-hot encoding and $f( )$ is the activation function. Please note that the conditional vector $C$ is different with the conditional image $x$ mentioned in Eq. \ref{eq1} of section \ref{section3.1}. We use $C$ to control the expression and the pose information and make our model to synthesize the facial images with appointed pose and expression class.

\subsection{Cascade Loss\label{section3.3}}

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{figure33.pdf}
\end{center}
\caption{The framework of cascade loss.}
\label{fig:fig3}
\end{figure}

In order to make the synthesized images clearer and perform better, we consider Chen et al.'s work and include an extra pre-trained VGG-19 network to provide the cascade loss in our hybrid discriminator\cite{chen2017photographic}. Figure.~\ref{fig:fig3} shows the detail of cascade loss. The feature maps of convolutional networks can express some important information of images. To achieve lower bound between the real data distribution and the sample distributions, the cascade refinement network can provide some important guidance for our model. The cascade loss is considered as a measurement of similarity between the target and the output images. We initialize the network with the weights and bias of the pre-trained VGG network on the Imagenet dataset\cite{deng2009imagenet}. Each layer of the network will provide cascade loss between the real target images and the synthesized images. We used the first five convolutional layers for the cascade refine network.
\begin{equation}
\label{eq5}
{L}_{Cascade}(\theta)=\sum^{N}_{n}{\lambda}_{n}||{\Phi}_{n}(x)-{\Phi}_{n}(G((x,z);\theta))||_{1}
\end{equation}
Following the definition mentioned in Eq. \ref{eq1}, here $y$ denotes the target image and $(G(x,z))$ is the image produced by the generator $G$; $\theta$ is the parameters of the generator G; $ {\Phi}_{n}$ is the cascade response in the $n_{th}$ level in the Cascade Refinement Network (CRN). We choose the first 5 convolutional layers in VGG-19 to calculate the cascade loss. So we have $N=5$. Please note the loss ${L}_{cascade}(\theta)$ mentioned in Eq. \ref{eq5} is only used to train the parameter $\theta$ of the generator G. The CRN is a pre-trained network. The weights of CRN will not be changed during we train the generator G. The parameter ${\lambda}_{n}$ controls the influence of cascade loss in the $n_{th}$ layer of CRN.

The cascade loss can provide measure the similarity between the output and the target images under $N$ different scales and enhance the ability of discriminator. Cascade loss from the higher layer controls the global structure; the loss from the low layer controls the local detail during generation. Thus, the generator should provide better synthesized images to cheat the hybrid discriminator and finally improve the synthesized image quality. The loss constrains the generator and aims to seek the boundary between the real data distribution and sample data distribution.
\subsection{Gradient Penalty\label{section3.4}}
To further improve the performance of GANs, we consider Gulrajani et al.'s work and include the gradient penalty (GP) to our model\cite{gulrajani2017improved}. The gradient penalty can be expressed as
\begin{equation}
L_{GP} = E_{\hat{x}\sim P_{\hat{x}}} \left[(\left \| \bigtriangledown_{\hat{x}}D(\hat{x})\right \| _{2}- 1)^{2}\right]
\end{equation}
\begin{equation}
\hat{x}=(1-\alpha)x+\alpha \tilde{x}\: \: \: \: \: where\: \alpha\sim U[0 , 1]
\end{equation}
Here $x$ represents the real sample and $\tilde{x}$ means the synthesized sample; $\alpha$ is the random parameter that controls the balance between real and fake and follows the average distribution between 0 and 1; $\bigtriangledown_{\hat{x}}$ is the gradient of $D(\hat{x})$. Please note that $\hat{x}$ is only used for calculating $L_{gp}$. We believe that the GAN with gradient penalty converge more stable and generate images with higher quality. The experiment results in section \ref{section4} also supports this point.

\subsection{Generative loss\label{section3.5}}
As mentioned in Isola et al.'s work \cite{isola2016image}, location loss is really important for synthesizing images. In our network, we use the L1 loss as the location loss. So the total loss of our generator is defined as:
\begin{equation}
\begin{split}
L = \xi_{1}L_{CGAN}(G,D) + \xi_{2}L_{Cascade} + \\
\xi_{3}L_{GP} + \xi_{4}L_{PC}+\xi_{5}\left\| y -G(x,z) \right\|_{1}
\end{split}
\end{equation}
Here $y$ is the target image and $G(x,z)$ is the image synthesized by the generator. In our experiments, we find that the model performs well when we choose $\xi_{1}=\xi_{2}=\xi_{3}=1, \xi_{4}=10, \xi_{5}=50$. And our final loss is the sum of this three different loss. We apply this final loss to the generator with Adam optimizer of learning rate $0.0002$.In our experiments.

\section{Experimental results\label{section4}}

\subsection{Datasets}
We test our methods on three face datasets. We use two datasets to evaluate the image generation ability on pose direction and facial expression, respectively. The first dataset we used is FEI dataset\cite{thomaz2012fei}. This dataset contains 11 different pose directions from 200 individuals. Then we evaluate our methods for facial expression generation on the Yale dataset\cite{georghiades1997yale} which consist of 15 individuals and 6 different kinds of facial expression. In these two experiments, images only contains one attribute. Thus, we only use half of the model which we mentioned in Figure.~\ref{fig:architecture} for comparison and evaluation. At last, we train our model on the Karolinska Directed Emotional Faces dataset (KDEF)\cite{calvo2008facial} and evaluate the image generation ability with multiple attributes. The KDEF datasets is a set of totally 4900 pictures of human facial expressions pictures with different pose. Each subject contains 5 different pose and 7 emotional expressions (totally $5*7=35$ images). So it has 35 different face images for each person. We split the datasets into training dataset and testing dataset for 4:1.

