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Neuroimaging studies have demonstrated gray matter (GM) volume abnormalities in substance users. While the majority of substance users are polysubstance users, very little is known about the relation between GM volume abnormalities and polysubstance use.In this study we assessed the relation between GM volume, and the use of alcohol, tobacco, cocaine and cannabis as well as the total number of substances used, in a sample of 169 males: 15 non-substance users, 89 moderate drinkers, 27 moderate drinkers who also smoke tobacco, 13 moderate drinkers who also smoke tobacco and use cocaine, 10 heavy drinkers who smoke tobacco and use cocaine and 15 heavy drinkers who smoke tobacco, cannabis and use cocaine.Regression analyses showed that there was a negative relation between the number of substances used and volume of the dorsal medial prefrontal cortex (mPFC) and the ventral mPFC. Without controlling for the use of other substances, the volume of the dorsal mPFC was negatively associated with the use of alcohol, tobacco, and cocaine. After controlling for the use of other substances, a negative relation was found between tobacco and cocaine and volume of the thalami and ventrolateral PFC, respectively.These findings indicate that mPFC alterations may not be substance-specific, but rather related to the number of substances used, whereas, thalamic and ventrolateral PFC pathology is specifically associated with tobacco and cocaine use, respectively. These findings are important, as the differential alterations in GM volume may underlie different cognitive deficits associated with substance use disorders.

Global mitigation pathways play a critical role in informing climate policies and targets that are in line with international climate goals. However, it is not possible to directly compare modelled results with national inventories used to assess progress under the UNFCCC due to differences in how land-based fluxes are accounted for.National inventories consider carbon flux on managed land using an area-based approach with managed land-areas determined by nations. Emissions scenarios consider a different managed land area and are calibrated against data from detailed global carbon cycle models that account for natural (indirect) and anthropogenic (direct) fluxes separately by design. To disentangle the direct and indirect components of land-based carbon fluxes, we use a reduced complexity climate model with explicit treatment of the land-use sector, OSCAR, one of the models used by the Global Carbon Project. We find the discrepancy between model and NGHGI-based accounting methods globally to be 4.4 ± 1.0 Gt CO2 yr-1 averaged over the 2000-2020 time period, which is in line with existing estimates. We then apply OSCAR to the set of pathways assessed by the IPCC to quantify how this gap evolves over time and estimate how key mitigation benchmarks change.Across both 1.5°C and 2°C scenarios, LULUCF emissions pathways aligned with NGHGI accounting practices show a strong increase in the total land sink until around mid-century. However, the ‘NGHGI alignment gap’  decreases over this period, converging in the 2050-2060s for 1.5°C scenarios and 2070s-2080s for 2°C scenarios. The convergence is primarily a result of the simulated stabilization and then decrease of the CO2-fertilization effect as well as background climate warming reducing the overall effectiveness of the land sink, which in turn reduces the indirect removals considered by NGHGIs. These dynamics lead to land-based emissions reversing their downward trend in most NGHGI-aligned scenarios by mid-century, and result in the LULUCF sector becoming a net-source of emissions by 2100 in about 25% of both 1.5°C and 2°C scenarios.Assessing emission pathways using LULUCF definitions from national inventory accounting results in downward revisions to emissions benchmarks derived from scenarios. NGHGI-aligned pathways result in earlier net-zero CO2 emissions by around 2-5 years for both 1.5°C and 2°C scenarios, and 2030 emission reductions relative to 2020 are enhanced by about 5 percentage points for both pathway categories. When incorporating the additional land removals considered by NGHGIs, the assessed cumulative net CO2 emissions to global net-zero CO2 also decreases systematically by 15-18% for both 1.5°C and 2°C scenarios.We find that increasing removals from direct fluxes in 1.5C scenarios overtake estimated removals using NGHGI conventions in the near term. However, by midcentury, the strengthening of direct removals is balanced by weakening of indirect removals, meaning that, on average, carbon removal on land accounted for using NGHGI conventions in 1.5C scenarios results in about half of the LULUCF removals in current policy scenarios. We discuss the implications of our results for future Global Stocktakes and market mechanisms under the Paris Agreement.

