Scaling Success: Lessons from Adaptation Pilots in the Rainfed Regions of India

"Scaling Success" examines how agricultural communities are adapting to the challenges posed by climate change through the lens of India's rainfed agriculture regions. Rainfed agriculture currently occupies 58 percent of India's cultivated land and accounts for up to 40 percent of its total food production. However, these regions face potential production losses of more than $200 billion USD in rice, wheat, and maize by 2050 due to the effects of climate change. Unless action is taken soon at a large scale, farmers will see sharp decreases in revenue and yields.Rainfed regions across the globe have been an important focus for the first generation of adaptation projects, but to date, few have achieved a scale that can be truly transformational. Drawing on lessons learnt from 21 case studies of rainfed agriculture interventions, the report provides guidance on how to design, fund and support adaptation projects that can achieve scale

Tiresias: Predicting Security Events Through Deep Learning

With the increased complexity of modern computer attacks, there is a need for defenders not only to detect malicious activity as it happens, but also to predict the specific steps that will be taken by an adversary when performing an attack. However this is still an open research problem, and previous research in predicting malicious events only looked at binary outcomes (e.g., whether an attack would happen or not), but not at the specific steps that an attacker would undertake. To fill this gap we present Tiresias, a system that leverages Recurrent Neural Networks (RNNs) to predict future events on a machine, based on previous observations. We test Tiresias on a dataset of 3.4 billion security events collected from a commercial intrusion prevention system, and show that our approach is effective in predicting the next event that will occur on a machine with a precision of up to 0.93. We also show that the models learned by Tiresias are reasonably stable over time, and provide a mechanism that can identify sudden drops in precision and trigger a retraining of the system. Finally, we show that the long-term memory typical of RNNs is key in performing event prediction, rendering simpler methods not up to the task

Samoa technical report - Review of volcanic hazard maps for Savai'i and Upolu

Both main islands of Samoa, Savai'i and Upolu need to be considered as potentially volcanically active. The most recent eruptions in historic times happened on Savai'i in 1905-1911, 1902 and 1760 (estimated). Though detailed volcanic studies and dating of volcanic events are very limited there is evidence for repeated volcanic activity on both islands since the time of human occupation of the islands marked by prominent and fresh appearance of tuff cones as Tafua (= fire mountain) Savai'i, the island of Apolima, Tafua Upolu and offshore Cape Tapaga. This report examines the volcanic risks for both islands and defines for disaster management considerations potential eruption scenarios based on eyewitness accounts of previous eruptions, geological field evidence, remote sensing information and experiences from similar volcanoes. A detailed timeline of events, potential impacts and required emergency response activities are listed for the five potential eruption types (1) long-term lava field (2) short-term spatter-cone (3) explosive phreatomagmatic (4) explosive scoria-cone and (5) submarine flank collapse. Given the nature of volcanism in Samoa with hundreds of individual "one-off" volcanoes scattered along zones of structural weakness within the Savai'i - Upolu Platform - predicting the exact location of future eruption centres is impossible. At the current stage of knowledge a presentation of a volcanic hazard map is inadequate and would require additional baseline studies to statistically define recurrence intervals and areas of higher volcanic activity. Taking these limitations into account, maps showing the relative potential for new eruption vents on Upolu and Savai'i are derived from geomorphologic features. To improve our understanding and management of the volcanic risks of Samoa, suggestions for achievable future work are listed and prioritised. These recommendations include geological/volcanological baseline studies (e.g. dating/detailed analyses of past events, rock chemistry, volcano structure); installation of early warning and monitoring network (e.g. permanent GPS, seismometers); and disaster preparedness and volcanic crisis response planning

Building an Emulation Environment for Cyber Security Analyses of Complex Networked Systems

