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Psychosocial impacts of a mouse plague and ongoing psychological stress
Abstract In 2020-21, parts of eastern Australia experienced a severe mouse plague, estimated to have caused up to AUD$1 billion worth of damage. Yet, the mental health impacts of such a pest plague are not empirically known. The present study sought to quantify and model the psychosocial impacts of the 2021 mouse plague and measure ongoing psychological stress two years post-plague, to provide insights into social impacts and mental wellbeing during a significant biosecurity incursion. An online survey ( N = 1,691) measured key psychosocial impact metrics included psychological traits, emotional states (depression, disgust, embarrassment), perceptions of social impacts (response costs, attitudes), support (social, government), and perceived threat of future plague. A partially mediated path model accounted for 74% of variability observed in perceived severity of impacts and ongoing psychological stress. Severity of impacts was predominantly influenced by perceived response costs , negative mood states (i.e. depression ) and disgust elicited by the odour of mice. The most influential direct predictors of ongoing psychological stress were depressive symptoms at the time of the plague, and concerns that a future mouse plague would be dangerous or catastrophic to oneself. This study provides empirical insights into both acute social impacts during a significant pest incursion, as well as ongoing psychological stress. Social impacts are rarely measured or modelled; yet these factors are critically important in understanding the effect of severe pest incursions on communities whose livelihoods often depend on the agricultural sector.
Gold-polymer hybrid metasurface for polarization-independent enhanced third harmonic generation in the ultraviolet
Optimal electric vehicle charging stations and distributed generation placement by partitioning the distribution network using the modified newman fast algorithm
Abstract This article introduces a novel and numerically validated framework for the well-optimized placement and capacity selection of Distributed Generation (DG) units and Electric Vehicle Charging Stations (EV-CSs) in power distribution networks (PDNs). The methodology employs a Modified Newman Fast Algorithm (NFA) enhanced with Electrical Coupling Strength (ECS) to partition the network into electrically cohesive Virtual Microgrids (VMs). Within each VM, resources are optimally allocated using two recent metaheuristic techniques: the Starfish Optimization (SFO) and the Puma Optimization (PO) methods and compared against the conventional Particle Swarm Optimization (PSO) approach. Each approach is executed for 500 iterations with 30 search agents. The discussed framework is tested on the IEEE 33-bus and IEEE 118-bus PDNs. For the 33-bus PDN, the approach minimized active power losses by approximately 82%, improved the lowest bus voltage magnitude from 0.8361 p.u to 0.979 p.u, and increased the Stability Index (SI) from 0.6256 p.u to 0.927 p.u. For the 118-bus network, real-power losses were decreased by 68–69%, with notable enhancements in both voltage profile and SI. Additionally, PO demonstrated the fastest convergence speed among the tested algorithms, confirming its suitability for large-scale optimization. The study results demonstrate the effectiveness of the presented VM-based co-allocation strategy in enhancing power system performance and scalability, with future work focusing on cost-aware multi-objective optimization and real-world deployment in Egyptian PDNs.
Drone-based composite risk mapping reveals vegetation–shade interaction and housing typology as key determinants of Aedes habitat risk
Aeroponic root leachate (ARL)-induced hatching as a sustainable strategy for the management of Globodera rostochiensis in potato (Solanum tuberosum L.)
