Audantic provides data and analytic solutions that enable our customers to make decisions in real time that drive revenue growth

audantic

The Battle of the North Atlantic

Purple.com is apparently Virgin Atlantic’s choice of domain for its In-flight Wi-Fi landing page. But what does that mean? Greetings from sky bar of Airbus A330! Shortly after I boarded my favourite airline, I couldn’t help but notice the crew member sneak in something along the lines of, during the safety announcement. I did not, at the time know if this was an official branding strategy employed by Virgin or something that the cheeky crew manager made up uffice to say, the technical gears in my head started turning rapidly. “If you can’t find the page that lets you connect to Wi-Fi, just go to purple.com and you’ll get there,” in the air. S It’s clever. After all is Virgin Atlantic’s theme colour, as abundantly evident from cabin décor and colour scheme. But as always, I’m here to help you understand the technical workings behind the scenes that make “claiming” at 35,000 feet possible. purple purple.com In , the domain is owned by mattress giant and is actively used by them. On Earth, visiting would lead you to the mattress retailer’s website. This also becomes clear right after you pay for Gogo In-flight Wi-Fi and retry visiting in your browser. That’s when you’ll get to the mattress seller’s website instead. real life purple.com Purple® purple.com purple.com But that should make you wonder, how could be owned by Virgin Atlantic, Gogo Inflight Wi-Fi and the mattress seller all at the same time? This is where come into play. purple.com local domains Local domains and DNS Local domains or hostnames, in a make it possible for network administrators to (pun) and redirect it to an intranet website of their choice, such as a . That’s the “sign-on to Wi-Fi” portal typically presented by hotspots until you accept their terms of service or if applicable, pay the charges. Whether such a domain exists on the gigantic World Wide Web WWW or not, has no relevance. That means a network admin could make anything up … , whether these domains exist in on the internet or not isn’t a prerequisite. certain context, make any domain up in the air Captive Portal localhost axsharma, ax.wifi, inflight.com, purple.com, virginwifi.go… reality — Anyone connecting to the network — your routing devices or access points, will be redirected to the location of your choice when they visit these locally setup domains. In some cases, the Wi-Fi access point, also acting as the DNS server, can the actual IP address of a domain with a different one, thereby redirecting you elsewhere. through you override Local domains indeed make it possible to host your websites accessible only to a select few members of a dedicated network but not the outside world — the internet. It’s what makes possible! corporate intranet However, in case of most Wi-Fi hotspots — in-flight or on ground, local domains may not be at play because visiting virtually website should redirect you to the in-flight W-Fi purchase portal or “sign-in page,” as long as you haven’t paid charges or accepted terms of service. always any Typical workflow implemented by Wi-Fi hotspots ( ) Image credit Security This is also why when connecting to webpages beginning with https — which is nearly all of the pages today, over a public Wi-Fi hotspot, you get a series of SSL errors up until the point you “sign-in to the hotspot” or visit a non-HTTPS website. This happens because of a certificate mismatch. The website you are trying to visit, let’s say, is “ facebook.com” but the router is persistently redirecting all HTTP/HTTPS traffic to its access point homepage, the SSL certificate of which was issued (e.g. https:// only for that homepage airborne.gogoinflight.com). https:// An example SSL/TLS certificate mismatch errors Web browsers treat this as a security issue because you are visiting but effectively being served a website whose certificate clearly dictates you are on . Browsers see this as an ominous sign of a attack where an attacker has possibly in-flight routing devices to redirect users to a malicious page instead, although in most cases this isn’t the case. facebook.com airborne.gogoinflight.com Man-in-the-Middle (MitM) hijacked It can further be confirmed that local domains are not at play here by running a simple DNS lookup. Looking up the IP addresses of DNS servers, returned the same result and both in-flight (whether prior to or post payment) as well as on Earth. purple.com’s 104.20.55.235 104.20.56.235 DNS query (nslookup) results for purple.com in-flight, pre or post payment: DNS query (nslookup) results for purple.com on Earth: The finding implies aren’t really being used and rather employed by Gogo In-flight WiFi is redirecting any and all HTTP(S) traffic to its sign-in page, up until the point a payment is made. Had this not been the case and was officially setup locally by the network admin, we’d get very different DNS results at 35,000 feet and on Earth. local domains captive portal purple.com Impromptu Branding Although fair point to note, more likely than not, the name or for that matter is merely being used as a catchy, marketing phrase that’s easy to remember for passengers. In actuality, or phrase — even your own name followed by a forward slash, should redirect you to the in-flight Wi-Fi page as you’ve likely observed. purple.com any domain any domain purple.com or any domain redirects users to the Wi-Fi captive portal until they sign-in. When asked if had anything to do with strategic branding, Virgin Atlantic’s spokesperson officially responded with: purple.com the specific website mentioned isn’t something we’re affiliated with and it isn’t part of our procedure to tell our customers to use that site, so we expect that it was a case of the crew using their initiative on the day. But for Virgin Atlantic, this is clever marketing generated by the crew member. At over 35,000 feet you may easily lose track of time left to your destination or what your choice of red wine was, but stays fresh in your memory for long. on the fly purple.com © 2019. ( ). All Rights Reserved. Akshay “Ax” Sharma Twitter

