Impact of strong disorder on the static magnetic properties of the spin-chain compound BaCu2SiGeO7

The disordered quasi-1D magnet BaCu2SiGeO7 is considered as one of the best physical realizations of the random Heisenberg chain model, which features an irregular distribution of the exchange parameters and whose ground state is predicted to be the scarcely investigated random-singlet state (RSS). Based on extensive 29Si NMR and magnetization studies of BaCu2SiGeO7, combined with numerical Quantum Monte Carlo simulations, we obtain remarkable quantitative agreement with theoretical predictions of the random Heisenberg chain model and strong indications for the formation of a random-singlet state at low temperatures in this compound. As a local probe, NMR is a well-adapted technique for studying the magnetism of disordered systems. In this case it also reveals an additional local transverse staggered field (LTSF), which affects the low-temperature properties of the RSS. The proposed model Hamiltonian satisfactorily accounts for the temperature dependence of the NMR line shapes.Comment: 10 pages, 7 figure

Single-Subject Writing Strategy Instruction: A Meta-Analysis

This meta-analysis reports on single-subject design (SSD) writing strategy instruction research conducted in the 15 years since Rogers and Graham\u27s (2008) meta-analysis on SSD writing instruction. The analysis reviewed 36 studies and aimed to answer four questions: 1) Are writing strategy interventions tested using single-subject methodology effective with students in Grades 1 to 8? (2) Is writing strategy instruction more effective for some grades than others? (3) Is writing strategy instruction more beneficial for specific samples of students? (4) Do studies deemed higher quality based on What Works Clearinghouse (2022) (WWC) indicators have more or less overlap than those deemed lower quality? Results showed that students benefited from writing strategy instruction, making significant gains in holistic text quality, number of genre elements and word count. When comparing the effectiveness across grade levels, writing strategy instruction was highly effective in improving holistic text quality of students in grades 5-8 and moderately effective for students in grades 1-4. When exploring the effectiveness with various student samples, writing strategy instruction was highly effective in improving holistic text quality for emotional behavioural disorders/suspected emotional behavioural disorders and autism spectrum disorder groups but moderately effective for the learning disabilities/struggling writers\u27 group. Visual analysis results revealed low to moderate study validity. Although study quality was poor to acceptable and should be improved, the effectiveness of writing strategy instruction did not differ significantly between low and higher quality studies

Toward the automation of threat modeling and risk assessment in IoT systems

The Internet of Things (IoT) has recently become one of the most relevant emerging technologies in the IT landscape. IoT systems are characterized by the high heterogeneity of involved architectural components (e.g., device platforms, services, networks, architectures) and involve a multiplicity of application domains. In the IoT scenario, the identification of specific security requirements and the security design are very complex and expensive tasks, since they heavily depend on the configuration deployment actually in place and require security experts. In order to overcome these issues, we propose an approach aimed at supporting the security analysis of an IoT system by means of an almost completely automated process for threat modeling and risk assessment, which also helps identify the security controls to implement in order to mitigate existing security risks. We demonstrate the effectiveness of the approach by discussing its application to a home automation system, built on top of commercial IoT products

Toward automated threat modeling of edge computing systems

Edge computing brings processing and storage capabilities closer to the data sources, to reduce network latency, save bandwidth, and preserve data locality. Despite the clear benefits, this paradigm brings unprecedented cyber risks due to the combination of the security issues and challenges typical of cloud and Internet of Things (IoT) worlds. Notwithstanding an increasing interest in edge security by academic and industrial communities, there is still no discernible industry consensus on edge computing security best practices, and activities like threat analysis and countermeasure selection are still not well established and are completely left to security experts.In order to cope with the need for a simplified yet effective threat modeling process, which is affordable in presence of limited security skills and economic resources, and viable in modern development approaches, in this paper, we propose an automated threat modeling and countermeasure selection strategy targeting edge computing systems. Our approach leverages a comprehensive system model able to describe the main involved architectural elements and the associated data flow, with a focus on the specific properties that may actually impact on the applicability of threats and of associated countermeasures

