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Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), for both idealized model experiments and climate projections of different emissions scenarios. We argue that although this approach was practical to allow parallel development of Earth system model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth system models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy, and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently calculated in integrated assessment models (IAMs) during scenario development with only the net carbon emissions passed to the ESM. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use and projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon–climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular, sources and sinks of methane and nitrous oxide) and process-based representation of carbon removal options. These developments will allow three primary benefits: (1) resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts, (2) scenario modeling of the range of possible future climate states including Earth system processes and feedbacks that are increasingly well-represented in ESMs, and (3) optimal utilization of the strengths of ESMs in the wider context of climate modeling infrastructure (which includes simple climate models, machine learning approaches and kilometer-scale climate models).

Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.

Although often seen as places of culture, cultivation and creativity, language courses borrow the language of creativity for test-centered practices. Research in sociolinguistics and linguistic anthropology has long recognized language courses as sites for the legitimation of neoliberal ideals that emphasize language as global, individual, and economic, human capital for the global market. Yet research in education often focuses on language education as building student identities, ignoring how it prepares students for participation in an affluent 'creative class.' This paper aims to bring a more critical lens on discourses of creativity in the classroom. It explores how neoliberal ideology is realized in teacher development literature on creative management, and it investigates how this commercial creativity affects the language curriculum and assessment in a New England High School, ending with a call to a more critical, communal creativity.

Abstract Background Factors to accurately stratify patients with early-stage non-small cell lung cancer (NSCLC) in different prognostic groups are still needed. This study aims to investigate 1) the prognostic potential of circulating cell-free (CF) and extracellular vesicles (EVs)-derived microRNA (miRNAs), and 2) their added value with respect to known prognostic factors (PFs). Methods The RESTING study is a multicentre prospective observational cohort study on resected stage IA-IIIA patients with NSCLC. The primary end-point was disease-free survival (DFS), and the main analyses were carried out separately for CF- and EV-miRNAs. CF- and EV-miRNAs were isolated from plasma, and miRNA-specific libraries were prepared and sequenced. To reach the study aims, three statistical models were specified: one using the miRNA data only (Model 1); one using both miRNAs and known PFs (age, gender, and pathological stage) (Model 2), and one using the PFs alone (Model 3). Five-fold cross-validation (CV) was used to assess the predictive performance of each. Standard Cox regression and elastic net regularized Cox regression were used. Results A total of 222 patients were enrolled. The median follow-up time was 26.3 (95% CI 25.4–27.6) months. From Model 1, three CF-miRNAs and 21 EV-miRNAs were associated with DFS. In Model 2, two CF-miRNAs (miR-29c-3p and miR-877-3p) and five EV-miRNAs (miR-181a-2-3p, miR-182-5p, miR-192-5p, miR-532-3p and miR-589-5p) remained associated with DFS. From pathway enrichment analysis, TGF-beta and NOTCH were the most involved pathways. Conclusion This study identified promising prognostic CF- and EV-miRNAs that could be used as a non-invasive, cost-effective tool to aid clinical decision-making. However, further evaluation of the obtained miRNAs in an external cohort of patients is warranted.

Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities.

Abstract Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low‐cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low‐cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio‐temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

Tick-borne encephalitis (TBE) is a considerable public health concern caused by the tick-borne encephalitis virus (TBEV), a member of the Flaviviridae family. This virus is classified into 5 genotypes; European, [...]

Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

Abstract Scenarios have been an important integrating element in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) in the understanding of possible climate outcomes, impacts and risks, and mitigation futures. Integration supports a consistent, coherent assessment, new insights and the opportunity to address policy-relevant questions that would not be possible otherwise, for example, which impacts are unavoidable, which are reversible, what is a consistent remaining carbon budget to keep temperatures below a level and what would be a consistent route of action to achieve that goal. The AR6 builds on community frameworks that are developed to support a coherent use of scenarios across the assessment, yet their use in the assessment and the related timelines presented coordination challenges. From lessons within each Working Group (WG) assessment and the cross-WG experience, we present insights into the role of scenarios in future assessments, including the enhanced integration of impacts into scenarios, near-term information and community coordination efforts. Recommendations and opportunities are discussed for how scenarios can support strengthened consistency and policy relevance in the next IPCC assessment cycle.

ABSTRACT Metal oxide nanoparticles (NPs) possess antibacterial activities and can be used for the control of phytopathogenic bacteria. The objective of this work was to evaluate the antibacterial activity of pure and doped NPs against Dickeya zeae, Pantoea ananatis, and Xanthomonas vasicola pv. vasculorum in vitro, and to assess the efficacy of preventive and curative application of zinc oxide (ZnO), nickel oxide (NiO), and silver-doped zinc oxide (ZnO:Ag) NPs for the control of white spot (WS) and bacterial leaf streak (BLS) in vivo. Bacterial growth inhibition was first evaluated by measuring the diameter of the inhibition zone formed in Petri dishes. Subsequently, the severity of WS and BLS diseases was evaluated in a greenhouse calculating the area under the disease progress curve. The in vitro antibacterial activity was not influenced by the increase in the concentration of doping elements for most NPs. ZnO NPs doped with Ag, K, and Mo; ZnOCl doped with Ag, and pure NPs (Ag2O, CuO, and NiO) showed antibacterial activity against D. zeae, P. ananatis, and X. vasicola pv. vasculorum with relatively similar inhibition zones at different concentrations. Commercial copper showed antibacterial activity only against D. zeae. NiO NPs in preventive and curative applications reduced WS and BLS severities, whereas commercial copper application increased WS severity and reduced BLS severity. The use of NPs has promising applications and further evaluation of their formulation, application form, and timing is necessary for new strategies to control the activity of phytopathogenic bacteria.