How Virgin Atlantic's WiFi Landing Page is Purple.com

Until last year I was not familiar with SXSW. Boasted as one of the largest tech conferences, and with a history spanning over 30 years, its loud performances somehow didn’t make it across the Atlantic Ocean, or if they did, the wind was not blowing in my direction. I then happened to notice one announcement that mentioned this conference focused in the intersection between technology and art and decided to tune in to the content live streamed on . Watching some videos of the talks of the 2017 event, back then, that connection seemed to be real. facebook On the other side of the ocean, in Lisbon, since 2015, we have Web Summit, also claiming to be one of the biggest tech conferences. Like in Southby there are dozens of talks with prominent figures of the tech world, addressing the hot topics of the moment such as VR, AI or Blockchain. True, some of the talks in Web Summit, usually in the last days, have musicians as hosts, but the focus is always in more “uptight” tech or at least there is not such an artsy vibe around it. However there is one thing that strikes me as particularly different, the proud connection with the arts world that its Texan contender shows. Just as London Major Sadiq Khan remarked, looking at the hipster avocado socks in an interview this year, at the event’s Facebook Studio, to the live stream host Douglas Caballero — he had never seen such a large number of hipsters. (To which the host responded by proudly by putting his feet on the table so that everyone in the remote audience could see). If someone from London is surprised at the quantity of hipsters at a tech conference, then perhaps someone from other city in Europe would be even more surprised: this marriage between art and tech is not so often proudly displayed. hipster, noun informal: a person who follows the latest trends and fashions, especially those regarded as being outside the cultural mainstream. Moving beyond socks and appearances, something more profound grants this conference — at least to the remote spectator — a different vibe. The intersection between digital and art is expressed by the panels on music, TV and film production or VR and AR enabled journalistic narratives, where the creative side takes the lead, while technology, not less proudly, assumes the supporting role. Moving also beyond the previous definition, a hipster always struck me as someone who was deeply sensitive to the arts, and that when spotted at these events, would be signaling that indeed a connection between art and tech had been well achieved. Tech as enabler for Art In music This year, Lyor Cohen— a legendary music executive that broke in artists such as Run-DMC or the Beastie Boys, went to stage to talk about his new role the Head of Music for Google / YouTube. After an overview of the ups and downs of his career in music, which turned out to be an overview of the history of hip hop as well, he concluded by explaining his acceptance of the challenge to work with the giants shaping the industry and contribute to the to the development of the industry he saw being disrupted from the first row. In journalism and visual arts VR Director Nonny de la Peña displayed how she used the technology to make people more aware of topics such as police violence or incarceration, and while most of it seemed to be along the lines of “bleed and lead” — a term I learned later that week when attending the Women in VR meetup at Altspace, it is clear how VR can be such an entry point for other journalists and artists to begin start using on their creations. technology Sasha Samochina, Immersive Reality Producer at NASA, confessed she was amused every time someone asked, in surprise, what an artist was doing there and talked about projects such as Accessmars.com in which the public can interact with images collected by the Curiosity Rover, and how she developed a fun first-person personality for the organization’s twitter account. There is the case, also, in which technology is liberated from its supporting role and becomes itself the focus of discussion. Tech as the focus of art In hit TV series There was a talk with the crew of Westworld — a dystopia about a technological advanced Wild West where robots exist to please the desires of visitors — whose first season was one of the most watched HBO original series. It seems that speculative implications about the dark side of technology, captured by series such as this and Black Mirror, is making its way into individual tv screens, prompting people to think about philosophical issues, such as the nature of reality or ethics, quite different from the light-heartedness of other tv series that used to be big hits. Tech as lever of societal unrest And the emergence of continued activism In a panel with Melinda Gates, the CEO of TaskRabbit, the COO of Hearst Magazines and a co-founder of the “Time’s Up” Movement, talked about the issues regarding women in tech (and overall), implying that that the movement is “here to stay” and perhaps even that no longer “laissez-faire” is acceptable to deal with the fast-paced change our society is undergoing. Ta-Nehisi Coates, correspondent of the Atlantic and author of the Black Panther series for Marvel Comics, in a keynote, repeatedly stressed the difference between a journalist and activist (and the claim that he belonged to the former category). According to him, while the latter had the purpose of making people act, the first didn’t. But anyone watching the movie knows the power of narrative that runs counter the “white-hero stereotype” seen in most of the movies can have in bringing people to conceive alternative futures for a society. One in which different people can be seen at the edge of technological advancement. We are now used to the title of “something / activist” being displayed to introduce someone about to give a speech in a tech conference, and that was not the case some years ago. And the need for effective personal development tools One of the other appearances that magnetized the audience was the one of New York times bestselling autho and psychotherapist Esther Perel. While on stage, she avidly answered questions from the millennial audience, addressing topics such loneliness (which she claims to be one of the major health problems in the US), the impacts of social media and the overall the need to bring the quality of relationships to the top of the agenda. Just by looking at the top charts of books sold, where more than one title of self-help type is likely to be present, it is clear that these topics are of concern to swats of people that are finding this advice crucial to deal with the amount of change our society is undergoing. And while all of this had some connection with technology there was space for talks about things that were almost purely analogue, like for example watching Run-DMC talk about his new series of comics books on the live TuneIn channel at SXSW. This seems quite unlikely to happen at other conferences , but somehow gives it a more human touch, as people are still living in analogue and digital worlds, and have not made the full transition in one fell swoop as these major conferences tend to make us think — at least in Lisbon it seems that once in an year, everyone in society is involved working in tech projects, while the reality, once you leave the conference rooms, is not like that. Having said that I am looking forward to seeing more avocato socks rocking their laptops, but more profound than that, a proudly displayed marriage between art and tech, because that is what is happening in any case.

