# Facilities Published articles for Facilities. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## French Blood Banks Hit Alongside Cyberattack On European Supermarkets DevFeed: [French Blood Banks Hit Alongside Cyberattack On European Supermarkets]() Original publisher: [Read original article]() Author: BeauHD Published: 2026-11-04T19:00:00Z Content type: news Language: en Sources: [Slashdot]() Topics: [Cybersecurity]() Tags: [alerts](), [attack](), [banks](), [belgium](), [blood](), [control](), [cooling](), [cyberattack](), [cybersecurity](), [efs](), [equipment](), [facilities](), [france](), [french-blood-establishment](), [hackers](), [incident](), [investigations](), [monday](), [monitoring](), [security](), [supermarkets]() ### AI overview A cyberattack disrupted cold-storage monitoring and control systems at three regional French blood-bank facilities, but blood supplies were unaffected. Staff were alerted and moved blood to refrigerators that were not connected to the affected systems. Investigations are examining how the attack happened, which equipment was affected, and when the systems can safely return to service. The excerpt also notes a similar French supermarket cooling-unit incident the previous month, which caused fires and food losses. ### Source excerpt An anonymous reader quotes a report from Reuters: The refrigerators at three regional blood banks in France were hit by a cyberattack overnight between Sunday and Monday, at the same time hackers struck supermarkets from Sweden to Belgium. "Several regional facilities of the French Blood Establishment (EFS) were affected by a cybersecurity incident that impacted certain cold storage room monitoring and control systems," the health ministry said in a statement. The incident had no impact on blood supplies, EFS spokesperson Charley Dubois said. "We have staff round the clock since blood can be needed at any time. They were warned about the problems by alerts and moved the blood to other refrigerators that were not connected," she said. [...] Investigations are under way into how the attack was carried out, what equipment may have been affected and when systems can safely return to service. The attack followed a similar incident in France last month when police said hackers seized control of cooling units at hundreds of supermarkets, causing fires and food losses. Read more of this story at Slashdot. ## Building connections across the research infrastructure DevFeed: [Building connections across the research infrastructure]() Original publisher: [Read original article]() Author: MIT.nano Published: 2026-11-03T19:30:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Tool](), [synchronization]() Tags: [2018](), [2023](), [2026](), [about](), [adapting](), [added](), [administration](), [advanced](), [all](), [anna-osherov](), [artificial-intelligence](), [building](), [characterization-nano](), [coalition](), [collaboration](), [electronics](), [fab-nano](), [facilities](), [infrastructure](), [jorg-scholvin](), [lab-management](), [make](), [microelectronics](), [microscopy](), [mit](), [mit-nano](), [more](), [nanofab-equipment-management-and-operations-nemo](), [nanofabrication-facilities](), [nanoscience-and-nanotechnology](), [nemc-technical-concierge](), [northeast-microelectronics-coalition-nemc-hub](), [open-source](), [research](), [shared-facilities](), [sharing-lab-equipment](), [special-events-and-guest-speakers](), [technology](), [vladimir-bulovic]() ### AI overview The NEMO community uses an open-source platform to manage operations within individual shared research facilities and share facility-specific extensions. At the 2026 NEMO User Meeting, institutions showed adaptations for equipment status and reservations, billing, tool monitoring, chemical management, training, and workflow automation. MIT.nano also presented Hydra, an open-source platform under development for the NEMC Technical Concierge: it connects multiple NEMO installations and draws current information from existing facility systems, rather than replacing them or relying on a separately maintained database. NEMO supplies operational information within a facility; Hydra is intended to make capabilities discoverable across facilities. The article presents this as a way to address the challenge of finding specialized research resources, while emphasizing that facilities have distinct needs and can adapt the shared platform. ### Source excerpt MIT.nano and the Northeast Microelectronics Coalition gathered facility leaders and technology professionals from across the nation to explore ways to make shared-access facilities more connected. ## SensOFormer: Foundation Models for Particle Accelerators DevFeed: [SensOFormer: Foundation Models for Particle Accelerators]() Original publisher: [Read original article]() Author: Mahindra Rautela, Alexander Scheinker Published: 2026-11-03T05:00:00Z Content type: article Language: en Sources: [arXiv: Machine Learning]() Topics: [AI Foundation Models](), [Representation learning](), [Artificial Intelligence]() Tags: [accelerators](), [anomaly-detection](), [architecture](), [complex-systems](), [control](), [cs-lg](), [data](), [datasets](), [diagnostics](), [facilities](), [foundation-model](), [foundation-models](), [learn](), [missing-data](), [networks](), [physics-acc-ph](), [sensor](), [telemetry](), [transformer](), [variable](), [volumes]() ### AI overview SensOFormer is a self-supervised foundation model for learning reusable sensor representations from particle-accelerator data. Its denoising masked transformer uses a Perceiver-style encoder-decoder to handle variable sensor sets, different sampling rates, and noisy measurements. Pretrained on multiple accelerator datasets, it is transferred to missing-data imputation, anomaly detection, cavity identification, and fault identification. The abstract reports evaluations suggesting one model can support these diverse operational tasks; it does not provide quantitative results in the supplied excerpt. ### Source excerpt arXiv:2611.02031v1 Announce Type: new Abstract: Large-scale scientific facilities, such as particle accelerators, are complex systems composed of thousands of interacting components that must operate collectively to support diagnostics and control, and ensure safe, reliable operation. These facilities rely on extensive sensor networks that generate large volumes of heterogeneous, incomplete, and noisy telemetry, often sampled at different rates across subsystems. In this paper, we adopt the foundation-model paradigm to learn general-purpose sensor representations from historical accelerator data through self-supervised pretraining. We introduce SensOFormer, a denoising masked transformer with a Perceiver-style encoder-decoder architecture designed to handle variable sensor sets, accommodate heterogeneous sampling rates, and learn robust representations from noisy measurements. The model is pretrained on multiple particle-accelerator datasets and transferred to downstream tasks, including missing-data imputation, anomaly detection, cavity identification, and fault identification. Through extensive evaluations and comparisons, we demonstrate that a single self-supervised model can learn reusable representations for diverse operational tasks in large-scale scientific facilities. Project page: https://mahindrautela.github.io/sensoformer.