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{figure6.pdf}
\end{center}
\caption{Head pose generation results with different methods.}
\label{fig:fei_compare}
\end{figure}

\begin{figure*}
\begin{center}
\includegraphics[width=1.0\linewidth,height=1.0\textheight,keepaspectratio]{figure7.pdf}
\end{center}
\caption{Head pose generation results on 10 different angles. The images from the first column on the left are the inputs and the left images are the synthesized samples.}
\label{fig:fei_merge}
\end{figure*}

\subsection{Head pose generation\label{section4.2}}
In the FEI database, each individual contains 1 standard frontal facial image and 10 kinds of images with different pose direction. We choose the standard frontal facial image as the input for our model to generate the left 10 classes. In this task, we aim to generate images with different pose. A comparison is displayed in Figure.~\ref{fig:fei_compare}. It seems that each method is able to generate an image with the correct head direction. However, a synthesized image with correct facial detail is not an easy task. The results of Pix2pix is blur and fail to generate the eyes. The results impove when we integrate more methods mentioned in section \ref{section3}. Our methods performs better when we considered parallel classification, cascade loss and gradient penalty simultaneously.

Figure.~\ref{fig:fei_merge} shows more pose generation results on 10 different pose with our methods (Pix2pix + Cascade + GP + PC). In most of cases, our model can generate clear images with correct local facial information. The results also prove that the conditional vectors which we defined in \ref{section3.2} on the coded layer successfully controls the pose direction well.

\subsection{Facial expression generation\label{section4.3}}
In the Yale dataset, we choose 1 neutral facial image as the input of our model and the left 5 different facial expression images as the targets to evaluate the expression generation performance of our model. Figure.~\ref{fig:yale_compare} shows the comparing testing results using different methods. At the first glance, each method seems to be able to generate images with the correct expression. If we enlarge the image size, we can find that the image generated by Pix2pix has a unclear boundary surrounding the subject's face. And our model can generate a clear facial image after we integrate Pix2pix with cascade loss, gradient penalty and parallel classification.

Figure.~\ref{fig:yale_merge} shows more testing results in the Yale face datasets using our methods. These plausible generations show that our model can solve these image transfer tasks with one attribute well.
\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{yale-compare.pdf}
\end{center}
\caption{Facial expression generation results with different methods.}
\label{fig:yale_compare}
\end{figure}

\begin{figure}[t]
\begin{center}
\includegraphics[width=1.0\linewidth]{yale_data.pdf}
\end{center}
\caption{Facial expression generation results on 5 different classes.}
\label{fig:yale_merge}
\end{figure}

\begin{table}
\begin{center}
\begin{tabular}{|c|c|c|c|}
\hline
Method & P-SNR &MSE &R-MSE\\
\hline\hline
Ours & 17.0296 & 0.01394& 0.1158\\
PE + Cascade +GP & 16.9893 & 0.01411 &0.1163 \\
PE + Cascade & 16.8210 & 0.01451 & 0.1183\\
PE + GP& 16.9636 & 0.01410 & 0.1166 \\
PE & 16.4461 & 0.01586 & 0.1237\\
EP+GP& 16.5461 & 0.01547 & 0.1222\\
EP& 16.4180 & 0.01557 & 0.1236\\
Pix2pix & 17.0004 & 0.01556 & 0.1230\\
\hline
\end{tabular}
\end{center}
\caption{Multiple attributes generation task using different methods on KDEF dataset.}
\label{table:comparison}
\end{table}

\begin{figure*}
\begin{center}
\includegraphics[width=1.0\linewidth,height=1.0\textheight,keepaspectratio]{figure10.pdf}
\end{center}
\caption{Image generation results on different subjects with multiple attributes. (a) subject 1 with -45 degrees and a sad expression; (b) subject 2 with +45 degree and a disgust expression; (c) subject 3 with -90 degree and a happy expression; (d)subject 3 with -45 degree and a happy expression.}
\label{fig:fig10}
\end{figure*}

\subsection{Face generation with multiple attributes}
In this paper, our final goal is to develop a model to generate images with multiple attributes using a Pipeline generative adversarial network. We choose KDEF dataset to evaluate the performance of our model on this task. There are 4900 images including 5 different angles (-90, -45, 0, +45, +90 degrees) and 7 different expressions (afraid, angry, disgusted, happy, neutral, sad, surprised) from 70 participants (35 males and 35 females) in this dataset. Similar to the experiments mentioned in section \ref{section4.2} and \ref{section4.3}, we use one neutral straight image as the model input to generate facial images with 4 different poses using the Generator 1 (Figure.~\ref{fig:architecture}). In this step, we can generate 4 different poses with neutral expression. And these images are reused as the inputs for the Generator 2 to generate $4\time6=24$ facial images. The Table.~\ref{table:comparison} shows the image evaluation results of our experiments. Although Pix2pix has a similar P-SNR (higher is better) comparing to our methods, it has a poor performance on MSE and R-MSE (lower is better on both criteria). Our model, which integrate PE structure, Cascade loss, gradient penalty and parallel classification, has the best performs when considering cascade loss, gradient penalty, cross entropy and Pose-Emotion (PE) pipeline structure simultaneously. It should be noted that we find that PE structure performs better than EP structure. By using this trick, our results can be clearer and can generate elaborate images with plausible parts such as teeth, eyes and so on. Because we find that pose generation task on KDEF has better performance than facial expression generation task on the Generator 1. The generation quality of the first generator will influent the performance of the next generator. That's why we choose PE structure in Figure.~\ref{fig:architecture}.