Remote review of SXSW’18: looking at tech wearing hipster socks from the other side of the Atlantic

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University;
(2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics;
(3) Nicole Arulanantham, Space Telescope Science Institute;
(4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences;
(5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences;
(6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. Table of Links Abstract and Intro
X-ray Observations and Data Extraction
Flare Analyses
Comparison with X-ray Flares from Young Stars
Discussion
Conclusions
Acknowledgments and References 2. X-RAY OBSERVATIONS AND DATA EXTRACTION 2.1. NuSTAR Data We conducted a single observation (ObsID 30801011002; PI K. Getman) of this system with NuSTAR (Harrison et al. 2013) from 04:51:09 UTC on July 28, 2022, to 19:36:09 UTC on July 31, 2022. This time window covers the orbital phase range of Φ = (0.9 − 1.13) around the periastron passage on July 30, 2022 (Φ = 1.0). The science exposure of the observation, taking into account Earth occultations, is 156 ksec. The data obtained from focal plane modules A and B (FPMA and FPMB), covering similar energy ranges, were processed using tools from the NuSTAR Data Analysis Software package NuSTARDAS (v. 2.1.2), which is incorporated into HEASOFT (v. 6.31.1) as detailed in (Nasa High Energy Astrophysics Science Archive Research Center (Heasarc) 2014). NuSTAR’s calibration database (CALDB) v. 20221229 was utilized. The data went through calibration and screening using the nupipeline tool. Parameters saamode=OPTIMIZED and tentacle=yes were employed to screen the data for elevated count rates resulting from the spacecraft’s passages through the South Atlantic Anomaly. Subsequently, the nuproducts tool was utilized to generate various outputs, including the source and background lightcurves and spectra, as well as response and response matrix files. Figures 1(a,b) present images of the combined FPMA and FPMB event lists for the (3 − 10) keV and (10 − 50) keV energy bands, respectively. The source counts were obtained from a circular region with a radius of 40′′ (indicated by the green circle in Figure 1), representing 60% of the energy within the point spread function. The background measurement was performed locally in an area devoid of sources. Within the source extraction circle, there are 771 X-ray events with energies ranging from 3 to 10 keV, approximately one third of which are background events. The source is not detected in the (10 − 20) keV band (not shown) or the (10 − 50) keV band (Figure 1b), nor at higher energies. 2.2. Swift Data Using the Neil Gehrels Swift observatory (Gehrels et al. 2004), we conducted 16 short observations of DQ Tau near periastron over a time period of July 28 to August 2, 2022. These observations are part of our joint NuSTAR/Swift program. The observations were spaced several hours apart, with durations ranging from 1 to 1.7 ksec, totaling 22.5 ksec. The target ID for these observations is 14857. The X-ray Telescope (XRT) operated in the PC mode, while the Ultraviolet/Optical Telescope (UVOT) operated in the 0x30ed standard sixfilter blue-weighted mode. The Swift-XRT data product generator (Evans et al. 2007, 2009) was utilized to construct X-ray light curves and source/background spectra, along with the relevant calibration files. The generator employed HEASOFT package (v. 6.29) and CALDB (v. 20230109). Figure 1c presents the XRT image obtained from merging the event lists of all 16 observations. Within the circular source extraction region of a 30′′ radius (indicated by the green circle in the image), we identified 249 X-ray counts with energies ranging from 0.2 to 10 keV, of which only a few percent represented background counts. For each of the 16 observations, UVOT magnitudes for the six filters (V:B:U:W1:M2:W2) were measured by applying the fappend (Blackburn et al. 1999) and uvotmaghist tools from HEASOFT (v. 6.31.1). 2.3. Chandra Data To investigate the soft X-ray emission throughout the entire orbital phase of DQ Tau and complement the observations made by NuSTAR and Swift at periastron, additional X-ray data were obtained utilizing the Chandra X-ray Observatory (Weisskopf et al. 2002). The investigation involved 12 short Chandra imaging observations of DQ Tau away from periastron, with each observation lasting approximately 1.5 ksec. These observations were part of the Director’s Discretionary Time (DDT) program, with corresponding observation IDs ranging from 26464 to 26475. Data were obtained between August 1 and August 14, 2022, covering an orbital phase range of 1.1 to 1.9. To mitigate potential pileup effects during anticipated Xray flares, a 1/8 sub-array of a single ACIS-I3 chip was employed (Garmire et al. 2003). For the Chandra data reduction and analysis, CIAO v4.15(Fruscione et al. 2006) and CALDB v4.10.4 were utilized. The CIAO tools chandra repro and reproject obs were used to reprocess the data and merge the event images. Figure 1d displays the cutout of the merged Chandra-ACIS-I3 image of DQ Tau. Count rates and apparent fluxes were measured, and spectra and response files were generated using the srcflux tool. Within the circular source extraction region, with a radius of 2′′ (indicated by the green circle in the image), and within the energy band of (0.5 − 8) keV, net X-ray events were observed between 30 and 50 per observation in 8 instances. However, the remaining 4 consecutive observations (ObsIDs 26471, 26472, 26473, and 26474) exhibited higher net count levels, ranging from 61 to 781 counts per observation. This paper is available on arxiv under CC 4.0 license. Authors: (1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University; (2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics; (3) Nicole