Tootfinder

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 180 nodes and 45047 edges.
Tags: Soc…

Search for a $\mu^ \mu^-$ resonance in four-muon final states at Belle II
Collaboration, Adachi, Adamczyk, Aggarwal, Ahmed, Aihara, Akopov, Aloisio, Ky, Asner, Atmacan, Aushev, Aversano, Ayad, Babu, Bae, Bahinipati, Bambade, Banerjee, Bansal, Barrett, Baudot, Baur, Beaubien, Becherer, Becker, Bennett, Bernlochner, Bertacchi, Bertemes, Bertholet, Bessner, Bettarini, Bhuyan, Bianchi, Bilka, Bilokin, Biswas, Bobrov, Bodrov, Bolz, Bozek, Bra\v{c}ko, Branchini, Browder, Budano, Bussino, Campajola, Cao, Casarosa, Cecchi, Cerasoli, Chang, Chang, Cheaib, Cheema, Cheon, Chilikin, Chirapatpimol, Cho, Cho, Cho, Choi, Choudhury, Corona, Cremaldi, Das, Dattola, De La Cruz-Burelo, De La Motte, De Nardo, De Nuccio, De Pietro, de Sangro, Destefanis, Dhamija, Di Canto, Di Capua, Dingfelder, Dole\v{z}al, Dong, Dorigo, Dort, Dreyer, Dubey, Dujany, Ecker, Eliachevitch, Epifanov, Feichtinger, Ferber, Ferlewicz, Fillinger, Finck, Finocchiaro, Fodor, Forti, Frey, Fulsom, Gabrielli, Ganiev, Garcia-Hernandez, Garg, Gaudino, Gaur, Gaz, Gellrich, Ghevondyan, Ghosh, Ghumaryan, Giakoustidis, Giordano, Giri, Glazov, Gobbo, Godang, Gogota, Goldenzweig, Gradl, Grammatico, Graziani, Greenwald, Gruberov\'a, Gu, Gudkova, Halder, Han, Hara, Hayashii, Hazra, Hearty, Hedges, Heidelbach, de la Cruz, Villanueva, Higuchi, Hoek, Hohmann, Horak, Hsu, Humair, Iijima, Inguglia, Ipsita, Ishikawa, Itoh, Iwasaki, Jackson, Jacobs, Jang, Ji, Jia, Jin, Joo, Junkerkalefeld, Kalita, Kandra, Kang, Karyan, Kawasaki, Keil, Kiesling, Kim, Kim, Kim, Kim, Kindo, Kinoshita, Kody\v{s}, Koga, Kohani, Kojima, Korobov, Korpar, Kovalenko, Kowalewski, Kraetzschmar, Kri\v{z}an, Krokovny, Kuhr, Kumar, Kumar, Kumar, Kumara, Kunigo, Kuzmin, Kwon, Lacaprara, Lai, Lam, Lanceri, Lange, Laurenza, Lautenbach, Leboucher, Le Diberder, Lee, Levit, Lewis, Li, Li, Li, Li, Libby, Liu, Liu, Liu, Liventsev, Longo, Lueck, Lyu, Ma, Maggiora, Maharana, Maiti, Maity, Mancinelli, Manfredi, Manoni, Mantovano, Marcantonio, Marcello, Marinas, Martel, Martellini, Martini, Martinov, Massaccesi, Masuda, Matsuoka, Matvienko, Maurya, McKenna, Mehta, Meier, Merola, Metzner, Milesi, Miller, Mirra, Miyabayashi, Miyake, Mizuk, Mohanty, Molina-Gonzalez, Mondal, Moneta, Moser, Mrvar, Mussa, Nakamura, Nakao, Nakazawa, Charan, Naruki, Narwal, Natkaniec, Natochii, Nayak, Nayak, Nazaryan, Niebuhr, Nishida, Ogawa, Onishchuk, Ono, Onuki, Oskin, Otani, Pakhlova, Panta, Pardi, Parham, Park, Park, Paschen, Passeri, Patra, Paul, Pedlar, Peschke, Pestotnik, Piccolo, Piilonen, Angioni, Podesta-Lerma, Podobnik, Pokharel, Praz, Prell, Prencipe, Prim, Purwar, Rados, Raeuber, Raiz, Rauls, Reif, Reiter, Remnev, Ripp-Baudot, Rizzo, Robertson, Roehrken, Roney, Rostomyan, Rout, Russo, Sanders, Sandilya, Santelj, Sato, Savinov, Scavino, Schmitt, Schwanda, Schwickardi, Seino, Selce, Senyo, Serrano, Sevior, Sfienti, Shan, Shen, Shi, Shillington, Shimasaki, Shiu, Shtol, Sibidanov, Simon, Singh, Skorupa, Sobie, Sobotzik, Soffer, Sokolov, Solovieva, Spataro, Spruck, Stari\v{c}, Stavroulakis, Stefkova, Stroili, Sumihama, Sumisawa, Sutcliffe, Svidras, Takizawa, Tamponi, Tanaka, Tanida, Tenchini, Tittel, Tiwary, Tonelli, Torassa, Trabelsi, Tsaklidis, Uchida, Ueda, Unger, Unno, Uno, Uno, Urquijo, Ushiroda, Vahsen, van Tonder, Varvell, Veronesi, Vinokurova, Vismaya, Vitale, Vobbilisetti, Volpe, Wach, Wakai, Wallner, Wang, Wang, Wang, Wang, Warburton, Watanuki, Wessel, Won, Xu, Yabsley, Yamada, Yan, Yang, Yelton, Yin, Yoshihara, Yuan, Yusa, Zani, Zhang, Zhilich, Zhou, Zhou, Zhukova
https://arxiv.org/abs/2403.02841 https://arxiv.org/pdf/2403.02841
arXiv:2403.02841v1 Announce Type: new
Abstract: We report on a search for a resonance $X$ decaying to a pair of muons in $e^{ }e^{-}\rightarrow \mu^ \mu^- X$ events in the 0.212-9.000 GeV/$c^{2}$ mass range, using 178 fb$^{-1}$ of data collected by the BelleII experiment at the SuperKEKB collider at a center of mass energy of 10.58 GeV. The analysis probes two different models of $X$ beyond the standard model: a $Z^{\prime}$ vector boson in the $L_{\mu}-L_{\tau}$ model and a muonphilic scalar. We observe no evidence for a signal and set exclusion limits at the 90\% confidence level on the products of cross section and branching fraction for these processes, ranging from 0.046 fb to 0.97 fb for the $L_{\mu}-L_{\tau}$ model and from 0.055 fb to 1.3 fb for the muonphilic scalar model. For masses below 6 GeV/$c^{2}$, the corresponding constraints on the couplings of these processes to the standard model range from 0.0008 to 0.039 for the $L_{\mu}-L_{\tau}$ model and from 0.0018 to 0.040 for the muonphilic scalar model. These are the first constraints on the muonphilic scalar from a dedicated search.

