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Simulation models of multi‐sector systems are increasingly used to understand societal resilience to climate and economic shocks and change. However, multi‐sector systems are also subject to numerous uncertainties that prevent the direct application of simulation models for prediction and planning, particularly when extrapolating past behavior to a nonstationary future. Recent studies have developed a combination of methods to characterize, attribute, and quantify these uncertainties for both single‐ and multi‐sector systems. Here, we review challenges and complications to the idealized goal of fully quantifying all uncertainties in a multi‐sector model and their interactions with policy design as they emerge at different stages of analysis: (a) inference and model calibration; (b) projecting future outcomes; and (c) scenario discovery and identification of risk regimes. We also identify potential methods and research opportunities to help navigate the tradeoffs inherent in uncertainty analyses for complex systems. During this discussion, we provide a classification of uncertainty types and discuss model coupling frameworks to support interdisciplinary collaboration on multi‐sector dynamics (MSD) research. Finally, we conclude with recommendations for best practices to ensure that MSD research can be properly contextualized with respect to the underlying uncertainties. Key Points Uncertainty is an inherent part of multi‐sector systems analysis Approaches to addressing uncertainty involve deliberate tradeoffs Best practices involve standardizing communication and improving transparency

Rice sheath blight disease, caused by the basidiomycetous necrotroph Rhizoctonia solani, became one of the major threats to the rice cultivation worldwide, especially after the adoption of high-yielding varieties. The pathogen is challenging to manage because of its extensively broad host range and high genetic variability and also due to the inability to find any satisfactory level of natural resistance from the available rice germplasm. It is high time to find remedies to combat the pathogen for reducing rice yield losses and subsequently to minimize the threat to global food security. The development of genetic resistance is one of the alternative means to avoid the use of hazardous chemical fungicides. This review mainly focuses on the effort of better understanding the host–pathogen relationship, finding the gene loci/markers imparting resistance response and modifying the host genome through transgenic development. The latest development and trend in the R. solani–rice pathosystem research with gap analysis are provided.

The three-dimensional (3D) documentation and surveying of cultural heritage can be carried out following several geomatics techniques such as laser scanning and thermography in order to detect the original 3D shape after applying reverse engineering solutions. In almost all cases, the integration of data collected by different instruments is needed to achieve a successful and comprehensive 3D model of the as-built architectural shape of the historical building. This paper describes the operations carried out by the authors to determine the as-built 3D model of the Escuelas Pias Church, related namely to the dome and circular nave. After the description of the church and historical notes, attention will be driven to the indirect registration results obtained with three different laser scanning software packages, highlighting similarities and differences, and the consequences while generating meshes. The 3D model carried out will then be described and the results of some investigations with regard to the hypotheses about the design of the dome and the origin of the alterations will be presented.

Women are more likely to use alcohol as a coping strategy for psychological distress, with higher rates of comorbidity with depression being found in those with an alcohol use disorder. The objective of this study was to analyze changes in problematic alcohol consumption and depression during the COVID-19 lockdown, and to establish a predictive model based on age. A total of 1889 women aged 18–64 years ( M  = 36.14) participated. The Patient Health Questionnaire was applied for depression, the Alcohol Use Disorders Identification Test–Short Version for alcohol, and active and avoidant coping were considered. In the period prior to the pandemic, depression and avoidant coping were good predictors of alcohol consumption in women, regardless of age. During lockdown, this predictive capacity was only maintained in women aged 35–64 years. In the mediational models, differences were observed according to age. For women aged 18–34 years, depression was the predictor variable of problematic alcohol consumption, but for women aged 35–64 years it was the avoidant coping style, which is the predominant style in women of this age with clinical depression. The relevance of age in the combined treatments of depression and problematic alcohol consumption is highlighted, and training in active coping strategies is suggested.