ABSTRACT Tomato bacterial spot caused by Xanthomonas hortorum pv. gardneri triggers significant losses in crop production, and the active ingredients availability for disease control is limited. For this reason, there is a great demand for plant protection alternatives, such as the use of nanocrystals. Thus, the aim of this work was to evaluate the performance of nanocrystals spraying intervals for the control of tomato bacterial spot. Tomato plants of cv. Santa Cruz Kada were sprayed at 3-4 leaf stage under greenhouse conditions with ZnO:1Mg, ZnOCl, and ZnOCl:0.1Cu nanocrystals, copper and water. Three days later, the plants were inoculated with a bacterial suspension (109 CFU mL -1). Then, after 3, 6, 9, or 12-day intervals, the plants were sprayed with the products. The bacterial spot severity was periodically quantified as affected leaf area percentage, and the area under the disease progress curve was calculated. Nanocrystals ZnO:1Mg, ZnOCl, and ZnOCl:0.1Cu reduced the tomato bacterial spot severity when sprayed at 3- and 6-day intervals. Thus, nanocrystals may be used for the tomato bacterial spot control when sprayed at 6-day intervals, once this interval is adequate and practical for disease management.

ABSTRACT This research presents the state-of-the-art related to the management of conservation units in the State of Espirito Santo, characterizing the conditions for management and infrastructure. The analysis carried out at the units, which were created in 2009, counted on the participation of all sixteen units’ managers, considering factors inherent to the prevention and combat actions impacting the units. Results indicated that ‘Duas Bocas REBIO’ holds the best conditions for management and infrastructure (82%) and ‘RDS Concha D’ostras’, the worst (5%). ‘PARE Itaúnas’ showed the greatest deficit of staff. Regarding the availability of operational equipment, it was possible to observe that 75% of the fully protected units are operationally deficient. As for tools to combat forest fires, ‘PARE Cachoeira da Fumaça’ presented the largest deficit, with no individual protection equipment (IPE). Inadequate infrastructure (14%) and hunting (12%) are the main threats to the units. These results will subsidize the planning and management of protected areas in the State of Espirito Santo.

Abstract Nowadays being resilient is a requirement of all companies and more in general supply chains, as a consequence of the frequent disruptions which repeatedly affect systems and challenge markets from different sides. But how to state whether a company and its related supply chain are resilient or not? To address the present issue, a literature review was carried out on documents proposing quantitative tools or metrics for quantifying the resilience level of an agri-food supply chain, which is a specific field subjected to several threats and accordingly deserving attention. Due to the limited number of documents retrieved (i.e., 26 articles), stressing the gap to be filled in literature, mainly bibliometric analyses were performed on the sample, but contents were also deepened, resuming the different tools available at present. Results reflect the call for the development of models aiming at assessing the resilience of these systems before disruptions and non-controlled events occur; moreover, the industrial level turned out to be neglected, given the fact that all the studies deal with the farm stage (and in general agricultural activities).

RESUMO O objetivo foi analisar a estrutura da paisagem florestal entre duas Unidades de Conservação por meio de índices de ecologia da paisagem. O mapeamento foi obtido por digitalização de aerofoto, utilizando-se técnicas de fotointerpretação na escala 1:2500. No cálculo dos índices, foi utilizada Patch Analyst (ArcGis 9.3). Os fragmentos foram divididos em classes (muito pequeno: 5 e 10 e 100 ha). Foram calculados os índices de área, densidade, tamanho, forma, proximidade, área central (obtidos para diferentes simulações de efeito de borda: 40, 80, 100, 140 m). Encontraram-se 2.652 fragmentos, representando 42,6% de cobertura florestal. Os fragmentos muito pequenos dominam (2.201), seguidos pelos médios (216), pequenos (177) e grandes (58). Houve diferenciações em relação às classes, demonstrando que os maiores apresentam métricas que indicam boa conservação. As classes média e grande indicam a necessidade de criação de políticas públicas que incentivem a formação de corredores ecológicos entre ambas as áreas protegidas.

Solid organ transplant (SOT) candidates and recipients are a fragile population, in which the presence of a pre-transplant disease leading to organ insufficiency and the post-transplant immunosuppressive treatment expose them to an increased risk of infectious diseases. The best intervention to guarantee efficient prevention of infections, with optimal cost–benefit ratio, is represented by vaccination programs; however, the response to vaccines needs that the immune system maintains a good function. This is even more relevant at paediatric age, when specific immunological conditions make transplant candidates and recipients particularly vulnerable. Paediatric patients may be naïve to most infections and may have incomplete immunization status at the time of transplant listing due to their age. Moreover, the unaccomplished development of a mature immune system and the immunosuppressive regimen adopted after transplant might affect the efficacy of post-transplant vaccinations. Therefore, every effort should be made to obtain the widest vaccination coverage before the transplantation, whenever possible. This review reports the most relevant literature, providing information on the current approach to the vaccinations in paediatric SOT candidates and recipients.