Chaad

chaad

After the successful touchdown of ’s lander in the south of the Moon, all eyes are on India’s space program. Already, ISRO and the Japan Aerospace Exploration Agency (JAXA) launch LUPEX, a successor to Chandrayaan-3, in 2026. Chandrayaan-3 have decided to jointly In the limelight is also startup ecosystem, which has secured its position as a formidable contender on the global stage. According to recent insights by on August 11, 2023, India ranks seventh in terms of funding within the international SpaceTech landscape for the year. India’s SpaceTech Tracxn The Indian SpaceTech sector’s journey has been one of transformation, driven by the sector’s privatization in 2020. Previously dominated by governmental players, the sector has witnessed a significant surge in private sector participation post-privatization. Private entities are now actively involved in crucial aspects of research, manufacturing, and fabrication of rockets and satellites, fostering a vibrant ecosystem of innovation. The funding trajectory of the Indian SpaceTech ecosystem tells a compelling story of growth and resilience. From a modest $35 million in funds raised between 2010 and 2019, the sector experienced a meteoric rise in 2020, securing a remarkable $28 million in funding. This trend continued with exponential growth, reaching $96 million in 2021 and an impressive $112 million in 2022, marking a 17% increase from the previous year. This steady expansion in funding sets the Indian SpaceTech sector apart from other industries affected by funding challenges and macroeconomic fluctuations. Building on its upward trajectory, the Indian SpaceTech sector has already attracted $62 million in funding for the year 2023, reflecting a substantial 60% increase compared to the same period last year. This exceptional growth trend is expected to continue in the upcoming months. India’s emergence as a potent player in SpaceTech is further highlighted by its impressive satellite deployment. With 381 satellites placed in low orbit, India has positioned itself as a key player in this arena. Notably, the successful launch of 36 satellites into orbit by ISRO for UK-based OneWeb illustrates India’s contribution to global satellite ownership. The funding trajectory of the Indian SpaceTech ecosystem tells a compelling story of growth and resilience The Indian private sector has taken the lead in for practical applications, including satellite-based communication services like phone signals, broadband, OTT, and 5G. The government’s Budget 2023 initiatives further support the private enterprises’ role in this sector, from launching satellites and rockets to operating Earth stations with a 0% GST regime. Plans for a Production Linked Incentive (PLI) scheme for satellite manufacturing are also in the pipeline. launching satellites India’s space agency, ISRO, boasts a series of remarkable milestones, including the successful landing of Chandrayaan-3 on the moon’s south pole, paving the way for groundbreaking studies in the region. Also, India achieved a major achievement by becoming the first country to successfully land a spacecraft near the moon’s south pole. Additionally, ISRO’s feat of deploying a record-breaking 104 satellites in sun-synchronous orbits during a single mission in 2017 stands as a testament to India’s prowess. Among the thriving business models within the Indian SpaceTech sector, Small Payload-based Launch Vehicles have garnered significant attention, securing $75.6 million in funding over the last two years. Key players such as Skyroot, AgniKul, and Pixxel are spearheading innovative endeavors that promise to reshape the industry landscape. Skyroot, for instance, has launched India’s first privately built rocket, Vikram-S, into space, with plans to revolutionize satellite launches. Satellite-based Imaging Solutions have also witnessed substantial support, with $84.2 million in funding secured over the past two years. Companies like Pixxel have introduced pioneering technologies for earth observation, while Dhruva Space and Bellatrix Aerospace are contributing to the sector through their unique offerings. The global space industry is undergoing a phase of rapid innovation, spanning 3D-printed rocket components, commercial space tourism, reusable launch vehicles, asteroid mining, and novel propulsion technologies. In this ever-evolving landscape, India stands poised to capitalize on emerging opportunities, underlined by its proven capabilities in manufacturing and satellite/launch vehicle development. The accomplishments of the Indian Space industry, bolstered by government support, are expected to fuel entrepreneurship and investments, ushering in a new era of innovation and growth in the years ahead. This article was originally published by on Navanwita Bora Sachdev The Tech Panda.

India's SpaceTech Startup Ecosystem Spotlighted After Chandrayaan-3 Triumph

চন্দ্রযান-৩ জয়ের পর ভারতের স্পেসটেক স্টার্টআপ ইকোসিস্টেম স্পটলাইট হয়েছে

Indiens SpaceTech-Startup-Ökosystem rückt nach Chandrayaan-3-Triumph ins Rampenlicht

El ecosistema de startups de SpaceTech de la India se destaca después del triunfo de Chandrayaan-3

L'écosystème indien des startups SpaceTech mis en lumière après le triomphe de Chandrayaan-3

चंद्रयान-3 की जीत के बाद भारत का स्पेसटेक स्टार्टअप इकोसिस्टम सुर्खियों में आया

チャンドラヤーン3号の成功を受けて注目されるインドの宇宙技術スタートアップエコシステム

찬드라얀 3호 성공 이후 인도의 SpaceTech 스타트업 생태계가 주목받다

Ecossistema de startups SpaceTech da Índia destacado após o triunfo do Chandrayaan-3

Индийская экосистема стартапов SpaceTech оказалась в центре внимания после триумфа Chandrayaan-3

Hindistan'ın SpaceTech Startup Ekosistemi Chandrayaan-3 Zaferinden Sonra Dikkate Alındı

Hệ sinh thái khởi nghiệp công nghệ vũ trụ của Ấn Độ nổi bật sau chiến thắng Chandrayaan-3

“月船 3 号”胜利后，印度航天科技初创企业生态系统成为众人瞩目的焦点

Hey Hackers! I am Nik Golos, an indie startup founder, and product manager. I want to share a project I've been working on over the past few months. What is MeMemes? MeMemes is a that uses AI to transform people into over 30 famous meme images. To create personalised memes, you simply need to send 10 selfies to the app, and within 1 hour, you will receive meme images featuring yourself. mobile app Here are some examples of the resulting images: How I came to the idea? I was inspired by the Remix option in Midjourney. Towards the end of 2022, I came across an showcasing how people used this feature to combine two pictures, resulting in some crazy outcomes by mixing humans with animals and generating new memes. article Later, just for some fun, I decided to prank my friend using the Midjourney Remix feature with his images. However, I wasn't satisfied with the results. So, I built my own pipeline using Stable Diffusion + DreamBooth and created a few memes by blending his face with GigaChad's. My friend had a good laugh when he saw these meme images. This experience sparked the idea to develop an app that would make the process easier to repeat. Next steps Currently, I'm seeking beta users to test the technology on different people. I'd love to hear your ideas and feedback on how to improve the app. I hope you all enjoy it and have some fun!

I Created a Mobile App That Turns People Into Giga Chads and Memes With AI

ChadGPT: How to Turn OpenAI’s Chatbot into a Republican and What We Can Learn From This

ChadGPT: কিভাবে OpenAI এর চ্যাটবটকে রিপাবলিকানে পরিণত করা যায় এবং এর থেকে আমরা কী শিখতে পারি

ChadGPT: Wie man den Chatbot von OpenAI in einen Republikaner verwandelt und was wir daraus lernen können

ChadGPT: Cómo convertir el chatbot de OpenAI en republicano y qué podemos aprender de esto

ChadGPT : comment transformer le chatbot d'OpenAI en républicain et ce que nous pouvons en tirer

ChadGPT: OpenAI के चैटबॉट को रिपब्लिकन में कैसे बदलें और हम इससे क्या सीख सकते हैं

ChadGPT: OpenAI のチャットボットを共和党員に変える方法と、これから学べること

ChadGPT: OpenAI의 챗봇을 공화당으로 바꾸는 방법과 여기서 배울 수 있는 것

ChadGPT: como transformar o chatbot da OpenAI em um republicano e o que podemos aprender com isso

ChadGPT: OpenAI'nin Chatbot'unu Cumhuriyetçiye Nasıl Dönüştürürüz ve Bundan Ne Öğrenebiliriz?