Haplotype-based breeding, a recent promising breeding approach to develop tailor-made crop varieties, deals with identification of superior haplotypes and their deployment in breeding programmes. In this context, whole genome re-sequencing data of 292 genotypes from pigeonpea reference set were mined to identify the superior haplotypes for 10 droughtresponsive candidate genes. A total of 83, 132 and 60 haplotypes were identified in breeding lines, landraces and wild species, respectively. Candidate gene-based association analysis of these 10 genes on a subset of 137 accessions of the pigeonpea reference set revealed 23 strong marker-trait associations (MTAs) in five genes influencing seven drought-responsive component traits. Haplo-pheno analysis for the strongly associated genes resulted in the identification of most promising haplotypes for three genes regulating five component drought traits. The haplotype C. cajan_23080-H2 for plant weight (PW), fresh weight (FW) and turgid weight (TW), the haplotype C. cajan_30211-H6 for PW, FW, TW and dry weight (DW), the haplotype C. cajan_26230-H11 for FW and DW and the haplotype C. cajan_26230-H5 for relative water content (RWC) were identified as superior haplotypes under drought stress condition. Furthermore, 17 accessions containing superior haplotypes for three drought-responsive genes were identified. The identified superior haplotypes and the accessions carrying these superior haplotypes will be very useful for deploying haplotype-based breeding to develop nextgeneration tailor-made better drought-responsive pigeonpea cultivars.

Background: Restoration of fertility (Rf) is an important trait for pigeonpea hybrid breeding. Few coarse quantitative trait locus (QTL) studies conducted in the past identified QTLs with large confidence intervals on the genetic map and could not provide any information on possible genes responsible for Rf in pigeonpea. Therefore, a larger population comprising of 369 F2s derived from ICPA 2039 × ICPL 87119 was genotyped with high density Axiom Cajanus SNP Array with 56 K single nucleotide polymorphism (SNPs) for high resolution mapping of Rf. Results: A genetic map with 4867 markers was developed and a total of four QTLs for Rf were identified. While one major effect QTL (qRf8.1) was co-localized with the QTL identified in two previous studies and its size was refined from 1.2 Mb to 0.41 Mb. Further analysis of qRf8.1 QTL with genome sequence provided 20 genes including two genes namely flowering locus protein T and 2-oxoglutarate/Fe (II)-dependent dioxygenases (2-ODDs) superfamily protein with known function in the restoration of fertility. Conclusion: The qRf8.1 QTL and the potential candidate genes present in this QTL will be valuable for genomicsassisted breeding and identification of causal genes/nucleotides for the restoration of fertility in the hybrid breeding program of pigeonpea.

Genetic diversity studies provide important details on target trait availability and its variability, for the success of breeding programs. In this study, GBS approach was used to reveal a new structuration of genetic diversity and population structure of pigeonpea in Benin. We used a total of 688 high-quality Single Nucleotide Polymorphism markers for a total of 44 pigeonpea genotypes. The distribution of SNP markers on the 11 chromosomes ranged from 14 on chromosome 5 to 133 on chromosome 2. The Polymorphism Information Content and gene diversity values were 0.30 and 0.34 respectively. The analysis of population structure revealed four clear subpopulations. The Weighted Neighbor Joining tree agreed with structure analyses by grouping the 44 genotypes into four clusters. The PCoA revealed that genotypes from subpopulations 1, 2 and 3 intermixed among themselves. The Analysis of Molecular Variance showed 7% of the total variation among genotypes while the rest of variation (93%) was within genotypes from subpopulations indicating a high gene exchange (Nm = 7.13) and low genetic differentiation (PhiPT = 0.07) between subpopulations. Subpopulation 2 presented the highest mean values of number of different alleles (Na = 1.57), number of loci with private alleles (Pa = 0.11) and the percentage of polymorphic loci (P = 57.12%). We discuss our findings and demonstrate how the genetic diversity and the population structure of this specie can be used through the Genome Wide Association Studies and Marker-Assisted Selection to enhance genetic gain in pigeonpea breeding programs in Benin.

