This Letter reports measurements of muon-neutrino disappearance and electron-neutrino appearance and the corresponding antineutrino processes between the two NOvA detectors in the NuMI neutrino beam. These measurements use a dataset with double the neutrino mode beam exposure that was previously analyzed, along with improved simulation and analysis techniques. A joint fit to these samples in the three-flavor paradigm results in the most precise single-experiment constraint on the atmospheric neutrino mass splitting, Δ m 32 2 = 2.43 1 − 0.034 + 0.036 ( − 2.47 9 − 0.036 + 0.036 ) × 10 − 3 eV 2 if the mass ordering is normal (inverted). In both orderings, a region close to maximal mixing with sin 2 θ 23 = 0.5 5 − 0.06 + 0.02 is preferred. The NOvA data show a mild preference for the normal mass ordering with a Bayes factor of 2.4 (corresponding to 70% of the posterior probability), indicating that the normal ordering is 2.4 times more probable than the inverted ordering. When incorporating a 2D Δ m 32 2 − sin 2 2 θ 13 constraint based on Daya Bay data, this preference strengthens to a Bayes factor of 6.6 (87%).
As cybercriminals increasingly target health care, hospitals face the growing threat of ransomware attacks. Ransomware is a type of malicious software that prevents users from accessing electronic systems and demands a ransom to restore access. We create and link a database of hospital ransomware attacks to Medicare claims data. We quantify the effects of ransomware attacks on hospital operations and patient outcomes. Ransomware attacks decrease hospital volume by 17-24 percent during the initial attack week, with recovery occurring within 3 weeks. Among patients already admitted to the hospital when a ransomware attack begins, in-hospital mortality increases by 34-38 percent. (JEL D83, I12, I13, K42)
This paper introduces a distributed data-driven attack-resilient consensus problem under both false data injection (FDI) and denial-of-service (DoS) attacks and proposes a data-driven consensus control framework, consisting of a group of comprehensive attack-resilient data-driven observers. The proposed group of observers is designed to estimate FDI attacks, external disturbances, and lumped disturbances, combined with a DoS attack compensation mechanism. A rigorous stability analysis of the approach is provided to ensure the boundedness of the distributed neighborhood estimation consensus error. The effectiveness of the approach is validated through numerical examples involving both leaderless consensus and leader–follower consensus, demonstrating significantly improved resilient performance compared to existing data-driven control approaches.
Acute, traumatic meniscus tears are common and should be repaired whenever possible. However, the biological age of the patient, along with the specific tear morphology, may significantly influence the selection of the repair technique, expected clinical outcomes and the postoperative rehabilitation protocol. Risk factors for failure of meniscus repair, such as ligament laxity, need to be addressed to improve the healing potential of the meniscus. Biologic augmentation strategies, including bone marrow stimulation, platelet-rich plasma, fibrin clot, mesenchymal stem cells or meniscal wrapping, can be used to enhance healing and reduce failure of meniscus repair rates. However, the clinical evidence remains limited and of low quality. As such, the routine use of biologic augmentation in meniscus repair warrants critical evaluation. In patients with post-meniscectomy syndrome, meniscus allograft transplantation (MAT) may be a viable option to reduce pain and joint degeneration and improve knee function. Meniscus implants provide alternatives to traditional MAT; however, their long-term efficacy, chondroprotective effects and integration within the knee joint require further research. Meniscus reconstruction using tendon autografts has been described as an alternative treatment option in patients with meniscus loss. Emerging methods, such as gene therapy and repurposed drugs, demonstrate in vitro potential for advancing meniscal repair, although their clinical applications are still in their infancy. Future research is necessary to optimize meniscal repair techniques, enhance clinical efficacy, and ultimately, improve outcomes in patients. Level of Evidence Level V.
