Rеkоnfigurаciја distributivnе mrеžе primеnоm mеtоdе pоmеrајućеg rеgistrа оtvоrеnih prеkidаčа by Dаrkо Šоšić, Тоmislаv Rајić, Brаnkо Stојаnоvić

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Molecular Epidemiology of Salmonella enterica in Poultry in South Africa Using the Farm-to-Fork Approach by Melissa A. Ramtahal, Anou M. Somboro, Daniel G. Amoako, Akebe L. K. Abia, Keith Perrett, Linda A. Bester, Sabiha Y. Essack

“…All isolates harboured the misL, orfL, pipD, stn, spiC, hilA, and sopB virulence genes, while pefA, spvA, spvB, and spvC were absent. …”
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Penot’s Compactness Property in Ultrametric Spaces with an Application by Mostafa Bachar, Messaoud Bounkhel, Samih Lazaiz

“…The spherical completeness property misled some mathematicians to it to hyperconvexity in metric spaces. …”
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Assessing ExxonMobil’s climate change communications (1977–2014) by Geoffrey Supran, Naomi Oreskes

“…Given this discrepancy, we conclude that ExxonMobil misled the public. Our content analysis also examines ExxonMobil’s discussion of the risks of stranded fossil fuel assets. …”
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Rapid Multiorgan Dissemination of Low-Grade Myxofibrosarcoma: A Case Report by Yasutaka Murahashi, Mitsunori Kaya, Tamotsu Soma, Mikito Sasaki, Satoshi Nagoya, Takuro Wada, Toshihiko Yamashita

“…The disease progression was really unexpected and misled every possible medical interpretation, leading to rapid worsening of the patient's clinical conditions and no chance for therapy. …”
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We are entering a new era of problems: AI-generated images in research manuscripts by Kabir Suman Dash, Vini Mehta, Priyanka Kharat

“…Every individual has the potential to be misled by the AI image-fraud techniques outlined in this article. …”
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Survey of optical-based physical domain adversarial attacks and defense by CHEN Jinyin, ZHAO Xiaoming, ZHENG Haibin, GUO Haifeng

“…Deep learning models are misled into making false predictions by adversarial attacks that implant tiny perturbations into the original input, which are imperceptible to the human eye. …”
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Eliminating the Effect of Rating Bias on Reputation Systems by Leilei Wu, Zhuoming Ren, Xiao-Long Ren, Jianlin Zhang, Linyuan Lü

“…However, many empirical cases demonstrate that consumers may be misled by rating scores added by unreliable users or deliberate tampering. …”
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The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading by Hiroki Maehara, Yuta Ueno, Takefumi Yamaguchi, Yoshiyuki Kitaguchi, Dai Miyazaki, Ryohei Nejima, Takenori Inomata, Naoko Kato, Tai-ichiro Chikama, Jun Ominato, Tatsuya Yunoki, Kinya Tsubota, Masahiro Oda, Manabu Suzutani, Tetsuju Sekiryu, Tetsuro Oshika

“…Less experienced ophthalmologists were misled due to incorrect AI guidance, but corneal specialists were not. …”
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