ChadGPT: Cách biến Chatbot của OpenAI thành Cộng hòa và chúng ta có thể học được gì từ điều này

ChadGPT：如何将 OpenAI 的聊天机器人变成共和党人以及我们可以从中学到什么

Episode 9 of : An interview with Noel Chandler, the CEO of Crypto Disrupted Clinicoin.io and I interview Noel Chandler, the CEO of Clinicoin. In the interview we discuss everything from health and wellness, meditation, blockchain technology, to cryptocurrency. Greg Kerr Also . available on iTunes For more episodes of , or . Crypto Disrupted subscribe on YouTube subscribe and listen on iTunes

Health and Wellness on the Blockchain with Noel Chandler of Clinicoin

Multilingual Coarse Political Stance Classification of Media: Acknowledgments and References

মিডিয়ার বহুভাষিক মোটা রাজনৈতিক অবস্থানের শ্রেণীবিভাগ: স্বীকৃতি এবং উল্লেখ

Mehrsprachige grobe politische Haltung Klassifizierung von Medien: Danksagungen und Referenzen

Clasificación multilingüe de posturas políticas generales de los medios: reconocimientos y referencias

Classification multilingue grossière des positions politiques des médias : remerciements et références

बहुभाषी असभ्य राजनीतिक रुख मीडिया का वर्गीकरण: आभार और संदर्भ

多言語メディアの粗い政治的立場の分類: 謝辞と参考文献

미디어의 다국어 거친 정치적 입장 분류: 감사의 글 및 참고 자료

Classificação Multilíngue da Posição Política Grosseira da Mídia: Agradecimentos e Referências

Многоязычная грубая политическая классификация СМИ: благодарности и ссылки

Medyanın Çok Dilli Kaba Siyasi Duruş Sınıflandırması: Teşekkür ve Referanslar

Phân loại quan điểm chính trị thô sơ đa ngôn ngữ của phương tiện truyền thông: Lời cảm ơn và tài liệu tham khảo