We evaluate the generation performance with multiple attribution of each model in Figure.~\ref{fig:fig10}. The first column image is the input of each model, other images represent outputs. (a), (b) and (c) show the performance of each model using 3 different subjects. (c) and (d) represent the generation results using the same subject with different attribute outputs (-90 degrees + happy). In the second column, we can find that the results of a single Pix2pix model are blur with distorted facial features. In this task, we try to generate $4\time6=24$ kinds of images with a single Pix2pix model. The result show that it's possible for a Pix2pix model to generate a facial image with correct head pose. But it fail to generate the correct expression in (b), (c) and (d) cases. Images in the third and the fifth column show the results of a pipeline Pix2pix structure of PE (pose first) and EP (expression first), respectively. In these two tasks, one Pix2pix model is only used to generate images with one attribute (pose or expression). The results of PE and EP perform better than a single Pix2pix case. We guess that the expression image generation is more difficult than pose image generation on KDEF dataset. However, the image detail of these two models are still very poor. Relatively, PE performs better than EP structure. The mouth generated by PE model is more approaching to the ground truth. We get better image quality when we include gradient penalty on PE and EP structure. We further enhanced the generation quality when we integrate GP and cascade loss on PE structure. And our method achieves the best performance among these methods.

\section{Conclusion}
In this paper, we proposed a new architecture that can generate facial images with multiple different attributes. And the pipeline architecture with two different generators and two discriminators can reduce the difficulty of each generator and guarantee the final image translation results. This direct approach can divide the difficult task into two stages and perform better than contemporaneous work single GAN based model. Furthermore, we successfully improve the image generation performance by adding cascade loss, gradient penalty and parallel classification. Our method also provide a new way for image data augmentation under multiple attributes.

Nowadays, unsupervised learning is very popular because its good performance in representation learning \cite{zhu2017unpaired}. On the other side, summarizing multiple attributes from images is not an easy work if the image is complex. How to collect attributes automatically through unsupervised learning is an interesting work. We leave this part in our future work.

{\small
\bibliographystyle{ieee}

redpajama_set_name: RedPajamaArXiv


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Q: Unable to switch between segments for UISegment Control Below is the code snippet I am using to set up my UISegment Control
//Add UIView below the nav bar
UIView *buttonContainer = [[UIView alloc]initWithFrame:CGRectMake(0, 0, 320, 30)];

[self.view addSubview:buttonContainer];

//Set up segment control
NSString *nicknameLabel = [NSString stringWithFormat:@"%@",self.nickname];

UISegmentedControl *tempSegmentControl = [[UISegmentedControl alloc]initWithItems:[NSArray arrayWithObjects:nicknameLabel,@"Friends", @"Everyone", nil]];
tempSegmentControl.frame = CGRectMake(-8, 44, 336, 30);

self.segmentControl = tempSegmentControl;
[self.segmentControl setWidth:112 forSegmentAtIndex:0];
[self.segmentControl setWidth:112 forSegmentAtIndex:1];
[self.segmentControl setWidth:112 forSegmentAtIndex:2];
self.segmentControl.selectedSegmentIndex = 0;
[self.segmentControl addTarget:self action:@selector(toggleControls:) forControlEvents:UIControlEventValueChanged];
[self.segmentControl setSegmentedControlStyle:UISegmentedControlStylePlain];

[self changeSegmentFontSize];

[tempSegmentControl release];
[buttonContainer addSubview:self.segmentControl];
[self.view bringSubviewToFront:buttonContainer];
[buttonContainer bringSubviewToFront:self.segmentControl];
[buttonContainer release];

However, I in the app, I am unable to switch between the segments for the segmented control. (only show default first segment highlighted)

Any advice on how I can fix this?

A: It looks like a bounds problem. The containing view has bounds {0, 0, 320, 30} while the segmented control has {-8, 44, 336, 30}. This means the segmented control is technically "outside" its containing view and the iOS hit test will not register a touch.
Try not setting the segmented control's frame (temporarily comment out the tempSegmentControl.frame = CGRectMake(-8, 44, 336, 30); line) and see what happens.

A: *

*Check that userInteractionEnabled is set to TRUE for your view, buttonContainer, and segment control.

*Check that the bounds of the buttonContainer's superview are wide and tall enough to fully contain the buttonContainer.  If they're not then hit-testing wont work and the segmented control wont get any touches.

redpajama_set_name: RedPajamaStackExchange


Closing Weekend...get those scripts in!
We are in the final stretch of our inaugural call for submissions! Submissions will be accepted until 11:59pm PST on May 1 (that's Monday!). Get your script in for consideration here!
The Talk Back team has been floored by the number of submissions we have received, the breadth of issues being explored, and the diversity of playwrights sharing their work. Add your voice!


