Forensic investigations of disasters: Past achievements and new directions.

In the 2020s, understanding disaster risk requires a strong and clear recognition of values and goals that influence the use of political and economic power and social authority to guide growth and development. This configuration of values, goals, power and authority may also lead to concrete drivers of risk at any one time. Building on previous disaster risk frameworks and experiences from practice, since 2010, the 'Forensic Investigations of Disasters (FORIN)' approach has been developed to support transdisciplinary research on the transformational pathways societies may follow to recognise and address root causes and drivers of disaster risk. This article explores and assesses the achievements and failures of the FORIN approach. It also focuses on shedding light upon key requirements for new approaches and understandings of disaster risk research. The new requirements stem not only from the uncompleted ambitions of FORIN and the forensic approach but also from dramatic and ongoing transformational changes characterised by climate change, the coronavirus disease 2019 (COVID-19) pandemic and the threat of global international confrontation, among other potential crises, both those that can be identified and those not yet identified or unknown. Contribution: Disasters associated with extreme natural events cannot be treated in isolation. A comprehensive "all risks" or "all disasters" approach is essential for a global transformation, which could lead to a better world order. To achieve this, an Intergovernmental Panel for Disaster Risk is suggested to assess risk science periodically and work towards sustainability, human rights, and accountability, within a development and human security frame and on a systemic basis and integrated perspective.

Inequality and the social construction of urban disaster risk in multi-hazard contexts: the case of Lima, Peru and the COVID-19 pandemic.

This field note examines the disaster risk construction process in Lima, Peru. More commonly experienced hazard contexts are considered in the light of the COVID-19 pandemic. We provide an empirical analysis based on Lima-wide data and using findings from a single case study settlement to illustrate more general conclusions. We attempt to reveal how exposure and vulnerability factors signify that very different hazards, including COVID-19, predominantly affect the same population groups. Underlying causes and drivers, all related to different expressions of urban inequality, include problems of access to suitable urban land, land trafficking and invasion, State exclusion from social housing and basic services, unsafe building practice and corruption. The research confirms the usefulness of a social construction approach to disaster risk, based on the notion of underlying causes and drivers, and the need to reconfigure urban planning processes, breaking sector silos and encouraging integrated intersectoral and interspatial approaches.

Reproducing the manual annotation of multiple sequence alignments using a SVM classifier.

MOTIVATION: Aligning protein sequences with the best possible accuracy requires sophisticated algorithms. Since the optimal alignment is not guaranteed to be the correct one, it is expected that even the best alignment will contain sites that do not respect the assumption of positional homology. Because formulating rules to identify these sites is difficult, it is common practice to manually remove them. Although considered necessary in some cases, manual editing is time consuming and not reproducible. We present here an automated editing method based on the classification of 'valid' and 'invalid' sites. RESULTS: A support vector machine (SVM) classifier is trained to reproduce the decisions made during manual editing with an accuracy of 95.0%. This implies that manual editing can be made reproducible and applied to large-scale analyses. We further demonstrate that it is possible to retrain/extend the training of the classifier by providing examples of multiple sequence alignment (MSA) annotation. Near optimal training can be achieved with only 1000 annotated sites, or roughly three samples of protein sequence alignments. AVAILABILITY: This method is implemented in the software MANUEL, licensed under the GPL. A web-based application for single and batch job is available at http://fester.cs.dal.ca/manuel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

La gestión del riesgo de desastres: Un enfoque basado en procesos

El presente texto se propone como una herramienta conceptual dirigida a actores sociales e institucionales comprometidos con la gestión del riesgo de desastres. Busca avanzar en la comprensión del riesgo y su intervención a través de un enfoque basado en procesos, como un aporte para mejorar la coordinación de sistemas organizacionales con énfasis en los existentes en la subregión andina

La gestión local del riesgo : Nociones y precisiones en torno al concepto y la práctica

Nociones y precisiones en torno al concepto y la práctica del riesgo y la gestión local del riesgo en el marco del desarrollo. Se analizan los parámetros y las prácticas de la gestión del riesgo a partir de un enfoque de pasar de proyectos a procesos.