多语言媒体粗略政治立场分类：致谢与参考文献

This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.
Authors:
(1) Brisha Jain, Independent researcher India and brishajain02@gmail.com;
(2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. Table of Links Abstract and Intro
Related Work
Data Collection
Analysis Methodology
Results
Limitations
Concluding Discussion
References REFERENCES [1] Toril Aalberg and Anders Todal Jenssen. 2017. Gender Stereotyping of Political Candidates. Nordicom Review 28, 1 (2017), 17–32. https://doi.org/10.1515/nor-2017-0198 [2] Pushkal Agarwal, Nishanth Sastry, and Edward Wood. 2019. Tweeting MPs: Digital Engagement between Citizens and Members of Parliament in the UK. Proceedings of the International AAAI Conference on Web and Social Media 13, 01. [3] Arshia Arya, Soham De, Dibyendu Mishra, Gazal Shekhawat, Ankur Sharma, Anmol Panda, Faisal M Lalani, Parantak Singh, Ramaravind Kommiya Mothilal, Rynaa Grover, Sachita Nishal, Saloni Dash, Shehla Rashid Shora, Syeda Zainab Akbar, and Joyojeet Pal. 2022. DISMISS: Database of Indian Social Media Influencers on Twitter. [4] Nichole M. Bauer. 2015. Emotional, Sensitive, and Unfit for Office? Gender Stereotype Activation and Support Female Candidates. Political Psychology 36, 6 (2015), 691–708. [5] Aditi Bhowmick, Paul Novosad, Sam Asher, Elliott Ash, Bilal Siddiqi, Christoph Goessmann, Daniel Chen, and Tanaya Devi. 2021. In-Group Bias in the Indian Judiciary: Evidence from 5.5 Million Criminal Cases. In Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS ’21). 47. https://doi.org/10.1145/3460112.3471943 [6] Jose Camacho-Collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa-Anke, Fangyu Liu, Eugenio Martínez-Cámara, et al. 2022. TweetNLP: Cutting-Edge Natural Language Processing for Social Media. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. [7] Tessa M. Ditonto, Allison J. Hamilton, and David P. Redlawsk. 2014. Gender Stereotypes, Information Search, and Voting Behavior in Political Campaigns. Political Behavior 36, 2 (2014), 335–358. https://doi.org/10.1007/s11109-013-9232-6 [8] Kathleen Dolan and Timothy Lynch. 2014. It Takes a Survey: Understanding Gender Stereotypes, Abstract Attitudes, and Voting for Women Candidates. American Politics Research 42, 4 (2014), 656–576. https://doi.org/10.1177/1532673X13503034 [9] Heather Evans. 2016. Do Women Only Talk about ‘Female Issues’? Gender and
Issue Discussion on Twitter. Online Information Review 40, 5 (2016), 660–672.
https://doi.org/10.1108/OIR-10-2015-0338 [10] Heather K. Evans and Jennifer Hayes Clark. 2016. You Tweet Like a Girl!’: How Female Candidates Campaign on Twitter. American Politics Research 44, 2 (2016), 326–352. https://doi.org/10.1177/1532673X15597747 [11] Peter A. Gloor, Joao Marcos, Patrick M. de Boer, Hauke Fuehres, Wei Lo, and Keiichi Nemoto. 2015. Cultural Anthropology through the Lens of Wikipedia: Historical Leader Networks, Gender Bias, and News-based Sentiment. arXiv:1508.00055 [cs.CY] https://doi.org/10.48550/ARXIV.1508.00055 [12] Leonie Huddy and Nayda Terkildsen. 1993. Gender Stereotypes and the Perception of Male and Female Candidates. American Journal of Political Science 37, 1 (1993), 119. https://doi.org/10.2307/2111526 [13] Berrin Beasley John H. Parmelee, Nataliya Roman and Stephynie C. Perkins. 2019. Gender and Generational Differences in Political Reporters’ Interactivity on Twitter. Journalism Studies 20, 2 (2019), 232–247. https://doi.org/10.1080/1461670X.2017.1364140 [14] Ashiqur R. KhudaBukhsh Kunal Khadilkar and Tom M. Mitchell. 2022. Gender Bias, Social Bias, and Representation in Bollywood and Hollywood. Patterns 3, 4 (2022), 100486. https://doi.org/10.1016/j.patter.2022.100486 [15] MingYu (Ethen) Liu. 2023. Topic Modeling. https://ethen8181.github.io/machine-learning/clustering/topic_model/LDA.html. [16] J. Nathan Matias, Sarah Szalavitz, and Ethan Zuckerman. 2017. FollowBias: Supporting Behavior Change toward Gender Equality by Networked Gatekeepers on Social Media (CSCW ’17). 1082–1095. https://doi.org/10.1145/2998181.2998287 [17] Lindsey Meeks. 2016. Gendered Styles, Gendered Differences: Candidates’ Use of Personalization and Interactivity on Twitter. Journal of Information Technology & Politics 13, 4 (2016), 295–310. https://doi.org/10.1080/19331681.2016.1160268 [18] Armin Mertens, Franziska Pradel, Ayjeren Rozyjumayeva, and Jens Wäckerle. 2019. As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’19). 193–201. [19] Sebo P. 2021. Using genderize.io to infer the gender of first names: how to improve the accuracy of the inference. J Med Libr Assoc. (2021). [20] Anmol Panda, A’ndre Gonawela, Sreangsu Acharyya, Dibyendu Mishra, Mugdha Mohapatra, Ramgopal Chandrasekaran, and Joyojeet Pal. 2020. NivaDuck - A Scalable Pipeline to Build a Database of Political Twitter Handles for India and the United States. In International Conference on Social Media and Society. 200–209. [21] John H. Parmelee. 2013. Political Journalists and Twitter: Influences on Norms and Practices. Journal of Media Practice 14, 4 (2013), 291–305. https://doi.org/10.1386/jmpr.14.4.291_1 [22] Pallavi Prasad. 2020. One in Every Seven Tweets About Indian Women Politicians Is Abusive: Study. https://www.theswaddle.com/women-politicians-india-twitter-trolls. [23] Gazal Shekhawat, Parantak Singh, Rynaa Grover, Saloni Dash, Himani Negi, Ankur Sharma, Somya Sagarika, and Joyojeet Pal. 2021. Twitter Use by Politicians Across States in India. [24] Carole Spary. 2007. Female Political Leadership in India. Commonwealth & Comparative Politics 45, 3 (2007), 253–277. https://doi.org/10.1080/14662040701516821 [25] Genderize team. 2023. Genderize. https://genderize.io/. [26] Jesse Holcomb Usher, Nikki and Justin Littman. 2018. Twitter Makes It Worse: Political Journalists, Gendered Echo Chambers, and the Amplification of Gender Bias. The International Journal of Press/Politics 23, 3 (2018), 324–344. https://doi.org/10.1177/1940161218781254 [27] Jason Gainous Wagner, Kevin M. and Mirya R. Holman. 2017. I Am Woman, Hear Me Tweet! Gender Differences in Twitter Use among Congressional Candidates. Journal of Women, Politics & Policy 38, 4 (2017), 430–455. https://doi.org/10.1080/1554477X.2016.1268871 This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Brisha Jain, Independent researcher India and brishajain02@gmail.com; (2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: Authors: (1) Brisha Jain, Independent researcher India and brishajain02@gmail.com; (2) Mainack Mondal, IIT Kharagpur India and mainack@cse.iitkgp.ac.in. Table of Links Abstract and Intro Related Work Data Collection Analysis Methodology Results Limitations Concluding Discussion References Abstract and Intro Abstract and Intro Related Work Related Work Data Collection Data Collection Analysis Methodology Analysis Methodology Results Results Limitations Limitations Concluding Discussion Concluding Discussion References References REFERENCES [1] Toril Aalberg and Anders Todal Jenssen. 