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Forecasting the impact of active or future volcanic eruptions and correctly interpreting the remnants of past eruptions requires access to models of eruptive processes. The volcano modeling community recognizes a need for more equitable access to robust, verified, validated, and easy-to-use models. To answer this need, we are building VICTOR (Volcanology Infrastructure for Collaboration, Tools, and Resources), a new cyberinfrastructure for the volcano modeling community. VICTOR is connected with national efforts including CONVERSE and SZ4D’s Modelling Collaboratory for Subduction (MCS). To ensure continuity of service for our community, during the transition to VICTOR, the existing Vhub.org platform is still available inside a separately supported new ghub.org.We formed a collaboration with a non-profit organization (2i2c, part of Code for Science and Society) that manages VICTOR’s back end in the form of a JupyterHub placed in the cloud. We are now developing jupyter notebooks for the hub, that call existing volcano models such as the lava flow codes MOLASSES, IMEX_lava and pyFLOWGo, the tephra dispersal codes Tephra2 and HYSPLIT, and the mass flow code TITAN2D.VICTOR will not only provide access to the modeling tool themselves, but also to workflows that utilize these forward models for inversion, benchmarking, and uncertainty quantification. For example, we are developing a workflow to validate mass flow models using the Jaccard fit, model sensitivity, and model precision metrics, all related to Bayes’ theorem. Lastly, we taught a graduate, multi-institutional course on volcanic hazard modeling using VICTOR in Spring 2023 and are creating multilingual tutorials for the workflows., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The processes of proliferation, differentiation, and apoptosis are tightly regulated during haemopoiesis with aberrations resulting in the uncontrolled clonal growth of non-functional haemopoietic cells, a disease state known as leukaemia. Approaches that target cellular growth and differentiation pathways to alter the proliferative potential of leukaemia cells while limiting cytotoxicity to healthy cells have recently undergone a revival in clinical interest. Known as differentiation therapy, the immature cancer cells undergo terminal differentiation culminating in the ultimate removal of these cells by apoptosis. The sphingomyelin signalling pathway, and its second messenger ceramide, has emerged as an important regulator of cellular growth, differentiation and apoptosis. Whilst numerous studies have addressed the apoptogenic properties of ceramide signalling, very few have investigated the mechanisms underlying ceramide mediated terminal differentiation. The aim of this study was to investigate the potential for the ceramide signalling pathway to be utilised in differentiation therapy for the treatment of human leukaemia. A range of haemopoietic cell lines were treated with the synthetic ceramide analogue, C2-ceramide. Growth inhibition, cell cycle arrest, activation of the retinoblastoma (Rb) tumour suppressor protein, expression of the cyclin-dependent kinase inhibitor p21aPI/Waf 1 and apoptosis were shown to be common outcomes of ceramide treatment. Myeloid cells exposed to ceramide differentiated into a mature phenotype. Taken together, these results show that ceramide is inducing terminal differentiation in the treated cell lines. Phosphatases have a well characterised function in Rb activation and their potential as an effector mechanism for ceramide-induced Rb activation and differentiation was examined. Inhibitor studies revealed that ceramide-mediated Rb activation resulted from protein phosphatase activity, and that the contribution of p2Cip 1/Waft was not significant, at least in the early phases of cell cycle arrest. Interestingly, inhibition of protein phosphatase activity did not impact on the ability of ceramide signalling to induce myeloid cell differentiation. This lead to the conclusion that Rb activation and ceramide-induced differentiation occur by two independent pathways. Gene expression profiling using a cDNA filter array was performed to elucidate the involvement of genetic mechanisms involved in the ceramide response. Genes that prevent progression through the cell cycle and genes involved in differentiation were upregulated whereas the expression of proliferation-related genes were downregulated. These findings are consistent with the hypothesis that ceramide reduces the proliferative potential of leukaemic cells by inducing terminal differentiation. This thesis presents a comprehensive study into the biological effects of the ceramide signalling pathway, and has in part defined the molecular mechanisms responsible for ceramide-induced growth arrest and differentiation. Ceramide was shown to mediate the terminal differentiation of leukaemia cells into mature, nondividing cells that die by apoptosis. Manipulation of the ceramide-signalling pathway may present a novel therapeutic target for the treatment of diseases that lack control of growth and differentiation processes.