The photoluminescence emission around 1.9 eV, excited from the ultraviolet to vacuum ultraviolet was investigated in neutron irradiated silica (at 1021 and 1022 n/m2 fluences) with different OH and impurity content: KU1 and KS-4V high purity silica and Infrasil 301. The measurements were made at different temperatures from 300K to 10K. The three irradiated silica grades show similar excitation spectra shape, although the band intensities are different depending on silica grade and temperature. Neutron irradiated KU1, with the highest OH content, shows the highest red emission attributed to nonbridging oxygen hole centers (NBOHCs). The excitation profile, from 4.0 to 8.8 eV, has two bands, which are centered around 4.85 eV and 6.5 eV. The band intensities increase with decreasing temperature from 300 to 10K for the three types of silica.

Fused silica is a material of interest due to its increasing number of applications in many different technology fields. In thermonuclear fusion it is one of candidate materials for both final focusing optics of lasers for NIF and future inertial fusion reactors and diagnostics of the Safety and Control Systems of the ITER machine as well as DEMO magnetic fusion reactors. In operation, these materials will be exposed to high neutron irradiation fluxes and it can result in point defect. Materials properties of interest (optical absorption, radioluminescence, mechanical properties,…) are closely related to the presence of defects. These defects can be generated directly by irradiation or by the presence of impurities in the material. We present molecular dynamic simulation of displacement cascade due to energetic recoils in amorphous silica without hydrogen atoms and with 1% of hydrogen atoms trying to identify defects formation and we present molecular dynamics simulations to study the effects of hydrogen atoms in this material and their interaction with defects; The diffusion coefficients and mechanisms of H mobility in fused silica has been calculated and compared with those existing in the literature. The interatomic potential developed by Feuston and Garofallini has been used in both studies.

The social-ecological systems paradigm emerged as an alternative to traditional approaches to natural resources management, bringing together a complex systems approach rooted in multi-equilibrium ecology that emphasizes managing feedbacks and transformations, a recognition of the intertwined nature of social and environmental dynamics, and a focus on institutions as a means of addressing collective action problems. However, despite the promise of this paradigm in integrating the social and natural sciences of natural resources management and governance, insights and methods from the complexity sciences have yet to be fully harnessed in understanding the social-ecological dynamics of natural resources, while social-ecological systems models tend to fall short in capturing the aspects of human systems that are distinct from ecological systems; namely, self-organization, heterogeneity, and subjectivity. This dissertation develops dynamical systems modeling approaches that address this gap in exploring how these dynamics shape system responses to change and differentiated outcomes. The first chapter develops a dynamical systems model of communities that are economically dependent on natural resource exploitation (e.g. mining, logging, and industrial agriculture communities) that links resource dynamics, migration, and community wellbeing. The results reveal an inevitable misalignment between policies that support a higher quality of life for communities and those that ensure resilience of the industry, and the temporal dynamics of this misalignment. To explore how the structure of resource governance shapes its function, Chapter 2 uses a generalized version of dynamical systems modeling to develop a modeling approach for linking system aspects, such as diversity, heterogeneity, and connectivity, correspond to stability. The results reveal that greater complexity – greater diversity of stakeholders and decisionmakers and greater interdependence among actors – corresponds to lower stability, while strategies such as venue shopping and a greater number and diversity of non-government organizations are stabilizing. Finally, the final chapter draws on the general principles and methods from the previous chapters in the context of the San Joaquin Valley (SJV), an industrial agriculture-dominated region that is rife with inequality and with rapidly degrading groundwater, to explore actors' strategies, narratives, and power in shaping how water governance and agriculture in the SJV change. Narrative analysis of interviews and focus groups with growers, various advocacy groups, and residents of rural communities alongside modeling of actors' interactions with each other and with water is used to explore how these narratives influence actors’ strategies for enacting change, and the implications of their envisioned changes for how different groups can influence and are influenced by each other. The results reveal how the structure of agriculture and water governance create a conflict for small growers and rural communities between seeking more just distribution of the benefits from water consumption and increasing their water access within the status quo, which tends to channel most of the benefits of water management to larger growers. Overall, this dissertation develops complex systems approaches to understanding how linked natural and social dynamics shape the resilience and equity of natural resources exploitation and governance systems, yielding methodologies that can be applied to diverse cases, general principles for natural resources governance and resource-based communities, and concrete insights for guiding management and transformation of these systems.