Effects of long-term wetland variations on flood risk assessments in the Yangtze River Basin

Flooding is the most frequent natural disaster in the Yangtze River Basin (YRB), causing significant socio-economic damages. In recent decades, abundant wetland resources in the YRB have experienced substantial changes and played a significant role in strengthening the hydrological resilience to flood risks. However, wetland-related approaches remain underdeveloped for mitigating flood risks in the YRB due to the lack of considering long-term wetland effects in the flood risk assessment. Therefore, this study develops an wetland-related GIS-based spatial multi-index flood risk assessment model by incorporating the effects of wetland variations, to investigate the long-term implications of wetland variations on flood risks, to identify dominant flood risk indicators under wetland effects, and to provide wetland-related flood risk management suggestions. These findings indicate that wetlands in the Taihu Lake Basin, Wanjiang Plain, Poyang Lake Basin, and Dongting and Honghu Lake Basin could enhance flood control capacity and reduce flood risks in most years between 1985 and 2021 except years with extreme flood disasters. Wetlands in the Sichuan Basin have aggravated but limited impacts on flood risks. Precipitation in the Taihu Lake Basin and Poyang Lake Basin, runoff and vegetation cover in the Wanjiang Plain, GDP in the Taihu Lake Basin, population density in the Taihu lake Basin, Dongting and Honghu Lake Basin, and the Sichuan Basin are dominant flood risk indicators under wetland effects. Reasonably managing wetlands, maximizing stormwater storage capacity, increasing vegetation coverage in urbanized and precipitated regions are feasible suggestions for developing wetland-related flood resilience strategies in the YRB

Cyber resilience quantification: a probabilistic estimation model for IT infrastructure

In today’s digital landscape, ensuring IT infrastructure resilience against increasingly frequent and sophisticated cyber-attacks is a critical priority. Cyber resilience is the ability of a system or organisation to anticipate and recover from cyber-attacks. Effective cyber resilience quantification enables systematic analysis and comparison of IT infrastructures. Cyber resilience involves resisting and recovering from cyber-attacks. Cyber resilience refers to the ability of a system to absorb, recover from, and adapt to cyber-attacks. However, existing approaches often fail to integrate dynamic probabilistic assessment methods that capture resilience fluctuations over time. This study introduces the Probabilistic Estimation-based Quantification Model for Cyber Resilience (PEQCRM), a novel framework that enhances cyber resilience measurement and strategic decision-making. The proposed model incorporates Resilience Curves (RC) and the Area Under the Curve (AUC) methodology to quantify resilience over attack and recovery phases. Additionally, it expands traditional resilience assessment by integrating cyber resilience strategies as key influencing factors. The PEQCRM model is evaluated through extensive simulations to assess its effectiveness in real-world cybersecurity scenarios. Findings reveal that different resilience strategies exhibit varying adoption, absorption, and recovery effectiveness levels. This study evaluates the extent to which a strategy can mitigate initial attack impact and adoption for the extent to which organisations implement and sustain strategy levels of four different cyber resilience strategies. Specifically, the pre-configuration strategy demonstrates the highest level of preparedness and adoption, while the buffering-supported strategy has the lowest absorption level. The managing complexity strategy achieves the highest absorption level, whereas the mesh topology strategy exhibits strong recovery capabilities and adoption rates

LGBTQ+ theatre from the 80s to the end of the millennium

No abstract available

La ‘longa aetas’ del poeta di Sulmona: tipologie femminili ovidiane negli Epigrammi di Decimo Magno Ausonio

No abstract available

The Social Dinosaur

No abstract available

Reducing hyper mirroring in misophonia: a proposal for cortico-cortical paired associative stimulation (ccPAS) as a potential intervention for treatment

Misophonia, a condition characterized by intense emotional and physiological reactions to specific human-generated sounds, was recently proposed as a disorder of hyper mirroring, in which there is an over-representation of the actions of others. A recent study used rTMS to indirectly reduce the hyperactivity in the anterior insula of people with misophonia, leading to a modest reduction in misophonic distress. But further research is needed to optimize TMS for greater efficacy. Recent TMS studies using a paired associative approach have shown that it could be used to reduce automatic mirroring in healthy controls. We propose the use of ccPAS for reducing the aberrant “hyper” connectivity of the motor cortex, suggested to be associated with mirroring, found in misophonia which is directly accessible to TMS. We hope this theoretically driven neuromodulation approach can take advantage of recent advances in brain stimulation and address the need for developing an effective evidence-based treatment for misophonia

AI & The Paradox of Agency

International group exhibition including new commissions and accompanying catalogue curated by Cook, Bildmuseet, Umea, Sweden, opening March 13 2026. Supported by Umeå University, UmArts, WASP-HS and the Jacob Wallenberg Fun