2017. Gender Stereotyping of Political Candidates. Nordicom Review 28, 1 (2017), 17–32. https://doi.org/10.1515/nor-2017-0198 [2] Pushkal Agarwal, Nishanth Sastry, and Edward Wood. 2019. Tweeting MPs: Digital Engagement between Citizens and Members of Parliament in the UK. Proceedings of the International AAAI Conference on Web and Social Media 13, 01. [3] Arshia Arya, Soham De, Dibyendu Mishra, Gazal Shekhawat, Ankur Sharma, Anmol Panda, Faisal M Lalani, Parantak Singh, Ramaravind Kommiya Mothilal, Rynaa Grover, Sachita Nishal, Saloni Dash, Shehla Rashid Shora, Syeda Zainab Akbar, and Joyojeet Pal. 2022. DISMISS: Database of Indian Social Media Influencers on Twitter. [4] Nichole M. Bauer. 2015. Emotional, Sensitive, and Unfit for Office? Gender Stereotype Activation and Support Female Candidates. Political Psychology 36, 6 (2015), 691–708. [5] Aditi Bhowmick, Paul Novosad, Sam Asher, Elliott Ash, Bilal Siddiqi, Christoph Goessmann, Daniel Chen, and Tanaya Devi. 2021. In-Group Bias in the Indian Judiciary: Evidence from 5.5 Million Criminal Cases. In Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS ’21). 47. https://doi.org/10.1145/3460112.3471943 https://doi.org/10.1145/3460112.3471943 [6] Jose Camacho-Collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa-Anke, Fangyu Liu, Eugenio Martínez-Cámara, et al. 2022. TweetNLP: Cutting-Edge Natural Language Processing for Social Media. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. [7] Tessa M. Ditonto, Allison J. Hamilton, and David P. Redlawsk. 2014. Gender Stereotypes, Information Search, and Voting Behavior in Political Campaigns. Political Behavior 36, 2 (2014), 335–358. https://doi.org/10.1007/s11109-013-9232-6 https://doi.org/10.1007/s11109-013-9232-6 [8] Kathleen Dolan and Timothy Lynch. 2014. It Takes a Survey: Understanding Gender Stereotypes, Abstract Attitudes, and Voting for Women Candidates. American Politics Research 42, 4 (2014), 656–576. https://doi.org/10.1177/1532673X13503034 https://doi.org/10.1177/1532673X13503034 [9] Heather Evans. 2016. Do Women Only Talk about ‘Female Issues’? Gender and
Issue Discussion on Twitter. Online Information Review 40, 5 (2016), 660–672. https://doi.org/10.1108/OIR-10-2015-0338 https://doi.org/10.1108/OIR-10-2015-0338 [10] Heather K. Evans and Jennifer Hayes Clark. 2016. You Tweet Like a Girl!’: How Female Candidates Campaign on Twitter. American Politics Research 44, 2 (2016), 326–352. https://doi.org/10.1177/1532673X15597747 https://doi.org/10.1177/1532673X15597747 [11] Peter A. Gloor, Joao Marcos, Patrick M. de Boer, Hauke Fuehres, Wei Lo, and Keiichi Nemoto. 2015. Cultural Anthropology through the Lens of Wikipedia: Historical Leader Networks, Gender Bias, and News-based Sentiment. arXiv:1508.00055 [ cs.CY ] https://doi.org/10.48550/ARXIV.1508.00055 cs.CY https://doi.org/10.48550/ARXIV.1508.00055 [12] Leonie Huddy and Nayda Terkildsen. 1993. Gender Stereotypes and the Perception of Male and Female Candidates. American Journal of Political Science 37, 1 (1993), 119. https://doi.org/10.2307/2111526 https://doi.org/10.2307/2111526 [13] Berrin Beasley John H. Parmelee, Nataliya Roman and Stephynie C. Perkins. 2019. Gender and Generational Differences in Political Reporters’ Interactivity on Twitter. Journalism Studies 20, 2 (2019), 232–247. https://doi.org/10.1080/1461670X.2017.1364140 https://doi.org/10.1080/1461670X.2017.1364140 [14] Ashiqur R. KhudaBukhsh Kunal Khadilkar and Tom M. Mitchell. 2022. Gender Bias, Social Bias, and Representation in Bollywood and Hollywood. Patterns 3, 4 (2022), 100486. https://doi.org/10.1016/j.patter.2022.100486 https://doi.org/10.1016/j.patter.2022.100486 [15] MingYu (Ethen) Liu. 2023. Topic Modeling. https://ethen8181.github.io/machine-learning/clustering/topic_model/LDA.html . https://ethen8181.github.io/machine-learning/clustering/topic_model/LDA.html [16] J. Nathan Matias, Sarah Szalavitz, and Ethan Zuckerman. 2017. FollowBias: Supporting Behavior Change toward Gender Equality by Networked Gatekeepers on Social Media (CSCW ’17). 1082–1095. https://doi.org/10.1145/2998181.2998287 https://doi.org/10.1145/2998181.2998287 [17] Lindsey Meeks. 2016. Gendered Styles, Gendered Differences: Candidates’ Use of Personalization and Interactivity on Twitter. Journal of Information Technology & Politics 13, 4 (2016), 295–310. https://doi.org/10.1080/19331681.2016.1160268 https://doi.org/10.1080/19331681.2016.1160268 [18] Armin Mertens, Franziska Pradel, Ayjeren Rozyjumayeva, and Jens Wäckerle. 2019. As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians. In Proceedings of the 10th ACM Conference on Web Science (WebSci ’19). 193–201. [19] Sebo P. 2021. Using genderize.io to infer the gender of first names: how to improve the accuracy of the inference. J Med Libr Assoc. (2021). genderize.io [20] Anmol Panda, A’ndre Gonawela, Sreangsu Acharyya, Dibyendu Mishra, Mugdha Mohapatra, Ramgopal Chandrasekaran, and Joyojeet Pal. 2020. NivaDuck - A Scalable Pipeline to Build a Database of Political Twitter Handles for India and the United States. In International Conference on Social Media and Society. 200–209. [21] John H. Parmelee. 2013. Political Journalists and Twitter: Influences on Norms and Practices. Journal of Media Practice 14, 4 (2013), 291–305. https://doi.org/10.1386/jmpr.14.4.291_1 https://doi.org/10.1386/jmpr.14.4.291_1 [22] Pallavi Prasad. 2020. One in Every Seven Tweets About Indian Women Politicians Is Abusive: Study. https://www.theswaddle.com/women-politicians-india-twitter-trolls . https://www.theswaddle.com/women-politicians-india-twitter-trolls [23] Gazal Shekhawat, Parantak Singh, Rynaa Grover, Saloni Dash, Himani Negi, Ankur Sharma, Somya Sagarika, and Joyojeet Pal. 2021. Twitter Use by Politicians Across States in India. [24] Carole Spary. 2007. Female Political Leadership in India. Commonwealth & Comparative Politics 45, 3 (2007), 253–277. https://doi.org/10.1080/14662040701516821 https://doi.org/10.1080/14662040701516821 [25] Genderize team. 2023. Genderize. https://genderize.io/ . https://genderize.io/ [26] Jesse Holcomb Usher, Nikki and Justin Littman. 2018. Twitter Makes It Worse: Political Journalists, Gendered Echo Chambers, and the Amplification of Gender Bias. The International Journal of Press/Politics 23, 3 (2018), 324–344. https://doi.org/10.1177/1940161218781254 https://doi.org/10.1177/1940161218781254 [27] Jason Gainous Wagner, Kevin M. and Mirya R. Holman. 2017. I Am Woman, Hear Me Tweet! Gender Differences in Twitter Use among Congressional Candidates. Journal of Women, Politics & Policy 38, 4 (2017), 430–455. https://doi.org/10.1080/1554477X.2016.1268871 https://doi.org/10.1080/1554477X.2016.1268871