Vent opening hazard models are routinely used as inputs for assessing distal volcanic hazards (lava flows, tephra fallout) in distributed volcanic fields. These vent opening hazard models have traditionally relied on the location of mapped vents; seldom have they taken into account how vents are linked in space and time. We show that inputs needed to appropriately model distal hazards are fundamentally different than thoses required to model near-vent hazards (ground deformation). We provide a computational model to obtain more appropriate eruptive source parameters (ESPs) for distal volcanic hazard sources and show the utility of our code through three examples. The code's strength is that it links events based on the spatio-temporal relationships of vents through heirarchical clustering. The development of the code and its strenghts and weaknesses are discussed. This work challenges previous ideas about ESPs and we hope this work leads to further improvement in hazard assessment methods.

Forecasting the impact of active or future volcanic eruptions and correctly interpreting the remnants of past eruptions requires access to models of eruptive processes. We are building VICTOR, a new cyber-infrastructure for the volcano modeling community. VICTOR will be a Jupyterhub-based portal that will provide access to a library of models and workflows, as well as computational tools and volcano data repositories. This poster presents an overview of VICTOR as well as the progress to date (June 2022).

International Financial Reporting Standard (IFRS) 9 becomes mandatory in January 2018, replacing International Accounting Standard (IAS) 39. The standard introduces a revolutionary forward-looking credit loss model requiring affected entities to calculate and report expected credit losses associated with financial instruments. The new expected credit loss model necessitates entities to use a range of data assets and big data analytical approaches which have not previously been employed for IFRS reporting. Industry analysis has identified the new standard as a practical challenge which impacts data governance frameworks and information systems infrastructures. Extant IFRS, data governance and big data literature does not address the impact of IFRS standard evolution on the data governance frameworks and big data information system infrastructures of affected entities. Moreover, extant literature does not explore the influence of an entity’s capability to conduct big data analytics on their ability to comply with new standard requirements. To address these literature gaps, this study extended DeLone and McLean’s information systems success model with the concepts of organisational big data analytics capabilities and attitudes towards IFRS 9 compliance. The model was then tested by surveying industry professionals involved with international IFRS 9 implementation projects. To evaluate the research model, the results of the survey were analysed using structural equational modelling partial least squares. The primary finding of this study is that the capability of an entity to conduct big data analytics positively affects their employee’s intentions to use IFRS 9 analytics applications and their attitude towards the ability of their entity to comply with IFRS 9. Another key finding is that the quality of the output of information systems used to support IFRS 9 analytics applications positively impacts the intention of affected entity’s employees to use IFRS 9 analytics applications and their attitude towards the ability of the entity to comply with the standard. This study is the first to test an information systems success model in the context of IFRS 9 and is the first to introduce the concept of organisational big data analytics capabilities as an independent variable in information systems success. The study is also relevant to entities which are required to comply with IFRS as it provides empirical research which may help them to develop readiness and capabilities for future IFRS standards.

Additional file 1: Supplementary Information Figure 1. The conditional probability maps showing the areas affected by volcanic ballistics given: a) a small eruption (S1), b) a moderate eruption (S2) and c) a large eruption (S3) from the central vent. Supplementary Information Figure 2. The conditional probability maps showing the areas affected by tephra fallout given: a) a small eruption (S1), b) a moderate eruption (S2) and c) a large eruption (S3) from the central vent. Supplementary Information Figure 3. The conditional probability maps showing the areas affected by lava flows given: a) a small eruption (S1) and b) a moderate eruption (S2) from the central vent. Supplementary Information Figure 4. The conditional probability maps showing the areas affected by pyroclastic density currents given: a) a moderate eruption (S2) and b) a large eruption (S3) from the central vent. Supplementary Information Figure 5. The conditional probability maps showing the areas affected by lahars given: a) a moderate eruption (S2) and b) a large eruption (S3) from the central vent.

Object coding in primate ventral pathway cortex progresses in sparseness/compression/efficiency, from many orientation signals in V1, to fewer 2D/3D part signals in V4, to still fewer multi-part configuration signals in AIT (anterior inferotemporal cortex). 1-11 This progression could lead to individual neurons exclusively selective for unique objects, the sparsest code for identity, especially for highly familiar, important objects. 12-18 To test this, we trained macaque monkeys to discriminate 8 simple letter-like shapes in a match-to-sample task, a design in which one-to-one coding of letters by neurons could streamline behavior. Performance increased from chance to >80% correct over a period of weeks, after which AIT neurons showed clear learning effects, with increased selectivity for multi-part configurations within the trained alphabet shapes. But these neurons were not exclusively tuned for unique letters based on training, since their responsiveness generalized to different, non-trained shapes containing the same configurations. This multi-part configuration coding limit in AIT is not maximally sparse, but it could explain the robustness of primate vision to partial object occlusion, which is common in the natural world and problematic for computer vision. Multi-part configurations are highly diagnostic of identity, and neural signals for various partial object structures can provide different but equally sufficient evidence for whole object identity across most occlusion conditions.