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 126 nodes and 28561 edges.
Tags: Soc…

Recently I had a unit test that was failing about 10% of the time. The error was a DOM element was not found. Upon further investigation a factory that built a test response built a response 1 in 10 times that didn't produce the DOM element.
Though the behavior of the code was correct I didn't have a clear good best practice in mind for how to allow the factory to generate responses but exclude a specific shape that was invalid.
Would love any links to articles that migh…

Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions
Roza Al-Hindaw, Taqwa I. Alhadidi, Mohammad Adas
https://arxiv.org/abs/2405.01504

Evaluation and Optimization of Adaptive Cruise Control in Autonomous Vehicles using the CARLA Simulator: A Study on Performance under Wet and Dry Weather Conditions
Adaptive Cruise Control ACC can change the speed of the ego vehicle to maintain a safe distance from the following vehicle automatically. The primary purpose of this research is to use cutting-edge computing approaches to locate and track vehicles in real time under various conditions to achieve a safe ACC. The paper examines the extension of ACC employing depth cameras and radar sensors within Autonomous Vehicles AVs to respond in real time by changing weather conditions using the Car Learning…

Elon Musk says X plans to make Grok available to all Premium subscribers "later this week", expanding on Premium support; X Premium costs $8 per month (Sarah Perez/TechCrunch)
https://techcrunch.com/2024/03/26/elon

Elon Musk says all Premium subscribers on X will gain access to AI chatbot Grok this week | TechCrunch
Following Elon Musk's xAI's move to open source its Grok large language model earlier in March, the X owner on Tuesday said that the company formerly

Human-Robot Interaction Conversational User Enjoyment Scale (HRI CUES)
Bahar Irfan, Jura Miniota, Sofia Thunberg, Erik Lagerstedt, Sanna Kuoppam\"aki, Gabriel Skantze, Andr\'e Pereira
https://arxiv.org/abs/2405.01354

Human-Robot Interaction Conversational User Enjoyment Scale (HRI CUES)
Understanding user enjoyment is crucial in human-robot interaction (HRI), as it can impact interaction quality and influence user acceptance and long-term engagement with robots, particularly in the context of conversations with social robots. However, current assessment methods rely solely on self-reported questionnaires, failing to capture interaction dynamics. This work introduces the Human-Robot Interaction Conversational User Enjoyment Scale (HRI CUES), a novel scale for assessing user enj…

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 180 nodes and 45047 edges.
Tags: Soc…

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 126 nodes and 28561 edges.
Tags: Soc…

sp_high_school_new: High school dynamic contacts (2011-2012)
These datasets contain the temporal network of contacts between students in a high school in Marseilles, France. The first dataset gives the contacts of the students of three classes during 4 days in Dec. 2011, and the second corresponds to the contacts of the students of 5 classes during 7 days (from a Monday to the Tuesday of the following week) in Nov. 2012.
This network has 180 nodes and 45047 edges.
Tags: Soc…