Two-component dynamics in supercritical $$\text {CO}_2$$ from inelastic X-ray scattering
Deep learning-based detection of retinal detachment with vitreous hemorrhage in ocular ultrasound images
Validation of chemoresistance phenotypes in pleural mesothelioma across 2D, 3D, and in vivo models
A Bayesian perspective on geographic influences in coach decision-making for athlete identification and selection
Influence of SNVs on adverse reactions and survival in gefitinib-treated lung cancer patients from a preliminary study
Climate action and responsible consumption and production in high-income countries
Structural and functional foetal renal abnormalities as a mechanism of oligohydramnios in a guinea pig model of growth restriction
Assessing the cytotoxicity and apoptosis-inducing ability of solar irradiated Salmonella Typhimurium in the RAW264.7 cell line in vitro
Combination of artesunate and ruxolitinib suppresses T cell leukemia/lymphoma proliferation via the JAK STAT pathway
Abstract T-cell lymphoblastic leukemia/lymphoma is a highly aggressive malignancy with a 5-year overall survival rate of 35%. Mutations in the JAK/STAT pathway are the second most common mutations in T-cell lymphoblastic leukemia/lymphoma, and hyperactivation of this pathway can promote proliferation of tumor cells. Considering that artesunate and ruxolitinib can inhibit activation of the JAK/STAT pathway, this study investigated the value of these drugs in the treatment of T-lymphoblastic leukemia/lymphoma. Jurkat cells were treated with various concentrations of artesunate and/or ruxolitinib. Cell viability was detected using the CCK-8 assay, and apoptosis was detected after 48 h of treatment using flow cytometry. The effect of each drug alone and in combination was analyzed by polymerase chain reaction and western blotting assays. We also investigated the expression of relevant proteins in the JAK/STAT pathway in lymph nodes and bone marrow samples from 10 patients with T-lymphoblastic leukemia/lymphoma and two healthy controls. Artesunate and ruxolitinib, both alone and in combination, promoted apoptosis and reduced phosphorylation of JAK2 and STAT5 but did not alter mRNA or protein expression of JAK2. The drugs had a stronger inhibitory effect on growth when used in combination than when either was administered alone. Cytotoxicity assays indicated that artesunate had a potent inhibitory effect on cell viability, with IC 50 values of 12.86 (24 h) and 5.412 µM (48 h), whereas ruxolitinib had weaker activity (with an IC 50 of 30.55 µM at 24 h and 15.51 µM at 48 h). At 24 h, the total apoptotic rate was 20.75% in the control group, 30.00% in the 20 µM artesunate group, 27.24% in the 30 µM ruxolitinib group, and 43.39% in the combination group. Artesunate and ruxolitinib alone and in combination inhibited aberrant activation of the JAK/STAT pathway in T-lymphoblastic lymphoma/leukemia, supporting the value of this combination in patients with JAK/STAT protein mutations.
No-rank tensor decomposition via metric learning
Discovery of potential antiviral compounds and accelerating the therapeutic discovery against monkeypox virus
Multi-sensor monitoring of a transient event in the Gran Sasso aquifer, Italy
Abstract A novel approach in monitoring the inner dynamics of mountains, massifs, and of the Earth crust in general, involves hydrogeological measurements, as well as new generation multi-component seismic stations. Several hydrogeological stations monitor the water parameters of the large Gran Sasso aquifer. This is especially important when the instrumentation used has a high sensitivity and is able to access frequencies below 1 mHz, opening the possibility of observing very slow signals of local origin. For several years, the ring laser gyroscope GINGERINO is operative inside the underground Gran Sasso laboratory ( LNGS-INFN ), and monitors the local Earth angular velocity around the vertical axis. Together with the co-located GIGS broadband seismometer (seismic stations of national network of INGV ), it constitutes a 4C seismic station; the 4 degrees of freedom put together give insight into the inner movements of the Gran Sasso massif, that find correspondence in measurements conducted on the groundwater of the aquifer. In particular, the hydrogeological interpretation of the slow dynamics of the period since May to August 2023, and of the powerful mountain bang event of August 14 is consistent with data from GINGERINO . The final large bang event was also detected by the GIGS broadband seismic station and accelerometer station of RAN (National Accelerometer Network of Civil Protection Department). Furthermore, in the underground laboratories the bang event was recorded by an acoustic sensor and the groundwater hydraulic pressure monitor shows an anomaly exactly when the bang event occurred. Finally, the monitoring data of the groundwater at the boundary of the Gran Sasso aquifer also reveal anomalies linked to the bang event.