Approaching the Ground State of Frustrated A-site Spinels: A Combined Magnetization and Polarized Neutron Scattering Study

We re-investigate the magnetically frustrated, {\it diamond-lattice-antiferromagnet} spinels FeAl$_2$O$_4$ and MnAl$_2$O$_4$ using magnetization measurements and diffuse scattering of polarized neutrons. In FeAl$_2$O$_4$, macroscopic measurements evidence a "cusp" in zero field-cooled susceptibility around 13~K. Dynamic magnetic susceptibility and {\it memory effect} experiments provide results that do not conform with a canonical spin-glass scenario in this material. Through polarized neutron scattering studies, absence of long-range magnetic order down to 4~K is confirmed in FeAl$_2$O$_4$. By modeling the powder averaged differential magnetic neutron scattering cross-section, we estimate that the spin-spin correlations in this compound extend up to the third nearest-neighbour shell. The estimated value of the Land\'{e} $g$ factor points towards orbital contributions from Fe$^{2+}$. This is also supported by a Curie-Weiss analysis of the magnetic susceptibility. MnAl$_2$O$_4$, on the contrary, undergoes a magnetic phase transition into a long-range ordered state below $\approx$ 40~K, which is confirmed by macroscopic measurements and polarized neutron diffraction. However, the polarized neutron studies reveal the existence of prominent spin-fluctuations co-existing with long-range antiferromagnetic order. The magnetic diffuse intensity suggests a similar short range order as in FeAl$_2$O$_4$. Results of the present work supports the importance of spin-spin correlations in understanding magnetic response of frustrated magnets like $A$-site spinels which have predominant short-range spin correlations reminiscent of the "spin liquid" state.Comment: 10 pages, 10 figures, double-column, accepted in Phys. Rev. B, 201

Is Noninvasive Vagus Nerve Stimulation a Safe and Effective Alternative to Medication for Acute Migraine Control?

BACKGROUND: Noninvasive neuromodulation devices have been used for a variety of headache disorders, including cluster and migraine, since recently being cleared by the Federal Drug Administration. Although these devices have been touted as low-risk options for improved headache control, the data behind actual efficacy endpoints remain unclear. OBJECTIVE: To critically assess current evidence regarding the efficacy of the noninvasive vagus nerve stimulator (nVNS) device for acute migraine management. METHODS: The objective was addressed through the development of a structured critically appraised topic. This included a clinical scenario with a clinical question, literature search strategy, critical appraisal, results, evidence summary, commentary, and bottom line conclusions.Participants included consultant and resident neurologists, a medical librarian, clinical epidemiologists, and a content expert in the field of headache. RESULTS: A randomized, double-blind, sham-controlled clinical trial was selected for critical appraisal. In this trial, the primary endpoint (pain freedom at 120 min after use of nVNS for first acute migraine attack) was not met when compared with sham device (30.4% for nVNS vs. 19.7% for sham; P=0.067). However, there were statistically significant differences found for various secondary endpoints favoring nVNS, such as pain freedom rates at 30 and 60 minutes, pain relief at 120 minutes, and mean percentage pain score reduction rates at 60 and 120 minutes. CONCLUSIONS: When comparing nVNS with sham, no statistically significant differences were found with regards to the primary endpoint of pain freedom at 120 minutes, although differences were found with various secondary endpoints and post hoc analysis. nVNS is likely a safe alternative to medications

Automated Generation of Formal Models from ST Control Programs for Verification Purposes

In large industrial control systems such as the ones installed at CERN, one of the main issues is the ability to verify the correct behaviour of the Programmable Logic Controller (PLC) programs. While manual and automated testing can achieve good results, some obvious problems remain unsolved such as the difficulty to check safety or liveness properties. This paper proposes a general methodology and a tool to verify PLC programs by automatically generating formal models for different model checkers out of ST code. The proposed methodology defines an automata-based formalism used as intermediate model (IM) to transform PLC programs written in ST language into different formal models for verification purposes. A tool based on Xtext has been implemented that automatically generates models for the NuSMV and UPPAAL model checkers and the BIP framework

Industry 4.0 in Finland:towards twin transition

Abstract In the global rankings of digitalization and Industry 4.0 maturity, Finland constantly places among the frontrunners. This study examines the path Finland has taken to reach the forefront, the drivers, and the current challenges and future opportunities related to Industry 4.0 and digitalization. This analysis is based on extensive experience in Industry 4.0-related ecosystem projects, policy documentation, and previous research. As Finland focuses on the export of high-value-added products and services, the early adoption of new technologies is vital and thus a key driver. Moreover, the national culture of innovation, R&D, and triple helix collaboration have driven Industry 4.0 implementation alongside a highly skilled workforce. However, multiple barriers hindering full Industry 4.0 utilization still exist, including SMEs’ hesitation to digitalize due to insufficient support mechanisms, an aging population, and the difficulty in finding single-source solutions. Respective future opportunities were found in areas such as smart sustainable manufacturing and ecosystems, enhanced SME involvement, lifelong learning, and the platform economy. Currently, Finland is moving from digitalization towards a twin transition and sustainable ecosystem-to-ecosystem collaboration. Practical early-stage examples of implementing this policy include the AI 4.0 and the Sustainable Industry X supercluster initiatives