AbstractMultinational conservation initiatives that prioritize investment across a region invariably navigate trade-offs among multiple objectives. It seems logical to focus where several objectives can be achieved efficiently, but such multi-objective hotspots may be ecologically inappropriate, or politically inequitable. Here we devise a framework to facilitate a regionally cohesive set of marine-protected areas driven by national preferences and supported by quantitative conservation prioritization analyses, and illustrate it using the Coral Triangle Initiative. We identify areas important for achieving six objectives to address ecosystem representation, threatened fauna, connectivity and climate change. We expose trade-offs between areas that contribute substantially to several objectives and those meeting one or two objectives extremely well. Hence there are two strategies to guide countries choosing to implement regional goals nationally: multi-objective hotspots and complementary sets of single-objective priorities. This novel framework is applicable to any multilateral or global initiative seeking to apply quantitative information in decision making.

<p>To understand how global warming can be kept well-below 2°C and even 1.5°C, climate policy uses scenarios that describe how society could transform in order to reduce its greenhouse gas emissions. Such scenario are typically created with integrated assessment models that include a representation of the economy, and the energy, land-use, and industrial system. However, current climate change scenarios have a key weakness in that they typically focus on reaching specific climate goals in 2100 only. <br><br>This choice results in risky pathways that delay action and seemingly inevitably rely on large quantities of carbon-dioxide removal after mid-century. Here we propose a framework that more closely reflects the intentions of the UN Paris Agreement. It focusses on reaching a peak in global warming with either stabilisation or reversal thereafter. This approach provides a critical extension of the widely used Shared Socioecononomic Pathways (SSP) framework and reveals a more diverse picture: an inevitable transition period of aggressive near-term climate action to reach carbon neutrality can be followed by a variety of long-term states. It allows policymakers to explicitly consider near-term climate strategies in the context of intergenerational equity and long-term sustainability.</p>

Countries around the world suffer the dramatic impact of earthquakes and other natural hazards reflected in casualties, infrastructure damage, service interruptions, and recovery costs. Although disaster exposure consciousness of electric power systems has increased in recent years, mitigation and adaptation actions, such as reserve scheduling and infrastructure investments, are usually performed without quantitative tools to account for the underlying stochasticity of these events. This article first discusses why an integrated assessment, which incorporates sources of uncertainty (risk) and manages the time-dependency of the recovery process (resilience), should be used to assess the impact of seismic events on electric power systems. Thereafter, a probabilistic methodology that considers the hazard, vulnerability, operation, and recovery of the system is presented. As a case study, the probabilistic seismic resilience of the electric power system of Northern Chile is assessed using different risk measures, including expected annual loss, value at risk, and conditional value-at-risk. Finally, a novel criticality assessment based on these metrics is developed to demonstrate that, for certain networks such as the study case, retrofit of selective components can notably improve the resilience of the complete system to seismic events. For example, if one specific component from the 152 components of the study system is assumed invulnerable, expected annual interruption costs decrease by 8%.

Background: The Skills for Life Adjustment and Resilience (SOLAR) programme is a brief, scalable, psychosocial skill-building programme designed to reduce distress and adjustment difficulties following disaster. Objectives: We tested the feasibility, acceptability, efficacy and safety of a culturally adapted version of SOLAR in two remote, cyclone-affected communities in the Pacific Island nation of Tuvalu. Method: This pilot adopted a quasi-experimental, control design involving 99 participants. SOLAR was administered to the treatment group (n = 49) by local, non-specialist facilitators (i.e. ‘Coaches’) in a massed, group format across 5 consecutive days. The control group (n = 50) had access to Usual Care (UC). We compared group differences (post-intervention vs. post-control) with psychological distress being the primary outcome. We also examined whether changes were maintained at 6-month follow-up. Results: Large, statistically significant group differences in psychological distress were observed after controlling for baseline scores in favour of the SOLAR group. Mean group outcomes were consistently lower at 6-month follow-up than at baseline. SOLAR was found to be acceptable and safe, and programme feedback from participants and Coaches was overwhelmingly positive. Conclusions: Findings contribute to emerging evidence that SOLAR is a flexible, culturally adaptable and scalable intervention that can support individual recovery and adjustment in the aftermath of disaster. RCTs to strengthen evidence of SOLAR’s efficacy are warranted. We report findings from the first control trial of SOLAR, a post-trauma, psychosocial intervention.SOLAR proved feasible, acceptable, safe, and effective relative to Usual Care when delivered using task-sharing to residents of the Small Island Developing State of Tuvalu. We report findings from the first control trial of SOLAR, a post-trauma, psychosocial intervention. SOLAR proved feasible, acceptable, safe, and effective relative to Usual Care when delivered using task-sharing to residents of the Small Island Developing State of Tuvalu.

AbstractThe increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real‐time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience‐based decisions for risk mitigation. The IEEE 24‐bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.