Uncovering Gender Bias within Journalist-Politician Interaction in Indian Twitter: References

ভারতীয় টুইটারে সাংবাদিক-রাজনীতিবিদ ইন্টারঅ্যাকশনের মধ্যে জেন্ডার বায়াস উন্মোচন: রেফারেন্স

Aufdeckung geschlechtsspezifischer Voreingenommenheit in der Interaktion zwischen Journalisten und Politikern im indischen Twitter: Referenzen

Descubriendo el sesgo de género en la interacción entre periodistas y políticos en Twitter indio: referencias

Découvrir les préjugés sexistes dans les interactions journalistes-hommes politiques sur Twitter indien : références

भारतीय ट्विटर पर पत्रकार-राजनेता बातचीत में लैंगिक पूर्वाग्रह को उजागर करना: संदर्भ

インドのツイッターにおけるジャーナリストと政治家の交流におけるジェンダーバイアスの解明：参考文献

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揭示印度推特上记者与政客互动中的性别偏见：参考文献

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References ABSTRACT Keywords: white dwarfs — stars: winds, outflows — stars: rotation 1. INTRODUCTION Consequences of a merger of massive white dwarfs (WDs) are of great astrophysical importance. It may explode as a Type Ia supernova in particular when the binary constitutes of carbon-oxygen WDs with a total mass exceeding the Chandrasekhar limit (Webbink 1984; Iben & Tutukov 1984). Instead, if a super-Chandrasekhar oxygen-neon core is synthesized after the merger, it may collapse into a neutron star (NS) (Nomoto & Iben 1985; Saio & Nomoto 2004). Such a merger induced collapse has gotten attention as a scenario for the formation of peculiar type of neutron stars, e.g., sources of fast radio bursts (e.g., Kashiyama & Murase 2017; Kremer et al. 2021; Kirsten et al. 2022; Lu et al. 2022). On the other hand, the expansion velocity of the wind observed in WD J005311 significantly surpasses the escape velocity of a WD with a typical mass. This suggests that the wind is either thermally driven, originating from a superor near-Chandrasekhar mass WD, or magnetically driven due to the rapid rotation and strong magnetic field of the WD. In the former case, the wind velocity will be (Parker 1965): while in the latter case, the maximum wind velocity along the equatorial plane is (Weber & Davis 1967; Michel 1969): The wind is so fast that it catches up and clashes into the surrounding supernova ejecta, forming a wind termination shock, which is observed as an inner X-ray nebula (Oskinova et al. 2020; Ko et al. 2023). The X-ray nebula is still in its infancy; given the observed angular size, it is only a few tens of years old (Ko et al. 2023). Subsequent observations may reveal the time variability and anisotropy of the wind, which is generally expected for a rotating magnetic wind but has not been explored in this context. These properties of the wind can also be linked to the mass-loss and spindown rates of the central WD, which are important in determining the fate of the central WD: whether it eventually collapses into a neutron star, and if so, how rapidly rotating and strongly magnetized the neutron star would be. Here we model a system like WD J005311 by numerically constructing a 2D axisymmetric wind solution driven by rotating dipole, with implementing a wind launching region that mimics the near-surface carbon burning region. We investigate the wind structure together with its time evolution (i.e., how the mass, energy and angular momentum loss rate from the system evolves with time), and the scaling of the spin-down torque with respect to system parameters such as surface magnetic field, rotation frequency and mass loss rate. This paper is organized as follows. We introduce our setup in Sec. 2, including numerical details. In Sec. 3, we show our results on wind structure, time evolution and scaling of spin-down torque. Finally, we discuss several implications and applications on observational results in Sec. 4. This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References ABSTRACT Keywords : white dwarfs — stars: winds, outflows — stars: rotation Keywords 1. INTRODUCTION Consequences of a merger of massive white dwarfs (WDs) are of great astrophysical importance. It may explode as a Type Ia supernova in particular when the binary constitutes of carbon-oxygen WDs with a total mass exceeding the Chandrasekhar limit (Webbink 1984; Iben & Tutukov 1984). Instead, if a super-Chandrasekhar oxygen-neon core is synthesized after the merger, it may collapse into a neutron star (NS) (Nomoto & Iben 1985; Saio & Nomoto 2004). Such a merger induced collapse has gotten attention as a scenario for the formation of peculiar type of neutron stars, e.g., sources of fast radio bursts (e.g., Kashiyama & Murase 2017; Kremer et al. 2021; Kirsten et al. 2022; Lu et al. 2022). On the other hand, the expansion velocity of the wind observed in WD J005311 significantly surpasses the escape velocity of a WD with a typical mass. This suggests that the wind is either thermally driven, originating from a superor near-Chandrasekhar mass WD, or magnetically driven due to the rapid rotation and strong magnetic field of the WD. In the former case, the wind velocity will be (Parker 1965): while in the latter case, the maximum wind velocity along the equatorial plane is (Weber & Davis 1967; Michel 1969): The wind is so fast that it catches up and clashes into the surrounding supernova ejecta, forming a wind termination shock, which is observed as an inner X-ray nebula (Oskinova et al. 2020; Ko et al. 2023). The X-ray nebula is still in its infancy; given the observed angular size, it is only a few tens of years old (Ko et al. 2023). Subsequent observations may reveal the time variability and anisotropy of the wind, which is generally expected for a rotating magnetic wind but has not been explored in this context. These properties of the wind can also be linked to the mass-loss and spindown rates of the central WD, which are important in determining the fate of the central WD: whether it eventually collapses into a neutron star, and if so, how rapidly rotating and strongly magnetized the neutron star would be. Here we model a system like WD J005311 by numerically constructing a 2D axisymmetric wind solution driven by rotating dipole, with implementing a wind launching region that mimics the near-surface carbon burning region. We investigate the wind structure together with its time evolution (i.e., how the mass, energy and angular momentum loss rate from the system evolves with time), and the scaling of the spin-down torque with respect to system parameters such as surface magnetic field, rotation frequency and mass loss rate. This paper is organized as follows. We introduce our setup in Sec. 2, including numerical details. In Sec. 3, we show our results on wind structure, time evolution and scaling of spin-down torque. Finally, we discuss several implications and applications on observational results in Sec. 4.

Magnetic Wind From a Massive White Dwarf Merger: Abstract and Intro

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Discussion

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Flare Analyses

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 6. CONCLUSIONS Drawing upon recent observations conducted during a single orbit of DQ Tau in July-August 2022, which utilized NuSTAR, Swift, and Chandra telescopes (§ 2), alongside previously gathered X-ray and mm-band data from multiple periastrons of DQ Tau (Salter et al. 2010; Getman et al. 2011, 2022b), our study embarks on an extensive analysis to compute the energetic characteristics of X-ray/NUV/optical flares within DQ Tau (§ 3). Serendipitously, we discovered X-ray super-flares outside of periastron, potentially related to interacting magnetospheres (§ 5.1.2). The absence of evidence for long-term variability in the baseline X-ray emission of ∼ 1 Myr old DQ Tau is consistent with the understanding that younger stars typically exhibit larger active regions and more extensive X-ray coronal structures. This may contribute to the reduction of observable magnetic dynamo cycling (§ 5.3). 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 6. CONCLUSIONS Drawing upon recent observations conducted during a single orbit of DQ Tau in July-August 2022, which utilized NuSTAR, Swift, and Chandra telescopes (§ 2), alongside previously gathered X-ray and mm-band data from multiple periastrons of DQ Tau (Salter et al. 2010; Getman et al. 2011, 2022b), our study embarks on an extensive analysis to compute the energetic characteristics of X-ray/NUV/optical flares within DQ Tau (§ 3). Serendipitously, we discovered X-ray super-flares outside of periastron, potentially related to interacting magnetospheres (§ 5.1.2). The absence of evidence for long-term variability in the baseline X-ray emission of ∼ 1 Myr old DQ Tau is consistent with the understanding that younger stars typically exhibit larger active regions and more extensive X-ray coronal structures. This may contribute to the reduction of observable magnetic dynamo cycling (§ 5.3).