Control and Local Measurement of the Spin Chemical Potential in a Magnetic Insulator

The spin chemical potential characterizes the tendency of spins to diffuse. Probing the spin chemical potential could provide insight into materials such as magnetic insulators and spin liquids and aid optimization of spintronic devices. Here, we introduce single-spin magnetometry as a generic platform for non-perturbative, nanoscale characterization of spin chemical potentials. We use this platform to investigate magnons in a magnetic insulator, surprisingly finding that the magnon chemical potential can be efficiently controlled by driving the system's ferromagnetic resonance. We introduce a symmetry-based two-fluid theory describing the underlying magnon processes, realize the first experimental determination of the local thermomagnonic torque, and illustrate the detection sensitivity using electrically controlled spin injection. Our results open the way for nanoscale control and imaging of spin transport in mesoscopic spin systems.Comment: 18 pages, 4 figure

Human Metapneumovirus Glycoprotein G Inhibits Innate Immune Responses

Human metapneumovirus (hMPV) is a leading cause of acute respiratory tract infection in infants, as well as in the elderly and immunocompromised patients. No effective treatment or vaccine for hMPV is currently available. A recombinant hMPV lacking the G protein (rhMPV-ΔG) was recently developed as a potential vaccine candidate and shown to be attenuated in the respiratory tract of a rodent model of infection. The mechanism of its attenuation, as well as the role of G protein in modulation of hMPV-induced cellular responses in vitro, as well as in vivo, is currently unknown. In this study, we found that rhMPV-ΔG-infected airway epithelial cells produced higher levels of chemokines and type I interferon (IFN) compared to cells infected with rhMPV-WT. Infection of airway epithelial cells with rhMPV-ΔG enhanced activation of transcription factors belonging to the nuclear factor (NF)-κB and interferon regulatory factor (IRF) families, as revealed by increased nuclear translocation and/or phosphorylation of these transcription factors. Compared to rhMPV-WT, rhMPV-ΔG also increased IRF- and NF-κB-dependent gene transcription, which was reversely inhibited by G protein expression. Since RNA helicases have been shown to play a fundamental role in initiating viral-induced cellular signaling, we investigated whether retinoic induced gene (RIG)-I was the target of G protein inhibitory activity. We found that indeed G protein associated with RIG-I and inhibited RIG-I-dependent gene transcription, identifying an important mechanism by which hMPV affects innate immune responses. This is the first study investigating the role of hMPV G protein in cellular signaling and identifies G as an important virulence factor, as it inhibits the production of important immune and antiviral mediators by targeting RIG-I, a major intracellular viral RNA sensor

Two Coupled Chains are Simpler than One: Field-induced Chirality in a Frustrated Quantum Spin Ladder

Although the frustrated spin chain (zigzag chain) is a Drosophila of frustrated magnetism, the understanding of a pair of coupled zigzag chains (frustrated spin ladder) in a magnetic field is incomplete. We address this problem through nuclear magnetic resonance (NMR) experiments on $\text{BiCu}_2\text{PO}_6$ in magnetic fields up to 45 T, revealing a field-induced spiral magnetic structure. Conjointly, we present advanced numerical calculations showing that even moderate rung coupling dramatically simplifies the phase diagram below half-saturation magnetization by stabilizing a field-induced chiral phase. Surprisingly for a one-dimensional model, this phase and its response to Dzyaloshinskii-Moriya (DM) interactions adhere to classical expectations. While explaining the behavior at the highest accessible magnetic fields, our results imply a different origin for the solitonic phases occurring at lower fields in $\text{BiCu}_2\text{PO}_6$. An exciting possibility is that the known, DM-mediated coupling between chirality and crystal lattice gives rise to a new kind of spin-Peierls instability.Comment: Revised manuscript, 7 pages, 6 figure