Arulanantham, Space Telescope Science Institute; (4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University; (2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics; (3) Nicole Arulanantham, Space Telescope Science Institute; (4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. Table of Links Abstract and Intro X-ray Observations and Data Extraction Flare Analyses Comparison with X-ray Flares from Young Stars Discussion Conclusions Acknowledgments and References Abstract and Intro Abstract and Intro X-ray Observations and Data Extraction X-ray Observations and Data Extraction Flare Analyses Flare Analyses Comparison with X-ray Flares from Young Stars Comparison with X-ray Flares from Young Stars Discussion Discussion Conclusions Conclusions Acknowledgments and References Acknowledgments and References 2. X-RAY OBSERVATIONS AND DATA EXTRACTION 2.1. NuSTAR Data We conducted a single observation (ObsID 30801011002; PI K. Getman) of this system with NuSTAR (Harrison et al. 2013) from 04:51:09 UTC on July 28, 2022, to 19:36:09 UTC on July 31, 2022. This time window covers the orbital phase range of Φ = (0.9 − 1.13) around the periastron passage on July 30, 2022 (Φ = 1.0). The science exposure of the observation, taking into account Earth occultations, is 156 ksec. The data obtained from focal plane modules A and B (FPMA and FPMB), covering similar energy ranges, were processed using tools from the NuSTAR Data Analysis Software package NuSTARDAS (v. 2.1.2), which is incorporated into HEASOFT (v. 6.31.1) as detailed in (Nasa High Energy Astrophysics Science Archive Research Center (Heasarc) 2014). NuSTAR’s calibration database (CALDB) v. 20221229 was utilized. The data went through calibration and screening using the nupipeline tool. Parameters saamode=OPTIMIZED and tentacle=yes were employed to screen the data for elevated count rates resulting from the spacecraft’s passages through the South Atlantic Anomaly. Subsequently, the nuproducts tool was utilized to generate various outputs, including the source and background lightcurves and spectra, as well as response and response matrix files. Figures 1(a,b) present images of the combined FPMA and FPMB event lists for the (3 − 10) keV and (10 − 50) keV energy bands, respectively. The source counts were obtained from a circular region with a radius of 40′′ (indicated by the green circle in Figure 1), representing 60% of the energy within the point spread function. The background measurement was performed locally in an area devoid of sources. Within the source extraction circle, there are 771 X-ray events with energies ranging from 3 to 10 keV, approximately one third of which are background events. The source is not detected in the (10 − 20) keV band (not shown) or the (10 − 50) keV band (Figure 1b), nor at higher energies. 2.2. Swift Data Using the Neil Gehrels Swift observatory (Gehrels et al. 2004), we conducted 16 short observations of DQ Tau near periastron over a time period of July 28 to August 2, 2022. These observations are part of our joint NuSTAR/Swift program. The observations were spaced several hours apart, with durations ranging from 1 to 1.7 ksec, totaling 22.5 ksec. The target ID for these observations is 14857. The X-ray Telescope (XRT) operated in the PC mode, while the Ultraviolet/Optical Telescope (UVOT) operated in the 0x30ed standard sixfilter blue-weighted mode. The Swift-XRT data product generator (Evans et al. 2007, 2009) was utilized to construct X-ray light curves and source/background spectra, along with the relevant calibration files. The generator employed HEASOFT package (v. 6.29) and CALDB (v. 20230109). Figure 1c presents the XRT image obtained from merging the event lists of all 16 observations. Within the circular source extraction region of a 30′′ radius (indicated by the green circle in the image), we identified 249 X-ray counts with energies ranging from 0.2 to 10 keV, of which only a few percent represented background counts. For each of the 16 observations, UVOT magnitudes for the six filters (V:B:U:W1:M2:W2) were measured by applying the fappend (Blackburn et al. 1999) and uvotmaghist tools from HEASOFT (v. 6.31.1). 2.3. Chandra Data To investigate the soft X-ray emission throughout the entire orbital phase of DQ Tau and complement the observations made by NuSTAR and Swift at periastron, additional X-ray data were obtained utilizing the Chandra X-ray Observatory (Weisskopf et al. 2002). The investigation involved 12 short Chandra imaging observations of DQ Tau away from periastron, with each observation lasting approximately 1.5 ksec. These observations were part of the Director’s Discretionary Time (DDT) program, with corresponding observation IDs ranging from 26464 to 26475. Data were obtained between August 1 and August 14, 2022, covering an orbital phase range of 1.1 to 1.9. To mitigate potential pileup effects during anticipated Xray flares, a 1/8 sub-array of a single ACIS-I3 chip was employed (Garmire et al. 2003). For the Chandra data reduction and analysis, CIAO v4.15(Fruscione et al. 2006) and CALDB v4.10.4 were utilized. The CIAO tools chandra repro and reproject obs were used to reprocess the data and merge the event images. Figure 1d displays the cutout of the merged Chandra-ACIS-I3 image of DQ Tau. Count rates and apparent fluxes were measured, and spectra and response files were generated using the srcflux tool. Within the circular source extraction region, with a radius of 2′′ (indicated by the green circle in the image), and within the energy band of (0.5 − 8) keV, net X-ray events were observed between 30 and 50 per observation in 8 instances. However, the remaining 4 consecutive observations (ObsIDs 26471, 26472, 26473, and 26474) exhibited higher net count levels, ranging from 61 to 781 counts per observation.