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Conclusions

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau:Acknowledgments and References

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

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 ABSTRACT DQ Tau is a unique young high-eccentricity binary system that exhibits regular magnetic reconnection flares and pulsed accretion near periastron. We conducted NuSTAR, Swift, and Chandra observations during the July 30, 2022 periastron to characterize X-ray, near-ultraviolet (NUV), and optical flaring emissions. Our findings confirm the presence of X-ray super-flares accompanied by substantial NUV and optical flares, consistent with previous discoveries of periastron flares in 2010 and 2021. These observations, supported by new evidence, strongly establish the magnetosphere collision mechanism as the primary driver of magnetic energy release during DQ Tau’s periastron flares. The energetics of the observed X-ray super-flares remain consistent across the three periastrons, indicating recurring energy sources during each passage, surpassing the capabilities of single stars. The observed flaring across multiple bands supports the Adams et al. model for magnetosphere interaction in eccentric binaries. Evidence from modeling and past and current observations suggests that both the mm/X-ray periastron flares and tentatively, the magnetic reconnection-related components of the optical/NUV emissions, conform to the classical solar/stellar non-thermal thick-target model, except for the distinctive magnetic energy source. However, our NuSTAR observations suffered from high background levels, hindering the detection of anticipated non-thermal hard X-rays. Furthermore, we report serendipitous discovery of X-ray super-flares occurring away from periastron, potentially associated with interacting magnetospheres. The current study is part of a broader multi-wavelength campaign, which is planned to investigate the influence of DQ Tau’s stellar radiation on gas-phase ion chemistry within its circumbinary disk. Keywords: Pre-main sequence stars (1290) — Spectroscopic binary stars (1557) — X-ray stars (1823) — Stellar magnetic fields (1610) — Optical flares (1166) — Ultraviolet transient sources (1854) —- Stellar x-ray flares (1637) — Solar x-ray flares (1816) — Solar flares (1496) — Stellar flares (1603) — Protoplanetary disks (1300) 1. INTRODUCTION DQ Tau is a nearby (D = 195 pc; Gaia Collaboration et al. 2023), non-eclipsing, double-lined spectro scopic binary system, consisting of two pre-main sequence (PMS) stars of equal mass (0.6 M⊙) and equal radius (2 R⊙) (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). These stars exhibit spectral types within the range of M0 to K7. The rotational periods of the primary and secondary components are 3 days (K´osp´al et al. 2018) and 4.5 days (Pouilly et al. in prep.), respectively. The orbital period measures 15.8 days. DQ Tau boasts a highly eccentric orbit (e ∼ 0.6) and displays an exceptionally small periastron separation, measuring only about 8 −10 stellar radii (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). Furthermore, the binary components of DQ Tau harbor relatively strong surface magnetic fields, estimated at around 2.5 kG, which give rise to formidable magnetospheres (Pouilly et al. 2023, Pouilly et al. in prep.). Surrounding DQ Tau is a protoplanetary disk of average size (≤ 100 au), complete with a small 0.3 au cavity (Czekala et al. 2016; K´osp´al et al. 2018; Ballering & Eisner 2019). Large optical and UV brightenings primarily occur at orbital phase (Φ = 0.8 − 1.2), and they are mainly attributed to the pulsed accretion of disk material onto the binary components (Tofflemire et al. 2017; K´osp´al et al. 2018; Muzerolle et al. 2019; Fiorellino et al. 2022). However, far-UV (FUV) observations of DQ Tau with the Cosmic Origins Spectrograph onboard HST (HST-COS) showed no correlation between the orbital phase of the binary and the C IV flux, a tracer of mass accretion rate, indicating that some component of the behavior is stochastic (Ardila et al. 2015). The system exhibits powerful mm/X-ray flares coinciding with periastron passage, attributed to collisions between the magnetospheres of the binary components. The evidence supporting the magnetsophere collision hypothesis includes the recurrence of synchrotron mmband flaring during 4 periastron encounters (Salter et al. 2008, 2010), the recurrence of soft X-ray flaring in 2 periastron encounters (Getman et al. 2011, 2022a), the timing and energy relationships between the mm and X-ray flares, and the consistency observed between the flare loop size and binary separation (Salter et al. 2010; Getman et al. 2011). Several other young binary systems with high eccentricities have been reported to exhibit enhanced levels of either X-ray, optical/mm, or radio emissions near their periastron passages. Notable examples include ϵ Lupi (Das et al. 2023), a collective study of four binaries (Parenago 523, RX J1622.7-2325 Nw, UZ Tau E, and HD 152404) conducted by Getman et al. (2016), UZ Tau E (K´osp´al et al. 2011), and V773 Tau A (Massi et al. 2008; Adams et al. 2011). In these systems, magnetosphere collision has been proposed as a primary mechanism responsible for generating the magnetic reconnection energy that drives these events. Modelling studies have shown that PMS X-rays have strong impact on disk ionization and chemistry (Glassgold et al. 2000; Alexander et al. 2014). But most studies assume continuous irradiation without considering the high-amplitude variations in flux and spectrum due to super-flares. A few time-dependent calculations show that disk ionization may respond to sudden large Xray flares (Rab et al. 2017; Waggoner & Cleeves 2022). This may already have been seen. One empirical report of ionization variability has emerged: the H13CO+ abundance of IM Lup’s disk jumped up and down by a factor of 2.5 over months (Cleeves et al. 2017). However, since no concurrent X-ray observations were conducted, the exact cause cannot be definitively ascribed to X-ray flaring. The occurrence of large X-ray flares in young stars is relatively rare and unpredictable, displaying a stochastic nature (Getman & Feigelson 2021). However, the presence of predictable X-ray super-flares and accretion outbursts in close proximity to periastron passage makes DQ Tau an extraordinary laboratory for investigating the influence of stellar radiation on the gas-phase ion chemistry within its disk. To achieve this, we conducted a single X-ray observation using the NuSTAR telescope, along with multiple short-duration observations using the Swift telescope in the X-ray, UV, and optical wavelengths. These observations were strategically timed near a specific periastron passage of DQ Tau, taking place in July-August 2022. Additionally, we captured multiple snapshots of the non-periastron portion of DQ Tau’s orbit using the Chandra X-ray telescope. However, we encountered unfavorable weather conditions that limited our ALMA observations to a single short session near periastron. The results from this ALMA observation will be presented in a forthcoming paper. Meanwhile, building upon the X-ray/UV/optical data acquired in 2022 and the previously obtained X-ray/mm data (Salter et al. 2010; Getman et al. 2011, 2022a), our current study is dedicated to further investigating the origins and energetic properties of X-ray flares, along with their corresponding near-ultraviolet (NUV) and optical flare counterparts, observed within the remarkable young binary system DQ Tau. The structure of the paper is outlined as follows: Section 2 provides a detailed description of the data reduction and reduction procedures employed for X-ray, UV, and optical analyses. In Section 3, we present the detection of flares and examine their spectral properties. Section 4 offers a comparison between the X-ray periastron flares observed in DQ Tau and super-flares observed in numerous other PMS stars. Finally, Section 5 delves into a discussion surrounding the origin and energetics of the X-ray flares, as well as their associated NUV and optical counterparts. 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 ABSTRACT DQ Tau is a unique young high-eccentricity binary system that exhibits regular magnetic reconnection flares and pulsed accretion near periastron. We conducted NuSTAR, Swift, and Chandra observations during the July 30, 2022 periastron to characterize X-ray, near-ultraviolet (NUV), and optical flaring emissions. Our findings confirm the presence of X-ray super-flares accompanied by substantial NUV and optical flares, consistent with previous discoveries of periastron flares in 2010 and 2021. These observations, supported by new evidence, strongly establish the magnetosphere collision mechanism as the primary driver of magnetic energy release during DQ Tau’s periastron flares. The energetics of the observed X-ray super-flares remain consistent across the three periastrons, indicating recurring energy sources during each passage, surpassing the capabilities of single stars. The observed flaring across multiple bands supports the Adams et al. model for magnetosphere interaction in eccentric binaries. Evidence from modeling and past and current observations suggests that both the mm/X-ray periastron flares and tentatively, the magnetic reconnection-related components of the optical/NUV emissions, conform to the classical solar/stellar non-thermal thick-target model, except for the distinctive magnetic energy source. However, our N u STAR observations suffered from high background levels, hindering the detection of anticipated non-thermal hard X-rays. Furthermore, we report serendipitous discovery of X-ray super-flares occurring away from periastron, potentially associated with interacting magnetospheres. The current study is part of a broader multi-wavelength campaign, which is planned to investigate the influence of DQ Tau’s stellar radiation on gas-phase ion chemistry within its circumbinary disk. u Keywords : Pre-main sequence stars (1290) — Spectroscopic binary stars (1557) — X-ray stars (1823) — Stellar magnetic fields (1610) — Optical flares (1166) — Ultraviolet transient sources (1854) —- Stellar x-ray flares (1637) — Solar x-ray flares (1816) — Solar flares (1496) — Stellar flares (1603) — Protoplanetary disks (1300) Keywords 1. INTRODUCTION DQ Tau is a nearby (D = 195 pc; Gaia Collaboration et al. 2023), non-eclipsing, double-lined spectro scopic binary system, consisting of two pre-main sequence (PMS) stars of equal mass (0.6 M⊙) and equal radius (2 R⊙) (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). These stars exhibit spectral types within the range of M0 to K7. The rotational periods of the primary and secondary components are 3 days (K´osp´al et al. 2018) and 4.5 days (Pouilly et al. in prep.), respectively. The orbital period measures 15.8 days. DQ Tau boasts a highly eccentric orbit (e ∼ 0.6) and displays an exceptionally small periastron separation, measuring only about 8 −10 stellar radii (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). Furthermore, the binary components of DQ Tau harbor relatively strong surface magnetic fields, estimated at around 2.5 kG, which give rise to formidable magnetospheres (Pouilly et al. 2023, Pouilly et al. in prep.). Surrounding DQ Tau is a protoplanetary disk of average size (≤ 100 au), complete with a small 0.3 au cavity (Czekala et al. 2016; K´osp´al et al. 2018; Ballering & Eisner 2019). Large optical and UV brightenings primarily occur at orbital phase (Φ = 0.8 − 1.2), and they are mainly attributed to the pulsed accretion of disk material onto the binary components (Tofflemire et al. 2017; K´osp´al et al. 2018; Muzerolle et al. 2019; Fiorellino et al. 2022). However, far-UV (FUV) observations of DQ Tau with the Cosmic Origins Spectrograph onboard HST (HST-COS) showed no correlation between the orbital phase of the binary and the C IV flux, a tracer of mass accretion rate, indicating that some component of the behavior is stochastic (Ardila et al. 2015). The system exhibits powerful mm/X-ray flares coinciding with periastron passage, attributed to collisions between the magnetospheres of the binary components. The evidence supporting the magnetsophere collision hypothesis includes the recurrence of synchrotron mmband flaring during 4 periastron encounters (Salter et al. 2008, 2010), the recurrence of soft X-ray flaring in 2 periastron encounters (Getman et al. 2011, 2022a), the timing and energy relationships between the mm and X-ray flares, and the consistency observed between the flare loop size and binary separation (Salter et al. 2010; Getman et al. 2011). Several other young binary systems with high eccentricities have been reported to exhibit enhanced levels of either X-ray, optical/mm, or radio emissions near their periastron passages. Notable examples include ϵ Lupi (Das et al. 2023), a collective study of four binaries (Parenago 523, RX J1622.7-2325 Nw, UZ Tau E, and HD 152404) conducted by Getman et al. (2016), UZ Tau E (K´osp´al et al. 2011), and V773 Tau A (Massi et al. 2008; Adams et al. 2011). In these systems, magnetosphere collision has been proposed as a primary mechanism responsible for generating the magnetic reconnection energy that drives these events. Modelling studies have shown that PMS X-rays have strong impact on disk ionization and chemistry (Glassgold et al. 2000; Alexander et al. 2014). But most studies assume continuous irradiation without considering the high-amplitude variations in flux and spectrum due to super-flares. A few time-dependent calculations show that disk ionization may respond to sudden large Xray flares (Rab et al. 2017; Waggoner & Cleeves 2022). This may already have been seen. One empirical report of ionization variability has emerged: the H13CO+ abundance of IM Lup’s disk jumped up and down by a factor of 2.5 over months (Cleeves et al. 2017). However, since no concurrent X-ray observations were conducted, the exact cause cannot be definitively ascribed to X-ray flaring. The occurrence of large X-ray flares in young stars is relatively rare and unpredictable, displaying a stochastic nature (Getman & Feigelson 2021). However, the presence of predictable X-ray super-flares and accretion outbursts in close proximity to periastron passage makes DQ Tau an extraordinary laboratory for investigating the influence of stellar radiation on the gas-phase ion chemistry within its disk. To achieve this, we conducted a single X-ray observation using the N u STAR telescope, along with multiple short-duration observations using the Swift telescope in the X-ray, UV, and optical wavelengths. These observations were strategically timed near a specific periastron passage of DQ Tau, taking place in July-August 2022. Additionally, we captured multiple snapshots of the non-periastron portion of DQ Tau’s orbit using the Chandra X-ray telescope. However, we encountered unfavorable weather conditions that limited our ALMA observations to a single short session near periastron. The results from this ALMA observation will be presented in a forthcoming paper. u Meanwhile, building upon the X-ray/UV/optical data acquired in 2022 and the previously obtained X-ray/mm data (Salter et al. 2010; Getman et al. 2011, 2022a), our current study is dedicated to further investigating the origins and energetic properties of X-ray flares, along with their corresponding near-ultraviolet (NUV) and optical flare counterparts, observed within the remarkable young binary system DQ Tau. The structure of the paper is outlined as follows: Section 2 provides a detailed description of the data reduction and reduction procedures employed for X-ray, UV, and optical analyses. In Section 3, we present the detection of flares and examine their spectral properties. Section 4 offers a comparison between the X-ray periastron flares observed in DQ Tau and super-flares observed in numerous other PMS stars. Finally, Section 5 delves into a discussion surrounding the origin and energetics of the X-ray flares, as well as their associated NUV and optical counterparts.