I was at a non-denominational summer camp when this question came up. It was the summer of 1984; I was thirteen-years old, identified as Jewish, and there had been three hijackings in the news. My friends and I had just talked a Florida camper down from tears. She was sure that her plane would be diverted to Cuba.
Because of how I choose to present my Judaism, it's pretty easy to be overlooked as a just another white person who might raise a tree on December 25th (I did in 20 years of marriage to a non-Jew) and eat chocolate bunnies in the spring. (Who would pass up chocolate—not me.) But that ability to pass, often makes me privy to microaggressions and anti-semitism that sometimes happen within closed groups. To avoid that, I often declare myself as Jewish early in new work relationships. I'm no shrinking violet and it's my moral imperative to not only speak up for all underrepresented people in negative situations but also to advocate positively for diversity and equality.
The growing anti-semitism in our country goes hand in hand with other messages of hate and othering against: Muslims, immigrants, LGBTQ people, and all brown and black people. The recent comments (from those who sit in the whitest White House in recent history) about Emma Lazarus's poem on the Statue of Liberty and our President's on-going reaction to the racist and anti-Semitic events of Charlottesville bring me to tears. There is no doubt that KKK and neo-Nazi members, and others who label themselves as white supremacists are emboldened by the friend they have in President Trump. I am equally aghast whenever I see Jewish organizations supporting this president.
What does one do when it looks as if our entire country has stepped into a time machine that takes us back to (reveals that we never left) an amorphous period between 1890 and 1969?
In addition to my donation, I will continue to shut up and listen to those who face bigots daily simply because of the color of their skin. I will stand up, speak out for, and ask difficult questions about equality, diversity, and peace in my art, writing, personal, and professional life. I will suggest wonderful books to children and families that provide empathy and education. And if, G-d forbid, I am put in a situation where I have to declare my identity and face possible harm, I hope we will all stand together on the same side of that plane as human beings.
Two big deadlines are coming up for kidlit authors and illustrators of color.
One, the New Visions Writer's Award from Lee & Low Publishing.
The NEW VISIONS AWARD will be given for a middle grade or young adult fantasy, science fiction, or mystery novel by a writer of color. The Award winner receives a cash grant of $1000 and our standard publication contract, including our basic advance and royalties for a first time author. An Honor Award winner will receive a cash grant of $500.
Submissions are due October 31st. Click for details.
The second, is the new SCBWI On-The-Verge Emerging Voices Award.
The grant was created to foster the emergence of diverse voices in children's books. The grant will be given to two writers or illustrators who are from an ethnic and/or cultural background that is traditionally under-represented in children's literature in America.
Two writers or writer/illustrators will each receive an all-expenses paid trip to the SCBWI Winter Conference in New York to meet with editors and agents, a press release to publishers, a year of free membership to SCBWI, and an SCBWI mentor for a year.
Submissions are due November 15th. Click for details.
Please share freely and encourage those who are eligible to submit!
Just the other day I got to be with New England Web guru and ARA Greg Fishbone, author of Galaxy Games published by Tu Books. Check it out then submit your own speculative fiction. Read guidlines carefully please.
For more information on how to submit, please see our submission guidelines at http://www.leeandlow.com/p/tu_submissions.mhtml. We are not accepting unagented email submissions at this time.
What we're particularly interested in seeing lately: Asian steampunk, any African culture, contemporary African-American stories, Latino/a stories, First Nations/Native American/Aboriginal fantasy or science fiction written by tribal members, original postapocalyptic worlds, historical fantasy or mystery set in a non-Western setting.
We look forward to reading your book!


Losing Sanity: Week One: We Survived!
Today's Friday! End of the first week of school AKA the longest week of the year. Who knew that being a mom would mean I would get to suffer the pangs and indignities of childhood doublefold.
Here are the low points and high notes of week one.
Child #2 walks home sobbing because he's already incurred three time outs. I experience a pang of resentment for his teacher, even as I remind him of the importance of listening, instead of talking, (he's my chatty one) and keeping your hands to yourself (also my grabby one). A short chat with the object of my resentment the next morning reassures me they weren't so much time outs as reminders to listen. Hmm, that explains why he described them as short time outs.
Child #1 realizes that all her best friends are in the other fourth grades. "Mom, every one is friends with each other and no one is friends with me." My heart breaks. Honestly and truly, it just breaks but I hold it together and point out how lucky she is to have the opportunity to make a whole bunch of new friends this year. "You'll have all your old friends AND all the new ones you make this year." She looks skeptical. I don't blame her, but she does agree to ask to try to sit with a couple of the nicer girls at lunchtime.
Child #2 describes his teacher as "hot". "She's hot?" I ask. "Yeah, especially in the afternoon 'cause there's no air-conditioning in our class."
Child #1 comes home excited about maps. "Did you know they made the first maps out of clay in Egypt? We get to make a bumpy map [topographical] that shows mountains and volcanoes out of packaged frosting." Child #1 has a deep fondness for packaged frosting ever since I banned it from our home.
It's ups, it's downs. One minute they're happy. The next, life is terrible, miserable, awful, end of the world. I mirror whatever they're feeling with an intensity they would find laughable. In the end Child #2 says it best, "This week's been kinda good, kinda bad. Mostly, I'm looking forward to the ice cream social on Friday."
Have you had the talk about the "Sometimes friends"? The ones that are only friends when there is no one else for them to play with.
You said it. Any slights that my girls suffered when they were younger stayed with me a lot longer than with them!
Thanks for joining the Insecure Writer's Support Group, Look forward to your first post on October 5.


