Tootfinder

Playable Pressure: Affective Dramaturgy and Selective Realism in the Design of a VR Emergency-Response Serious Game
Jan K. Argasi\'nski
https://arxiv.org/abs/2608.10763 https://arxiv.org/pdf/2608.10763 https://arxiv.org/html/2608.10763
arXiv:2608.10763v1 Announce Type: new
Abstract: Professional simulations stage not only procedures but models of what should command attention, which emotions belong in competent practice, and whose distress becomes part of the task. This article develops affective dramaturgy through critical design-document analysis of a virtual-reality emergency-response project. The corpus comprises two non-public production records. We identify six families of specified pressure and examine how sensory staging, proximity, trigger authority, task conflict, and response allocation imply a selectively receptive triage professional. The documented design can make emergency work morally and socially crowded, yet it can also turn grief, vulnerability, and mental-health-coded behavior into adjustable difficulty. We propose answerability at two levels-in-play response and post-play debriefability-and derive case-based questions about occupational purpose, representation, adaptation, and accountability. These questions are sensitizing propositions, not a validated framework for user effects or emergency practice.
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How to spot a psychopath
"Mitchell built a template of 20 attributes, divided into four clusters, and 25 tactics that would identify a high-functioning persistent predatory personality type. Cluster one includes a need for control; a grandiose sense of self; pathological inner response to challenge; vengefulness; refusal to compromise. Cluster two includes being predatory or exploitative; sadistic and cruel; having a low regard for laws, agreements, social and moral codes; no boundarie…

How to spot a psychopath: ‘It’s like the difference between a domestic cat and a wild cat’
People with persistent predatory personalities cause an inordinate amount of pain. Recently, our shared understanding of them has grown – and it could help protect us

Euclid: Quick Data Release (Q1) -- Exploring the detailed visual morphology of galaxies in clusters
Mas-Buitrago, Kruk, O'Ryan, Nardone, La Marca, Awad, Baes, Fossati, G\'eron, Ghaffari, Girardi, Lintott, Sorce, Altieri, Durret, Pettorino, Irureta-Goyena, Simmons, Reerink, S\'anchez, Knapen, Shankar, Duran-Camacho, P\'erez-Mart\'inez, Walmsley, Auricchio, Baccigalupi, Baldi, Bardelli, Battaglia, Biviano, Bolzonella, Bonchi, Branchini, Brescia, Brinchmann, Camera, Ca\~nas-Herrera, Capobianco, Carbone, Carretero, Castellano, Castignani, Cavuoti, Cimatti, Colodro-Conde, Congedo, Conselice, Conversi, Copin, Costille, Courbin, Courtois, Cropper, Degaudenzi, De Lucia, Dole, Dubath, Dupac, Dusini, Ealet, Fabricius, Farina, Farinelli, Ferriol, Fosalba, Fotopoulou, Frailis, Franceschi, Fumana, Galeotta, George, Gillis, Giocoli, G\'omez-Alvarez, Gracia-Carpio, Grazian, Grupp, Gwyn, Holmes, Hook, Hormuth, Hornstrup, Huertas-Company, Jahnke, Jhabvala, Joachimi, Kermiche, Kiessling, Kubik, K\"ummel, Kunz, Kurki-Suonio, Le Brun, Ligori, Lilje, Lindholm, Lloro, Mainetti, Mansutti, Marggraf, Martinelli, Martinet, Marulli, Massey, Maurogordato, Medinaceli, Melchior, Meneghetti, Merlin, Meylan, Mora, Moresco, Moscardini, Munari, Neissner, Niemi, Nightingale, Padilla, Paltani, Pasian, Pedersen, Percival, Pezzotta, Pires, Polenta, Poncet, Popa, Pozzetti, Raison, Renzi, Rhodes, Riccio, Romelli, Roncarelli, Rusholme, Saglia, Sakr, S\'anchez, Sapone, Sartoris, Schneider, Schrabback, Scodeggio, Secroun, Sihvola, Simon, Sirignano, Sirri, Tallada-Cresp\'{i}, Taylor, Teplitz, Tereno, Tessore, Toft, Toledo-Moreo, Torradeflot, Tutusaus, Valiviita, Vassallo, Kleijn, Veropalumbo, Wang, Weller, Zacchei, Zamorani, Zerbi, Zucca, Macias-Perez, Sereno
https://arxiv.org/abs/2609.08962 https://arxiv.org/pdf/2609.08962 https://arxiv.org/html/2609.08962
arXiv:2609.08962v1 Announce Type: new
Abstract: Galaxy clusters provide unique laboratories for studying environmental effects on galaxy evolution. The morphology--density ($T$--$\Sigma$) and morphology--cluster-centric radius ($T$--$R$) relations trace how galaxy morphology is influenced by the environment, but previous studies at intermediate redshifts have been limited in both sample size and radial coverage. We use the Euclid Quick Data Release 1 (Q1) visual morphology catalogue to measure the $T$--$\Sigma$ and $T$--$R$ relations for smooth, featured-or-disc, and barred galaxies in known clusters at $0.2\leq z\leq 0.5$, extending this analysis to large cluster-centric distances ($3 R_{500c}$) and studying their dependence on stellar mass. Using photometric redshifts and stellar masses provided by Euclid, we identify 1754 cluster members within $1.5 R_{500c}$, distributed across 71 clusters. We classify the identified galaxies as smooth, featured-or-disc, or barred using the predicted vote fractions provided by the Zoobot deep learning foundation model in the Q1 visual morphology catalogue. We confirm the $T$--$\Sigma$ relation in all the stellar mass ranges studied, with a stronger influence of the cluster environment on galaxy morphology in the densest parts of the cluster and closer to the cluster centre. Beyond $1.5 R_{500c}$, the morphological segregation weakens, with featured-or-disc galaxies overtaking smooth galaxies at the lowest densities, consistent with the growing contribution of field interlopers in the cluster outskirts. For barred galaxies, we find a tentative decline of the bar fraction toward lower densities that is most pronounced for the most massive galaxies. In conclusion, our results show that the cluster environment drives a progressive transformation of galaxy morphology, with the loss of disc structure becoming more pronounced towards the cluster core, where environmental processes act most efficiently.
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