Colliding Magnetospheres: X-ray Observations and Data Extraction

Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 2 of 11. A. TikTok Is a Speech Platform Used by 170 Million Americans. 12. TikTok is an online video entertainment platform designed to provide a creative and entertaining forum for users to express themselves and make connections with others over the Internet. More than 170 million Americans use TikTok every month, to learn about and share information on a range of topics — from entertainment, to religion, to politics. Content creators use the TikTok platform to express their opinions, discuss their political views, support their preferred political candidates, and speak out on today’s many pressing issues, all to a global audience of more than 1 billion users. Many creators also use the platform to post product reviews, business reviews, and travel information and reviews. 13. In the United States, the TikTok platform is provided by TikTok Inc., a California-incorporated company that has its principal place of business in Culver City, California and offices in New York, San Jose, Chicago, and Miami, among other locations. TikTok Inc. has thousands of employees in the United States. Like many platforms owned by companies that operate globally, the global TikTok platform is supported not only by those employees, but also by employees of other ByteDance subsidiaries around the globe, including in Singapore, the United Kingdom, Brazil, Germany, South Africa, Australia, and China. Many of the global TikTok platform’s functions are spread across different corporate entities and countries, and the global TikTok business is led by a leadership team based in Singapore and the United States. Like other U.S. companies, TikTok Inc. is governed by U.S. law. 14. TikTok Inc.’s ultimate parent company is ByteDance Ltd., a Cayman Islands-incorporated equity holding company. ByteDance was founded in 2012 by Chinese entrepreneurs. Over time, the company sought funding to fuel growth, as is common in the technology sector, which resulted in the issuance of additional equity and the dilution of existing shares. Today, approximately 58 percent of ByteDance Ltd. is owned by global institutional investors (such as BlackRock, General Atlantic, and Susquehanna International Group), 21 percent is owned by the company’s founder (a Chinese national who lives in Singapore), and 21 percent is owned by employees — including approximately 7,000 Americans. 15. ByteDance launched TikTok in May 2017 in over 150 countries, including the United States.[3] Since its launch, TikTok has become one of the world’s most popular applications, with over 1 billion users worldwide. As of January 2024, more than 170 million Americans use TikTok on a monthly basis. 16. Users primarily view content on TikTok through its “For You” page, which presents a collection of videos curated by TikTok’s proprietary recommendation engine. The recommendation engine customizes each user’s content feed based on how the user interacts with the content that the user watches. TikTok’s popularity is based in large part on the effectiveness of the recommendation engine. The source code for TikTok’s recommendation engine was originally developed by ByteDance engineers based in China, and the engine is customized for operations in TikTok’s various global markets, including in the United States. TikTok is not offered in mainland China. 17. Aside from TikTok, ByteDance has developed and operates more than a dozen other online platforms and software applications for use in U.S. and international markets, including for content-sharing, video and music editing, e-commerce, gaming, and enterprise productivity. Continue Reading Here. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings.