How to make the most of every moment of your summer in Calgary. 6 new reasons to go to the mountains. Plus local brews: all you need to know about the city's big five microbreweries and the new brew pubs and breweries that are coming soon.


Discussion in 'B4J Share Your Creations' started by thedesolatesoul, Mar 7, 2015.
Create a server that holds B4A library information in a easily searchable and linkable format.
It needs to be easy to input data. And easy to find libraries.
It requires you to upload your library xml file to get critical information. This code is adapter from Erel's form and upload tutorial.
The xml is parsed with a sax parser till we hit EndElement(Root). The information gained is libraryname, version, author, classes list.
This data is inserted into a simple SQLite table. (No duplicate checking is done).
On the Library list page, it uses a jQuery datatable (adapted from Erel's example on datatables). As I dont know how to do server-side filtering, the whole table is downloaded in a json array and fed to the datatable. The result is very fast filtering and searching.
- More annotations exported into the xml. A library description and class description annotation will help. This will mean it is easier to import the information without additional fields in the form.
This is opensource, I may or may not work on this anymore.
Currently I dont have a VPS to host this on.
Thank you to @Erel for B4J and the tutorials, very useful and informative. I'm not a web guy, but it was enough for me to create a workable solution.
Erel, klaus, Peter Simpson and 1 other person like this.
To be honest not so hard.
But I'd like to see what direction this takes in the community if any.
I'm pretty sure that you already know my opinion, however how will it be different than the built-in search engine which makes it simple to filter libraries only results?
1. All the data is already there and it is always up to date. There is no need to do anything special to keep it updated.
2. The search engine itself is based on Lucene which is much more powerful than using a simple substring based filter.
3. This is the same tool that you use to search for any other information about B4X products.
I'm aware of your opinion and I respect that. I'm not expecting you to change anything.
how will it be different than the built-in search engine which makes it simple to filter libraries only results?
- Any search and search engine is as good as the information put into it. There is an amazing amount of junk questions on the forum, so sometimes a more recent 'Where can I find <library>" is ranked higher than "<Library>" thread. Put simply there is too much junk and useless questions on the forum than for e.g. 3 years ago. Its makes searching so much harder. While Lucene may be more powerful than a substring based filter, it has to shift through more junk, while this tool doesnt require anything more than a substring filter. Lucene is an overdesigned solution for a simpler problem.
- With the search & find library, we end up reading more text to get to the point. Its not a clear user experience.
- With my method mentioned above, we embed all the required information to make the library searchable/categorisable into the essential files (xml) itself. This means it is searchable on any platform. Even the B4A IDE can add a search function to search the local subset of libraries for a particular class (for e.g. in the Phone library).
- Categorization. For e.g. libraries such as WebViewUtils or WebViewExtras. Nobody knows what the library does until you read everything in it, but by categorizing them in a WebView library category, and simply two clicks you can read their documentation and included functions. The search engine cannot do this (well you open two pages on the forum, and ignore the boilerplate).
Personally, I thought there is too much talk and not much 'do' on the forum. I wrote this so I can retain my right to talk. If I get time I might improve on it.
JakeBullet70, rwblinn, Erel and 2 others like this.