Computer networks are undergoing a phenomenal growth, driven by the rapidly increasing number of nodes constituting the networks. At the same time, the number of security threats on Internet and intranet networks is constantly growing, and the testing and experimentation of cyber defense solutions requires the availability of separate, test environments that best emulate the complexity of a real system. Such environments support the deployment and monitoring of complex mission-driven network scenarios, thus enabling the study of cyber defense strategies under real and controllable traffic and attack scenarios. In this paper, we propose a methodology that makes use of a combination of techniques of network and security assessment, and the use of cloud technologies to build an emulation environment with adjustable degree of affinity with respect to actual reference networks or planned systems. As a byproduct, starting from a specific study case, we collected a dataset consisting of complete network traces comprising benign and malicious traffic, which is feature-rich and publicly available

Environmental representativity in marine protected area networks over large and partly unexplored seascapes

Converting assemblages of marine protected areas (MPAs) into functional MPA networks requires political will, multidisciplinary information, coordinated action and time. We developed a new framework to assist planning environmental representativity in a network across the marine space of Portugal, responding to a political commitment to protect 14% of its area by 2020. An aggregate conservation value was estimated for each of the 27 habitats identified, from intertidal waters to the deep sea. This value was based on expert-judgment scoring for environmental properties and features relevant for conservation, chosen to reflect the strategic objectives of the network, thus providing an objective link between conservation commitments and habitat representativity in space. Additionally, habitats' vulnerability to existing anthropogenic pressures and sensitivity to climate change were also scored. The area coverage of each habitat in Portugal and within existing MPAs (regionally and nationally) was assigned to a scale of five orders of magnitude (from 10%) to assess rarity and existing representation. Aggregate conservation value per habitat was negatively correlated with area coverage, positively correlated with vulnerability and was not correlated with sensitivity. The proposed framework offers a multi-dimensional support tool for MPA network development, in particular regarding the prioritization of new habitats to protect, when the goal is to achieve specific targets while ensuring representativity across large areas and complex habitat mosaics. It requires less information and computation effort in comparison to more quantitative approaches, while still providing an objective instrument to scrutinize progress on the implementation of politically set conservation targets.Agência financiadora Número do subsídio Oceanic Observatory of Madeira M1420-01-0145-FEDER-000001-OOM national funds through FCT UID/BIA/00329/2013 UID/Multi/04326/2013 Fundacao para a Ciencia e a Tecnologia SFRH/BPD/95334/2013 CESAM - FCT/MEC through national funds UID/AMB/50017 - POCI-01-0145-FEDER-007638 FEDER FCT SFRH/BPD/94320/2013 MARE - UID/MAR/04292/2019 EU through the Cohesion Fund POSEUR-03-2215-FC-000046 POSEUR-03-2215-FC-000047 FCT national funds ECO/28687/2017info:eu-repo/semantics/publishedVersio

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An integrated approach to supply chain risk analysis

Despite the increasing attention that supply chain risk management is receiving by both researchers and practitioners, companies still lack a risk culture. Moreover, risk management approaches are either too general or require pieces of information not regularly recorded by organisations. This work develops a risk identification and analysis methodology that integrates widely adopted supply chain and risk management tools. In particular, process analysis is performed by means of the standard framework provided by the Supply Chain Operations Reference Model, the risk identification and analysis tasks are accomplished by applying the Risk Breakdown Structure and the Risk Breakdown Matrix, and the effects of risk occurrence on activities are assessed by indicators that are already measured by companies in order to monitor their performances. In such a way, the framework contributes to increase companies' awareness and communication about risk, which are essential components of the management of modern supply chains. A base case has been developed by applying the proposed approach to a hypothetical manufacturing supply chain. An in-depth validation will be carried out to improve the methodology and further demonstrate its benefits and limitations. Future research will extend the framework to include the understanding of the multiple effects of risky events on different processe

The adaptation continuum: groundwork for the future

The focus of the program was to understand the challenges posed by climate change and climate variability on vulnerable groups and the policies needed to support climate adaptation in developing countries. The aim of the book is to share this experience in the hope that it will be helpful to those involved in shaping and implementing climate change policy