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Abstract and Intro

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Authors:
(1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de);
(2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de);
(3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de);
(4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Table of Links Abstract and 1 Introduction 2 Background 3 Design and Implementation of Licma and 3.1 Design 3.2 Implementation 4 Methodology and 4.1 Searching and Downloading Python Apps 4.2 Comparison with Previous Studies 5 Evaluation and 5.1 GitHub Python Projects 5.2 MicroPython 6 Comparison with previous studies 7 Threats to Validity 8 Related Work 9 Conclusion, Acknowledgments, and References 9 CONCLUSION In this paper, we presented the first empirical study of crypto misuses in Python. To conduct the study, we implemented the first multi-language analysis tool for crypto misuses with rules to detect common misuses of five different Python libraries as well as the standard Java library. We analyzed 895 popular Python apps from GitHub and 51 MicroPython projects to identify misuses. Our analysis revealed that 52.26 % of the projects using a crypto API, misuse the respective library. Furthermore, we observed that only 7 % of the 1,501 misuses are within the application code. The analysis of embedded applications written in MicroPython revealed the importance of hybrid analysis as the only crypto calls were in C code that got shipped with the projects. To get an impression on the differences between the different domains and languages analyzed in previous studies, we compared our results against the misuses reported for Android apps [4] and C firmware images [13]. Our comparison confirms the impression that an opinionated API design actually helps developers avoiding misuses. While we concentrated on the impact of a user-friendly API design for Python, future work can verify if these results generalize to other languages, like Rust and Go. Thus, extending LICMA with new languages. Further, it may be interesting to extend the currently implemented rules in LICMA by an in-depth analysis of misuses of Python crypto APIs. ACKNOWLEDGMENTS This research work has been co-funded by the Deutsche Forschung gemeinschaft (DFG) – SFB 1119 CROSSING (236615297) and SFB 1053 MAKI (210487104), by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE, by the LOEWE initiative (Hesse, Germany) within the emergenCITY center. REFERENCES [1] Yasemin Acar, Michael Backes, Sascha Fahl, Simson Garfinkel, Doowon Kim, Michelle L Mazurek, and Christian Stransky. 2017. Comparing the usability of cryptographic apis. In IEEE Symposium on Security and Privacy (SP). IEEE, 154–171. [2] Yasemin Acar, Christian Stransky, Dominik Wermke, Michelle L Mazurek, and Sascha Fahl. 2017. Security developer studies with github users: Exploring a convenience sample. In Symposium on Usable Privacy and Security (SOUPS). 81– 95. [3] Alexia Chatzikonstantinou, Christoforos Ntantogian, Georgios Karopoulos, and Christos Xenakis. 2016. Evaluation of cryptography usage in android applications. In EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). 83–90. [4] Manuel Egele, David Brumley, Yanick Fratantonio, and Christopher Kruegel. 2013. An empirical study of cryptographic misuse in android applications. In ACM SIGSAC conference on Computer & communications security (CCS), Ahmad-Reza Sadeghi, Virgil Gligor, and Moti Yung (Eds.). ACM, 73–84. [5] Pietro Ferrara, Amit Kr Mandal, Agostino Cortesi, and Fausto Spoto. 2019. Crossprogramming language taint analysis for the iot ecosystem. Electronic Communications of the EASST 77 (2019). [6] Mohammadreza Hazhirpasand, Mohammad Ghafari, and Oscar Nierstrasz. 2020. Java Cryptography Uses in the Wild. In ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). ACM, Article 40. [7] Christopher Kane, Bo Lin, Saksham Chand, and Yanhong A. Liu. 2018. Highlevel Cryptographic Abstractions. CoRR abs/1810.09065 (2018). arXiv:1810.09065 http://arxiv.org/abs/1810.09065 [8] Stefan Krüger, Johannes Späth, Karim Ali, Eric Bodden, and Mira Mezini. 2018. CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs. In European Conference on Object-Oriented Programming (ECOOP) (Leibniz International Proceedings in Informatics (LIPIcs)), Vol. 109. Schloss Dagstuhl– Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 10:1–10:27. [9] David Lazar, Haogang Chen, Xi Wang, and Nickolai Zeldovich. 2014. Why does cryptographic software fail? A case study and open problems. In Asia-Pacific Workshop on Systems. 1–7. [10] Zaigham Mushtaq, Ghulam Rasool, and Balawal Shehzad. 2017. Multilingual source code analysis: A systematic literature review. IEEE Access 5 (2017), 11307– 11336. [11] Sarah Nadi, Stefan Krüger, Mira Mezini, and Eric Bodden. 2016. Jumping through hoops: Why do Java developers struggle with cryptography APIs?. In International Conference on Software Engineering (ICSE). 935–946. [12] Sazzadur Rahaman, Ya Xiao, Sharmin Afrose, Fahad Shaon, Ke Tian, Miles Frantz, Murat Kantarcioglu, and Danfeng Yao. 2019. Cryptoguard: High precision detection of cryptographic vulnerabilities in massive-sized java projects. In ACM SIGSAC Conference on Computer and Communications Security. 2455–2472. [13] Li Zhang, Jiongyi Chen, Wenrui Diao, Shanqing Guo, Jian Weng, and Kehuan Zhang. 2019. CryptoREX: Large-scale Analysis of Cryptographic Misuse in IoT Devices. In International Symposium on Research in Attacks, Intrusions and Defenses (RAID). USENIX Association, 151–164. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de); (2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de); (3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de); (4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Authors: Authors: (1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de); (2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de); (3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de); (4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Design and Implementation of Licma and 3.1 Design 3 Design and Implementation of Licma and 3.1 Design 3.2 Implementation 3.2 Implementation 4 Methodology and 4.1 Searching and Downloading Python Apps 4 Methodology and 4.1 Searching and Downloading Python Apps 4.2 Comparison with Previous Studies 4.2 Comparison with Previous Studies 5 Evaluation and 5.1 GitHub Python Projects 5 Evaluation and 5.1 GitHub Python Projects 5.2 MicroPython 5.2 MicroPython 6 Comparison with previous studies 6 Comparison with previous studies 7 Threats to Validity 7 Threats to Validity 8 Related Work 8 Related Work 9 Conclusion, Acknowledgments, and References 9 Conclusion, Acknowledgments, and References 9 CONCLUSION In this paper, we presented the first empirical study of crypto misuses in Python. To conduct the study, we implemented the first multi-language analysis tool for crypto misuses with rules to detect common misuses of five different Python libraries as well as the standard Java library. We analyzed 895 popular Python apps from GitHub and 51 MicroPython projects to identify misuses. Our analysis revealed that 52.26 % of the projects using a crypto API, misuse the respective library. Furthermore, we observed that only 7 % of the 1,501 misuses are within the application code. The analysis of embedded applications written in MicroPython revealed the importance of hybrid analysis as the only crypto calls were in C code that got shipped with the projects. To get an impression on the differences between the different domains and languages analyzed in previous studies, we compared our results against the misuses reported for Android apps [4] and C firmware images [13]. Our comparison confirms the impression that an opinionated API design actually helps developers avoiding misuses. While we concentrated on the impact of a user-friendly API design for Python, future work can verify if these results generalize to other languages, like Rust and Go. Thus, extending LICMA with new languages. Further, it may be interesting to extend the currently implemented rules in LICMA by an in-depth analysis of misuses of Python crypto APIs. LICMA ACKNOWLEDGMENTS This research work has been co-funded by the Deutsche Forschung gemeinschaft (DFG) – SFB 1119 CROSSING (236615297) and SFB 1053 MAKI (210487104), by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE, by the LOEWE initiative (Hesse, Germany) within the emergenCITY center. REFERENCES [1] Yasemin Acar, Michael Backes, Sascha Fahl, Simson Garfinkel, Doowon Kim, Michelle L Mazurek, and Christian Stransky. 2017. Comparing the usability of cryptographic apis. In IEEE Symposium on Security and Privacy (SP). IEEE, 154–171. [2] Yasemin Acar, Christian Stransky, Dominik Wermke, Michelle L Mazurek, and Sascha Fahl. 2017. Security developer studies with github users: Exploring a convenience sample. In Symposium on Usable Privacy and Security (SOUPS). 81– 95. [3] Alexia Chatzikonstantinou, Christoforos Ntantogian, Georgios Karopoulos, and Christos Xenakis. 2016. Evaluation of cryptography usage in android applications. In EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). 83–90. [4] Manuel Egele, David Brumley, Yanick Fratantonio, and Christopher Kruegel. 2013. An empirical study of cryptographic misuse in android applications. In ACM SIGSAC conference on Computer & communications security (CCS), Ahmad-Reza Sadeghi, Virgil Gligor, and Moti Yung (Eds.). ACM, 73–84. [5] Pietro Ferrara, Amit Kr Mandal, Agostino Cortesi, and Fausto Spoto. 2019. Crossprogramming language taint analysis for the iot ecosystem. Electronic Communications of the EASST 77 (2019). [6] Mohammadreza Hazhirpasand, Mohammad Ghafari, and Oscar Nierstrasz. 2020. Java Cryptography Uses in the Wild. In ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). ACM, Article 40. [7] Christopher Kane, Bo Lin, Saksham Chand, and Yanhong A. Liu. 2018. Highlevel Cryptographic Abstractions. CoRR abs/1810.09065 (2018). arXiv:1810.09065 http://arxiv.org/abs/1810.09065 [8] Stefan Krüger, Johannes Späth, Karim Ali, Eric Bodden, and Mira Mezini. 2018. CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs. In European Conference on Object-Oriented Programming (ECOOP) (Leibniz International Proceedings in Informatics (LIPIcs)), Vol. 109. Schloss Dagstuhl– Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 10:1–10:27. [9] David Lazar, Haogang Chen, Xi Wang, and Nickolai Zeldovich. 2014. Why does cryptographic software fail? A case study and open problems. In Asia-Pacific Workshop on Systems. 1–7. [10] Zaigham Mushtaq, Ghulam Rasool, and Balawal Shehzad. 2017. Multilingual source code analysis: A systematic literature review. IEEE Access 5 (2017), 11307– 11336. [11] Sarah Nadi, Stefan Krüger, Mira Mezini, and Eric Bodden. 2016. Jumping through hoops: Why do Java developers struggle with cryptography APIs?. In International Conference on Software Engineering (ICSE). 935–946. [12] Sazzadur Rahaman, Ya Xiao, Sharmin Afrose, Fahad Shaon, Ke Tian, Miles Frantz, Murat Kantarcioglu, and Danfeng Yao. 2019. 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LICMA's Analysis of Crypto API Misuses in Python Apps: Findings and Future Directions 