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What it's like to get Covid 19 and recover from it
Laura Jacobs got the virus after her mum returned from a holiday to Italy
Kathryn Williams
The Covid-19 news is having a negative impact on the nation day by day, but one Welsh mother & NHS worker wants others to know you can get better, after being tested for the virus at the start of March.
Laura Jacobs contracted the virus after her parents returned from Italy in mid-February, has spoken about what it's like to have the illness and how long she took to get over it.
Laura's mother, Melissa Powell, and Laura's husband Matthew, also came down with the coronavirus and were tested at home when testing in the community was still being carried out.
Morriston Hospital worker, Laura, said of her coronavirus experience on Facebook: "Since I am one of the first few 'recovered' Covid 19 patients in Wales, I feel like it's important to share my story, especially with all of the current panic and unrest going on.
"My symptoms came from nowhere. I felt absolutely fine at work and then bang, all of the symptoms arrived at once. I had a high fever, shivers, intense aching pains in my back and neck, sore throat, painfully tight chest and fatigue."
Laura, husband Matthew and their children Ava and Miles (Image: Laura Jacobs)
Along with Matthew, five-year-old daughter Ava and 10-month-old Miles, Laura was tested on Monday, March 9 - a day after her mother - by a nurse.
She told us: "I wanted people to see that you shouldn't take it lightly but also that there's so much negative stuff being reported in the media, I think people just want reassurance.
"My mum had been to Italy and went to an area that wasn't infected at the time, there were no reported cases, they came back on Sunday, February 22, within three days my mum started showing symptoms and then I caught it off her."
Laura, who is 31 and from Neath, explained that her mother had worse symptoms as she has a history of pneumonia.
"At first I thought I had the flu, I knew it wasn't a cold. It was much worse, I hadn't had my flu jab like every other year," she added.
"As time went on we saw in the news there were reported cases in the part of Italy they went to and it couldn't be a coincidence.
"So, Mam requested a test and was tested positive, that was Sunday March 8 and on March 9 - I was tested. At the time they were doing community testing, as only a handful people in Wales were confirmed to have it.
"A community nurse came to the house in protective clothing, a mask and visor. She tested me, my husband and children at the same time.
"It was awful. We did pre-warn my daughter she was ok with she wasn't thrilled with the throat swab, but they were ok.
"The kids came back as negative and we were surprised because we are round them all the time, giving them hugs and kisses. But that goes to show, people are worried about their kids, I've had loads of messages from people, but it seems they are a lot more resilient to it."
Laura from Neath had Covid-19 after catching it from her mother Melissa (right), who came back from Italy at the end of Feb. (Image: Laura Jacobs)
Laura has detailed her symptoms on Facebook, but she also spoke to WalesOnline a bit more about how she felt.
"I did feel really unwell, I'm healthy, I've never been really really unwell to compare it. The worst was the fever for days,high temp shivers, horrible aching up my back and around my neck, you feel like you can't move, exhausted.
"After the fever lifted, I started to feel a bit better in myself, it travelled down to my throat so I have a really sore throat and then I had a drier cough which I still have now. The fever is definitely the worst bit."
However, husband Matthew was hit worse, as the 35-year-old has asthma and he developed viral pneumonia and was admitted to Morriston Hospital overnight.
"He is on the mend the past two days, he's eating more," she said, adding how the couple coped with having the family home in quarantine with two small children.
"The consultant advised us to isolate ourselves from the kids as much as possible, which is difficult as they are so young. But we just constantly wash hands before feeding and dressing them, anti-baccing door handles, tables remotes and avoiding hugs and kisses. Everything for Miles is sterilized anyway as he's under one," Laura said.
"It was hard, it was a little bit scary for my five-year-old. She was told all of a sudden she couldn't go to school, go out of the house, go up the park and daddy is not well and there's a nurse coming."
Supermarkets face more restrictions
Schools in Wales closed until February
Pfizer jab works on mutant strain
Wales falls behind in vaccine rollout
Laura said she has had lots of messages about children and hoped her post would show people the virus, for most people wouldn't have people unwell forever.
"I think people are just really frightened," said Laura, who hopes that she'll be able to practically help those coming down with the virus, when she is fully recovered.
" I think it's because it's something new and unknown and you have no answers about how long you'll be ill for, does it get worse, what are the complications and that's a common thread in the messages I have had.
"People want answers, about whether they had a cough and how long for, and there's a lot of negativity with the numbers of deaths, cases doubling, the ITU beds being full, you need to hear about people getting better, and the more people hear about those stories the better."
Laura and daughter Ava when they were self-isolating
Laura is hoping that when she's able to return to work she'll be of help, but at the moment she's limited to open spaces because of her cough.
"My consultant is quite confident that once you have had it once you won't have it again," said Laura. "I'm hoping I can help people now and we're in quite a good position to help people out by dropping stuff off. And I work at Morriston Hospital
I don't have face-to-face contact with patients more of an admin role, but work as I know it, is going to be suspended as of now.
"It might be nice for me to do more face-to-face contact as I can't catch it off anyone.
"But it's all wait and see for now."


text:
Beyonce & Jay-Z Dress Daughter In Mini Michael Jackson Costume
She has previously claimed Michael Jackson made her the artist that she is today, and Beyonce again paid tribute to the late star on Friday with help from her only child. The hitmaker's daughter Blue Ivy emerged in New York dressed as the King Of Pop to attend a Halloween bash with her parents in the city's West Village. The little one was carried to the car by her father Jay Z while dressed in the Billie Jean singer's iconic red and gold jacket, while Beyonce, 33, channeled his sister Janet.