This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. [3] TikTok was later relaunched in August 2018 following a transaction involving the company Musical.ly. See generally Petition for Review, TikTok Inc. v. CFIUS, No. 20-1444 (D.C. Cir. Nov. 10, 2020). Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series. You can jump to any part in this filing here. This part is 2 of 11. Tiktok Inc., and ByteDance LTD., v. Merrick B. Garland Update Court Filing, retrieved on May 7, 2024, is part of HackerNoon’s Legal PDF Series . You can jump to any part in this filing here . This part is 2 of 11. HackerNoon’s Legal PDF Series here A. TikTok Is a Speech Platform Used by 170 Million Americans. 12. TikTok is an online video entertainment platform designed to provide a creative and entertaining forum for users to express themselves and make connections with others over the Internet. More than 170 million Americans use TikTok every month, to learn about and share information on a range of topics — from entertainment, to religion, to politics. Content creators use the TikTok platform to express their opinions, discuss their political views, support their preferred political candidates, and speak out on today’s many pressing issues, all to a global audience of more than 1 billion users. Many creators also use the platform to post product reviews, business reviews, and travel information and reviews. 13. In the United States, the TikTok platform is provided by TikTok Inc., a California-incorporated company that has its principal place of business in Culver City, California and offices in New York, San Jose, Chicago, and Miami, among other locations. TikTok Inc. has thousands of employees in the United States. Like many platforms owned by companies that operate globally, the global TikTok platform is supported not only by those employees, but also by employees of other ByteDance subsidiaries around the globe, including in Singapore, the United Kingdom, Brazil, Germany, South Africa, Australia, and China. Many of the global TikTok platform’s functions are spread across different corporate entities and countries, and the global TikTok business is led by a leadership team based in Singapore and the United States. Like other U.S. companies, TikTok Inc. is governed by U.S. law. 14. TikTok Inc.’s ultimate parent company is ByteDance Ltd., a Cayman Islands-incorporated equity holding company. ByteDance was founded in 2012 by Chinese entrepreneurs. Over time, the company sought funding to fuel growth, as is common in the technology sector, which resulted in the issuance of additional equity and the dilution of existing shares. Today, approximately 58 percent of ByteDance Ltd. is owned by global institutional investors (such as BlackRock, General Atlantic, and Susquehanna International Group), 21 percent is owned by the company’s founder (a Chinese national who lives in Singapore), and 21 percent is owned by employees — including approximately 7,000 Americans. 15. ByteDance launched TikTok in May 2017 in over 150 countries, including the United States.[3] Since its launch, TikTok has become one of the world’s most popular applications, with over 1 billion users worldwide. As of January 2024, more than 170 million Americans use TikTok on a monthly basis. 16. Users primarily view content on TikTok through its “For You” page, which presents a collection of videos curated by TikTok’s proprietary recommendation engine. The recommendation engine customizes each user’s content feed based on how the user interacts with the content that the user watches. TikTok’s popularity is based in large part on the effectiveness of the recommendation engine. The source code for TikTok’s recommendation engine was originally developed by ByteDance engineers based in China, and the engine is customized for operations in TikTok’s various global markets, including in the United States. TikTok is not offered in mainland China. 17. Aside from TikTok, ByteDance has developed and operates more than a dozen other online platforms and software applications for use in U.S. and international markets, including for content-sharing, video and music editing, e-commerce, gaming, and enterprise productivity. Continue Reading Here. Continue Reading Here . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on May 7, 2024, from sf16-va.tiktokcdn.com is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. sf16-va.tiktokcdn.com [3] TikTok was later relaunched in August 2018 following a transaction involving the company Musical.ly. See generally Petition for Review, TikTok Inc. v. CFIUS, No. 20-1444 (D.C. Cir. Nov. 10, 2020).