Sentiment Analysis through LLM Negotiations: Conclusion and References

As a society, we've always been drawn to a good story. From ancient myths to modern-day blockbusters, the power of narrative has the ability to captivate, inspire, and transform. In the world of technology, where innovation is the name of the game, storytelling has become the secret weapon behind some of the most buzzed-about startups. And the unexpected heroes of this new era? None other than the creative directors, the ad agency alchemists turned tech founders who have traded in their storyboards for the chance to rewrite the future. Armed with a knack for storytelling and a flair for the dramatic, these former ad agency stars are trading in their Cannes Lions for the chance to launch the next big thing. But as the hype around projects like Humane's AI Pin reaches fever pitch, it's worth asking: are these visionaries revolutionizing the tech landscape, or are they just spinning tales? Take Humane's AI Pin, for example. This little device, dreamt up by former Apple creative directors Imran Chaudhri and Bethany Bongiorno, has made quite the splash with its promise of a screenless, AI-driven future. But let's be real - it's not just the tech that's got everyone talking. It's the story. The vision of a world where technology seamlessly integrates into our lives, as natural as breathing. That's the kind of narrative that gets investors reaching for their checkbooks, the media clamoring for a headline and secures millions in funding. And Humane is far from alone in this new world order. Just look at the rise and fall of Elizabeth Holmes and Theranos. Sure, the revolutionary blood-testing technology never quite materialized, but damn if Holmes didn't spin one hell of a story. With her Steve Jobs-esque turtlenecks and promises of disruption, she had Silicon Valley eating out of the palm of her hand. Or what about Adam Neumann and WeWork? The man could sell a vision like no other, painting a picture of a workplace revolution that would “elevate the world's consciousness” (and the company's valuation to a cool $47 billion). But here's the thing about stories - they're only as good as the reality they're built on. When the curtain gets pulled back and the wizard is revealed to be just a guy with a smoke machine, things can get ugly fast. Just ask the folks who bought into the Theranos dream or the WeWork hype. When the story doesn't match the substance, it's not just disappointment that follows - it's disaster. Moreover, storytelling is not just about hype. Used responsibly, it can be a powerful tool for education and inspiration. When Steve Jobs introduced the iPhone, he didn't just sell a product; he painted a picture of how it would transform our lives. That narrative resonated because it was grounded in a genuine, revolutionary product. So what's the lesson here for the creative directors turned tech visionaries? The use of narrative as a launchpad is not without its risks: with great storytelling power comes great responsibility.The ability to craft a compelling narrative is a gift, but it's one that needs to be used wisely. The best stories, the ones that truly change the game, are the ones that are grounded in something real. Something tangible. Something that doesn't just tickle the imagination but actually follows through on its promises. This is the tightrope that creative directors in the tech world must walk. As for Humane's AI Pin? Only time will tell if it can live up to the hype. But one thing's for sure - in the wild west of tech startups, the storytellers are the new sheriffs in town. They're the ones who can make us believe in a brighter future, a more connected world, a reality where anything is possible. And in a world that can often feel like it's spinning out of control, that's a pretty powerful thing. But as we watch these narratives unfold, it's on us to remember that not every story has a happy ending, like . We've got to approach each new tale with a healthy dose of wonder and a hearty helping of skepticism. Because in the end, the most compelling story isn't always the most true - but it might just be the one that changes everything. As a society, we've always been drawn to a good story. From ancient myths to modern-day blockbusters, the power of narrative has the ability to captivate, inspire, and transform. In the world of technology, where innovation is the name of the game, storytelling has become the secret weapon behind some of the most buzzed-about startups. And the unexpected heroes of this new era? None other than the creative directors, the ad agency alchemists turned tech founders who have traded in their storyboards for the chance to rewrite the future. Armed with a knack for storytelling and a flair for the dramatic, these former ad agency stars are trading in their Cannes Lions for the chance to launch the next big thing. But as the hype around projects like Humane's AI Pin reaches fever pitch, it's worth asking: are these visionaries revolutionizing the tech landscape, or are they just spinning tales? Take Humane's AI Pin, for example. This little device, dreamt up by former Apple creative directors Imran Chaudhri and Bethany Bongiorno, has made quite the splash with its promise of a screenless, AI-driven future. But let's be real - it's not just the tech that's got everyone talking. It's the story. The vision of a world where technology seamlessly integrates into our lives, as natural as breathing. That's the kind of narrative that gets investors reaching for their checkbooks, the media clamoring for a headline and secures millions in funding. And Humane is far from alone in this new world order. Just look at the rise and fall of Elizabeth Holmes and Theranos. Sure, the revolutionary blood-testing technology never quite materialized, but damn if Holmes didn't spin one hell of a story. With her Steve Jobs-esque turtlenecks and promises of disruption, she had Silicon Valley eating out of the palm of her hand. Or what about Adam Neumann and WeWork? The man could sell a vision like no other, painting a picture of a workplace revolution that would “elevate the world's consciousness” (and the company's valuation to a cool $47 billion). But here's the thing about stories - they're only as good as the reality they're built on. When the curtain gets pulled back and the wizard is revealed to be just a guy with a smoke machine, things can get ugly fast. Just ask the folks who bought into the Theranos dream or the WeWork hype. When the story doesn't match the substance, it's not just disappointment that follows - it's disaster. Moreover, storytelling is not just about hype. Used responsibly, it can be a powerful tool for education and inspiration. When Steve Jobs introduced the iPhone, he didn't just sell a product; he painted a picture of how it would transform our lives. That narrative resonated because it was grounded in a genuine, revolutionary product. So what's the lesson here for the creative directors turned tech visionaries? The use of narrative as a launchpad is not without its risks: with great storytelling power comes great responsibility.The ability to craft a compelling narrative is a gift, but it's one that needs to be used wisely. The best stories, the ones that truly change the game, are the ones that are grounded in something real. Something tangible. Something that doesn't just tickle the imagination but actually follows through on its promises. This is the tightrope that creative directors in the tech world must walk. As for Humane's AI Pin? Only time will tell if it can live up to the hype. But one thing's for sure - in the wild west of tech startups, the storytellers are the new sheriffs in town. They're the ones who can make us believe in a brighter future, a more connected world, a reality where anything is possible. And in a world that can often feel like it's spinning out of control, that's a pretty powerful thing. But as we watch these narratives unfold, it's on us to remember that not every story has a happy ending, like . We've got to approach each new tale with a healthy dose of wonder and a hearty helping of skepticism. Because in the end, the most compelling story isn't always the most true - but it might just be the one that changes everything.

Narrative as a Launchpad: How Creative Directors Propel Tech Ventures Like Humane's AI Pin

একটি লঞ্চপ্যাড হিসাবে আখ্যান: কিভাবে ক্রিয়েটিভ ডিরেক্টররা হিউম্যানের এআই পিনের মতো টেক ভেঞ্চারকে এগিয়ে দেয়

Erzählung als Startrampe: Wie Kreativdirektoren Technologieunternehmen wie Humanes KI vorantreiben Pin

La narrativa como plataforma de lanzamiento: cómo los directores creativos impulsan empresas tecnológicas como la IA de Humane

Le récit comme rampe de lancement : comment les directeurs créatifs propulsent les entreprises technologiques comme l'IA de Humane

लॉन्चपैड के रूप में कथा: कैसे क्रिएटिव डायरेक्टर्स ह्यूमेन के एआई पिन जैसे तकनीकी उपक्रमों को आगे बढ़ाते हैं

物語を発射台として: クリエイティブ ディレクターが Humane の AI Pin のようなテクノロジー ベンチャーを推進する方法

런치패드로서의 내러티브: 크리에이티브 디렉터가 Humane의 AI 핀과 같은 기술 벤처를 추진하는 방법

Narrativa como plataforma de lançamento: como os diretores criativos impulsionam empreendimentos tecnológicos como o AI Pin da Humane

Нарратив как стартовая площадка: как креативные директора продвигают технологические предприятия, как пин от Humane об искусственном интеллекте

Bir Başlatma Paneli Olarak Anlatı: Yaratıcı Yönetmenler, Humane'nin Yapay Zeka Pinini Benzeri Teknoloji Girişimlerini Nasıl İlerletir?

Tường thuật như một bệ phóng: Cách các Giám đốc Sáng tạo Thúc đẩy các dự án mạo hiểm công nghệ giống như Ghim AI của Humane

叙事作为启动板：创意总监如何推动 Humane 的 AI Pin 等科技企业的发展

This paper is under CC 4.0 license. available on arxiv Authors: (1) Ryen W. White, Microsoft Research, Redmond, WA, USA. Table of Links Abstract and Taking Search to task AI Copilots Challenges Opportunities The Undiscovered Country and References 5 THE UNDISCOVERED COUNTRY AI copilots will transform how we search. Tasks are central to people’s lives and more support is needed for complex tasks in search settings. Some limited support for these tasks already exists in search engines, but copilots will expand the task frontier to make more tasks actionable and address the “last mile” in search interaction: task completion [58]. Moving forward, search providers should invest in “better together” experiences that utilize copilots plus traditional search, make these joint experiences more seamless for searchers, and add more support for their use in practice, e.g., help people to quickly understand copilot capabilities and potential and/or recommend the best modality for the current task or task stage. This includes experiences where both modalities are offered separately and can be selected by searchers and those where there is unification and the selection happens automatically based on the query and the conversation context. The foundation models that power copilots have other search-related applications, e.g., for generating and applying intent taxonomies [43] or for evaluation [19]. We must retain a continued focus on human-AI cooperation, where searchers stay in control while the degree of system support increases as needed [44], and on AI safety. 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