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Mayor Myrick endorses Seth Peacock for City Judge
by Madison Fernandez June 18, 2020 June 19, 2020
ITHACA, N.Y. — Mayor Svante Myrick has endorsed Seth Peacock for Ithaca City Court Judge.
"I believe that Seth is the right person for this seat," Myrick said in a Facebook live video on June 16. "He's the right person to lead the court at this moment, and that going to vote for him now is one piece of a much larger necessary puzzle if we're going to achieve justice here in the City of Ithaca with our system."
Myrick has shown his support for Peacock in the past by appointing him city court judge on an interim basis twice, once in 2014 and again in 2019, to fill a vacancy left by now-County Judge Scott Miller. Peacock is currently one of the two city court judges.
Myrick praised Peacock's engagement with the community, from coaching youth to serving on the board of the Ithaca City School District. He said that Peacock has matured over his career as a lawyer and has successfully run Ithaca's first Wellness and Recovery Court.
Peacock is the first and only person of color to serve on the bench in the Sixth Judicial District.
Peacock has garnered a number of other endorsements, including over 40 Ithaca attorneys; Leslyn McBean-Clairborne, chair of the Tompkins Legislature and J.R. Clairborne, former City of Ithaca common council member; Cornell University professor emeritus Richard Talman; executive director of the Greater Ithaca Activities Center Travis Brooks; member of the Tompkins County Human Rights Commission Kathleen Bergin; and common council members Deborah Mohlenhoff, Cynthia Brock, and George McGonigal.
The city court judge position is a 10-year term, which will begin January 1, 2021. Dan Johnson, Tompkins County assistant district attorney, is running against Peacock.
"I am grateful for his steady support especially regarding those areas and issues that we are both concerned with like Ithaca Wellness and Recovery Court and alternatives to incarceration," Peacock said. "We also share the belief that a strong connection to the entire Ithaca community is a necessary characteristic of an effective judge. I also agree that having a representative judiciary enhances the legal system's legitimacy."
New York State is holding its primary elections for state and local offices on June 23. Eligible voters can vote via absentee ballot due to the COVID-19 pandemic, and those ballots must be postmarked by June 23. Voters can also cast their ballot in person during early voting from June 13 to June 21, and in-person voting will take place on June 23. Other elections on the democratic primary City of Ithaca ballot are for the New York State 125th Assembly District, as well as Tompkins County district attorney.
Tagged: election, Ithaca City Court Judge, primary, seth peacock, svante myrick
Madison Fernandez
Madison Fernandez is a contributing reporter at the Ithaca Voice. You can reach her by email at mfernandez@ithacavoice.com. More by Madison Fernandez


I'm looking for advice on what to do with tax deferred retirement accounts from a previous employer. Long story short, I'm 35 now. I taught at a major east coast university for about two and a half years before deciding academia wasn't for me and going to grad school in my late 20s (I was an actor/musician before that, so needless to say, no investments from that time). I now work for a government agency with no intent to leave and I am invested in the federal TSP program for retirement which is presently in a lifecycle account and doing quite well. Given my projected income, over the years, I anticipate being well taken care of by my various retirement investments from this job alone, despite not getting this job until my early 30s. I'm also eligible for the public interest loan repayment program on my student loans (hopefully congress won't get rid of it in the next seven and a half years- fingers crossed!). My real question is this: while at the university, I invested in the university's tax deferred retirement plan, essentially, a 401K. Actually, when I signed up, the person helping us suggested splitting it between two separate companies, so I now have one account at vanguard and one at tiaa. The vanguard account had more in it to begin with and has done quite well, all things considered; it now has about $15k in it. The tiaa account was barely funded (I think I only put 20% of my total investment in it in the first place and, unlike the vanguard account, it did not receive the benefit of my employer match); it now has just shy of $1900 in it. I'm curious what to do about these accounts. I considered rolling them both over into the TSP but that makes me nervous for reasons I can't explain, although it certainly is an option. Because they were both employer plans, I can't really contribute more to them since I no longer work for that employer and they are both kind of just sitting there doing their thing. I've also considered leaving them separate from my tsp and putting them into more aggressive investment accounts available through the employer plan, but I'm not sure if that is a wise choice (both are presently in lifecycle funds). Does anyone have any suggestions on what to do with old employer retirement accounts?
Roll them over into a Rollover IRA at a discount brokerage like Fidelity or Vanguard. This will give you direct control with more investment options.
Give either a call - they can walk you through exactly what to do.
This is a rather complicated question for me to calculate! I don't know what to do and how to deal with old employer retirement accounts. However, I will be happy to get answers!


The Office of the Queensland Chief Entrepreneur has been working with Australian online platform Wholesale Investor which connects emerging companies with over 17,700 international private investors including venture capital, family offices, brokers and private equity.
Wholesale Investor is bringing their team to Brisbane along with over 50 investors. The premier event will showcase a short-list of leading emerging growth companies on a single stage and allow you to discover the latest unseen investment opportunities.
Register now to join up to 150 high net worth and professional investors to network with leading innovators, entrepreneurs and like-minded investors.


text:
Diestelkamp ist der Familienname folgender Personen:

 Adolf Diestelkamp (1900–1955), deutscher Archivar und Diplomatiker
 Bernhard Diestelkamp (* 1929), deutscher Rechtshistoriker, Sohn von Adolf
 Erich Diestelkamp (1900–1983), NSDAP-Politiker