Understanding TikTok's Global Influence

This paper is available on arxiv under CC BY-SA 4.0 DEED license.
Authors:
(1) Lana L. Blaschke, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany and lana.blaschke@pik-potsdam.de;
(2) Da Nian, Potsdam Institute for Climate Impact Research, Potsdam, Germany;
(3) Sebastian Bathiany,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany;
(4)  Maya Ben-Yami,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany;
(5) Taylor Smith, Institute of Geosciences, University of Potsdam, 14476 Potsdam, Germany;
(6)  Chris A. Boulton, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK ;
(7) Niklas Boers, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK, and Department of Mathematics, University of Exeter, EX4 4QF Exeter, UK. Table of Links Abstract and Introduction
Materials and Methods
Data
Results
Conclusions, Open Research Section and Conflict of Interest/Competing Interests
Author Contributions, Supplementary Information, Acknowledgments and References
Additional Insight from the Conceptual Model 
AMSR2 until 2022 Excluded Due to Missing Human Land Use Data
Investigation of Resilience Loss in AMSR2’s X-Band
Results Proving Robustness
Potential Driving Forces and Sources of Bias ADDITIONAL INSIGHT FROM THE CONCEPTUAL MODEL Text S1. Stability in the conceptual model The interaction of vegetation and precipitation is plotted in Figure S1. In the conceputal model, vegetation is a function of absolute incoming precipitation only and is not dependent on the cell’s location. Hence, it is the same for each cell and plotted as the single black solid line. Precipitation on the other hand is a function of the vegetation of the cell, but also of the vegetation of the cell’s eastern neighbors. Hence, it differs for all cells, which are encoded by the colors as in Figure 2. For the calculation of one cell’s precipitation as a function of vegetation, its eastern neighbors are considered to be in equilibrium. Furthermore, precipitation depends on the amount of moisture coming in from the Atlantic ocean, or in other words on the control parameter B. The solid lines represent the state in the beginning of the experiment with B = 1010, and the dashed lines in the end with B = 990. Where the black and coloured lines cross at some (V∗, P∗), the corresponding value of vegetation supports the value of precipitation P∗, but also is V∗ supported by P∗. Hence, this point is considered a fixed point, or equilibrium. As the moisture inflow is reduced in the simulations from 1010 (solid lines) to 990 (dashed lines), the fixed points with high vegetation values vanish, explaining the tipping in the Figures S4 and S5 . Text S2. Precipitation decrease in the conceptual model The results of simulations with decreasing moisture inflow from the Atlantic ocean (decreasing B(t)) were presented in the main text in Figure 4. Figure S2 zooms in into cell-wise total precipitation and highlights its stochasticity as well as the almost linear decrease up to the Tipping Point of vegetation. Text S3. Deforestation scenario leads to Tipping in the conceptual model The results of simulations with decreasing moisture inflow from the Atlantic ocean (decreasingB(t)) were presented in the main text in Figure 4. Figure S3 is identical but presents the results from simulations with unchanging inflow from the Atlantic, i.e. B(t) = 1000 for all t. Instead, the amount vegetation in the east-most cell is considered the bifurcation parameter and constantly decreased from 1 to 0, thereby mimicking deforestation. Text S4. Distribution of the trends for the three resilience indicators In the conceptual model, all indicators show clear trends when approaching the Tipping Point of vegetation, as illustrated in Figure S4. There, clearly all three indicators show a strong shift towards positive values with only very few negative ones for AC1. In a spatially extended system like the ARF, one would thus expect all three indicators to increase when the corresponding grid cell loses resilience. Text S5. Distribution of the trends for the three resilience indicators In Figure 4 the time of emergence (ToE) was defined as the first time when a trend becomes significant. Yet, as more conservative approach one can define the ToE as the time when a trend becomes permanently significant, i.e. when all trends later in time are significant as well. The results with this definition are displayed in Figure S5. The uncertainty in the timing of this type of ToE differs much less for AC1 compared to the definition in the main text. This indicates that AC1 might be more prone to false alarms. This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Lana L. Blaschke, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany and lana.blaschke@pik-potsdam.de; (2) Da Nian, Potsdam Institute for Climate Impact Research, Potsdam, Germany; (3) Sebastian Bathiany,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany; (4)  Maya Ben-Yami,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany; (5) Taylor Smith, Institute of Geosciences, University of Potsdam, 14476 Potsdam, Germany; (6)  Chris A. Boulton, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK ; (7) Niklas Boers, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK, and Department of Mathematics, University of Exeter, EX4 4QF Exeter, UK. This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: Authors: (1) Lana L. Blaschke, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany and lana.blaschke@pik-potsdam.de; (2) Da Nian, Potsdam Institute for Climate Impact Research, Potsdam, Germany; (3) Sebastian Bathiany,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany; (4)  Maya Ben-Yami,  Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, and Potsdam