Siehe auch:
 Distelkamp


text:
PODCAST: Joe O'Biden, Oil Production, Energy Prices & Politics
October 19, 2022 /in DrRichSwier.com, Energy, Environment, Politics, Regulation, Science /by DrRichSwier.com
By Conservative Commandos Radio Show
GUESTS AND TOPICS
DR. JOHN R. LOTT, JR.
Dr. John R. Lott, Jr., is the founder of The Crime Prevention Research Center (CPRC), an economist and a world-recognized expert on guns and crime. During the Trump administration, he served as the Senior Advisor for Research and Statistics in the Office of Justice Programs and then the Office of Legal Policy in the U.S. Department of Justice. Lott has held research or teaching positions at various academic institutions including the University of Chicago, Yale University, the Wharton School of the University of Pennsylvania, Stanford University, UCLA, and Rice University, and was the chief economist at the United States Sentencing Commission during 1988-1989. His latest book is: Gun Control Myths: How politicians, the media, and botched "studies" have twisted the facts on gun control.
TOPIC: Media Spin on Gun Control Doesn't Match Voters!
GEORGE LANDRITH
George Landrith, President and CEO of Frontiers of Freedom – a public policy think tank devoted to promoting a strong national defense, free markets, individual liberty, and constitutionally limited government. In 1994 and 1996, Landrith was the Republican candidate for the U.S. House of Representatives from Virginia's Fifth Congressional District. His work has been printed across the nation, including: Washington Times, Chicago Tribune, LA Daily News, National Review, Sacramento Bee, Ft. Worth Star-Telegram, Providence Journal, Daily Caller, Washington Examiner, Townhall, and Human Events. George Landrith is also a co-host here on the Conservative Commandos Radio Show.
TOPIC: Joe Biden, Oil Production, Energy Prices & Politics!
TODAYS GUEST HOST: Rick Manning is a Conservative Commandos and AUN-TV alumnus and the President, Americans for Limited Government. Rick also served on President Trump's transition team. And he is also the author of the new book with Starr Parker — "Necessary Noise: How Donald Trump Inflames the Culture War and Why this is good for America!"
©Conservative Commandos Radio and AUN-TV. All rights reserved.
This article is courtesy of DrRichSwier.com, an online community of citizen journalists, academics, subject matter experts, and activists to express the principles of limited government and personal liberty to the public, to policy makers, and to political activists. Please visit DrRichSwier.com for more great content.
https://libertyfirst.org/wp-content/uploads/logo_v6_225x110.png 0 0 DrRichSwier.com https://libertyfirst.org/wp-content/uploads/logo_v6_225x110.png DrRichSwier.com2022-10-19 23:51:312022-10-19 23:51:31PODCAST: Joe O'Biden, Oil Production, Energy Prices & Politics


text:
Chinese police crack down on bitcoin miners over $3m of stolen electricity
Police in eastern city of Zhenjiang confiscate almost 4,000 of bitcoin mining devices
Bitcoin's value has surged after Facebook announced its own cryptocurrency, Libra. Photograph: Chesnot/Getty Images
Agence France-Press
Fri 12 Jul 2019 11.13 EDT
Police in eastern China have cracked down on a ring of illicit bitcoin miners who stole nearly $3m (£2.4m) worth of electricity to generate the digital currency, prompting a local power company to tip off investigators, authorities said.
Police in Zhenjiang, in eastern Jiangsu province, said officers confiscated almost 4,000 mining devices from an illicit bitcoin operation that stole nearly 20m yuan in power.
"In value, it is the largest case in the amount of electricity stolen that Jiangsu has cracked since the founding of new China, and a rare sight in the whole country," Zhenjiang police said in an online statement.
The authorities said they were originally tipped off by a local power company, which reported abnormal electricity usage.
Police have taken "compulsory measures" against more than 20 criminal suspects, and the case is under investigation.
Cryptocurrencies are an alternative way of making payments to cash or credit cards. The technology behind it allows the 'money' to be sent directly to others without it having to pass through the banking system. For that reason they are outside the control of governments and are unregulated by financial watchdogs – and transactions can be made in a way that keeps you reasonably pseudonymous.
If you own a crypto-asset you control a secret digital key that you can use to prove to anyone on the network that a certain amount of that asset is yours. If you spend it, you tell the entire network that you have transferred ownership of it, and use the same key to prove that you are telling the truth. Over time, the history of all those transactions becomes a lasting record of who owns what: that record is called the blockchain.
Bitcoin was one of the first and biggest cryptocurrencies and has been on a wild ride since its creation in 2009, surging in value as investors piled in, drawing comparisons with the tulipmania of the 17th century before it crashed. Sceptics warn that the lack of central control make crypto-assets ideal for criminals and terrorists.
The number of crypto-assets has grown rapidly, including from several major companies. JP Morgan has built its own cryptocurrencies, while trading in traditional financial assets that track the value of cryptocurrencies – such as derivatives and contracts for difference – has also become available. Facebook is planning to launch its own digital currency – Libra – in 2020.
Richard Partington and Martin Belam
Bitcoin is a decentralised virtual currency that can be produced or "mined" by banks of computers solving complex algorithms. The mining process can be very expensive on a large scale because it requires cutting-edge technology and vast amounts of electricity.
The value of bitcoin has surged above $11,000 (£8,760), after Facebook unveiled last month its own global cryptocurrency called Libra, due to launch next year.
Unlike a traditional currency such as the dollar, the euro or the yen, bitcoin has no central bank and is not backed by any government. Instead, the unit is controlled and regulated by its community of users, who argue that this makes it more efficient than traditional currencies.
Donald Trump: Bitcoin and cryptocurrencies aren't money
Though China's digital payments ecosystem has developed faster than most of the world and mobile payments dominate everyday transactions in urban centres, the country's central bank has adopted a cautious attitude towards cryptocurrencies.
In 2017, Beijing cracked down on cryptocurrency trading by shutting down bitcoin exchanges. It also banned initial coin offerings, a way for companies to raise funds.
According to several studies, cryptocurrency mining consumes more energy per year than many countries – with more than half of mining farms located in China.
Besides electricity theft, other bitcoin-related crimes include hacking cryptocurrency owners.
Last August, Chinese police in the northern city of Xi'an arrested three suspects who had allegedly stolen assets worth 600m yuan by hacking the computers of victims who owned bitcoin and other virtual currencies.