Institute for Climate Impact Research, Potsdam, Germany; (5) Taylor Smith, Institute of Geosciences, University of Potsdam, 14476 Potsdam, Germany; (6)  Chris A. Boulton, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK ; (7) Niklas Boers, Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany, Potsdam Institute for Climate Impact Research, Potsdam, Germany, Global Systems Institute, University of Exeter, EX4 4QE Exeter, UK, and Department of Mathematics, University of Exeter, EX4 4QF Exeter, UK. Table of Links Abstract and Introduction Materials and Methods Data Results Conclusions, Open Research Section and Conflict of Interest/Competing Interests Author Contributions, Supplementary Information, Acknowledgments and References Additional Insight from the Conceptual Model AMSR2 until 2022 Excluded Due to Missing Human Land Use Data Investigation of Resilience Loss in AMSR2’s X-Band Results Proving Robustness Potential Driving Forces and Sources of Bias Abstract and Introduction Abstract and Introduction Materials and Methods Materials and Methods Data Data Results Results Conclusions, Open Research Section and Conflict of Interest/Competing Interests Conclusions, Open Research Section and Conflict of Interest/Competing Interests Author Contributions, Supplementary Information, Acknowledgments and References Author Contributions, Supplementary Information, Acknowledgments and References Additional Insight from the Conceptual Model Additional Insight from the Conceptual Model AMSR2 until 2022 Excluded Due to Missing Human Land Use Data AMSR2 until 2022 Excluded Due to Missing Human Land Use Data Investigation of Resilience Loss in AMSR2’s X-Band Investigation of Resilience Loss in AMSR2’s X-Band Results Proving Robustness Results Proving Robustness Potential Driving Forces and Sources of Bias Potential Driving Forces and Sources of Bias ADDITIONAL INSIGHT FROM THE CONCEPTUAL MODEL Text S1. Stability in the conceptual model The interaction of vegetation and precipitation is plotted in Figure S1. In the conceputal model, vegetation is a function of absolute incoming precipitation only and is not dependent on the cell’s location. Hence, it is the same for each cell and plotted as the single black solid line. Precipitation on the other hand is a function of the vegetation of the cell, but also of the vegetation of the cell’s eastern neighbors. Hence, it differs for all cells, which are encoded by the colors as in Figure 2. For the calculation of one cell’s precipitation as a function of vegetation, its eastern neighbors are considered to be in equilibrium. Furthermore, precipitation depends on the amount of moisture coming in from the Atlantic ocean, or in other words on the control parameter B. The solid lines represent the state in the beginning of the experiment with B = 1010, and the dashed lines in the end with B = 990. Where the black and coloured lines cross at some (V∗, P∗), the corresponding value of vegetation supports the value of precipitation P∗, but also is V∗ supported by P∗. Hence, this point is considered a fixed point, or equilibrium. As the moisture inflow is reduced in the simulations from 1010 (solid lines) to 990 (dashed lines), the fixed points with high vegetation values vanish, explaining the tipping in the Figures S4 and S5 . Text S2. Precipitation decrease in the conceptual model The results of simulations with decreasing moisture inflow from the Atlantic ocean (decreasing B(t)) were presented in the main text in Figure 4. Figure S2 zooms in into cell-wise total precipitation and highlights its stochasticity as well as the almost linear decrease up to the Tipping Point of vegetation. Text S3. Deforestation scenario leads to Tipping in the conceptual model The results of simulations with decreasing moisture inflow from the Atlantic ocean (decreasingB(t)) were presented in the main text in Figure 4. Figure S3 is identical but presents the results from simulations with unchanging inflow from the Atlantic, i.e. B(t) = 1000 for all t. Instead, the amount vegetation in the east-most cell is considered the bifurcation parameter and constantly decreased from 1 to 0, thereby mimicking deforestation. Text S4. Distribution of the trends for the three resilience indicators In the conceptual model, all indicators show clear trends when approaching the Tipping Point of vegetation, as illustrated in Figure S4. There, clearly all three indicators show a strong shift towards positive values with only very few negative ones for AC1. In a spatially extended system like the ARF, one would thus expect all three indicators to increase when the corresponding grid cell loses resilience. Text S5. Distribution of the trends for the three resilience indicators In Figure 4 the time of emergence (ToE) was defined as the first time when a trend becomes significant. Yet, as more conservative approach one can define the ToE as the time when a trend becomes permanently significant, i.e. when all trends later in time are significant as well. The results with this definition are displayed in Figure S5. The uncertainty in the timing of this type of ToE differs much less for AC1 compared to the definition in the main text. This indicates that AC1 might be more prone to false alarms.

AUDANTIC

audantic.com

-- employees

Since n.d.

COMPANY RANKING

AUDANTIC

EVERGREEN INDEX #1034

Representing this company? Click here to claim and customize this page!

audantic WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

AUDANTIC

audantic.com

-- employees

Since n.d.

COMPANY RANKING

AUDANTIC

EVERGREEN INDEX #1034

RELATED COMPANIESRANK

STORIES ABOUT AUDANTIC

Representing this company? Click here to claim and customize this page!

audantic WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!