Water management and livelihood choices in southwestern Bangladesh

Coastal Bangladesh faces an increasing number of challenges including cyclones, tidal surges, floods, drought, saline water intrusion, waterlogging and land subsidence, which pose substantial threats to the livelihoods of the coastal inhabitants. In addition to these threats, profound social and land-use changes are complicating the livelihoods of resource users in the region, including the introduction of aquaculture and increasing competition for ground and surface water sources. The government of Bangladesh has targeted this region for investment with irrigation expansion. This paper uses a sustainable livelihood lens to understand the role of investments in water management and irrigation in driving and shaping livelihood changes and transitions over the past ten years and offers recommendations for investments. We find that while water infrastructure development has greatly enhanced the role of agriculture in coastal livelihoods over the last 10 years, further development of irrigation infrastructure should only be prioritized after issues of water governance and inequity across agricultural and aquacultural livelihoods are addressed

Joint water quantity/quality management analysis in a biofuel production area: Using an integrated economic-hydrologic model

"Water management in the Pirapama River Basin in northeastern Brazil is affected by both water quantity and water quality constraints. The region is known for significant sugarcane-based ethanol production—which is key to the Brazilian economy and expected to grow dramatically under recent global changes in energy policy. Sugarcane production in the region goes hand in hand with controlled fertirrigation practices with potentially significant adverse impacts on the environment. To assess sustainable water allocation in the basin, an integrated hydrologic-economic basin model is adapted to study both water quantity and water quality aspects. The model results show that incorporating water quality aspects into water allocation decisions leads to a substantial reduction in application of vinasse to sugarcane fields. To enforce water quality restrictions, the shadow price for maintaining water in the reservoir could be used as a pollution tax for fertirrigated areas, which are currently not subject to pollution charges." from authors' abstractWater quality, River basin model, Integrated economic-hydrologic modeling, Nonlinear optimization, Biofuels, Water resources, Environmental impacts,

Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning

This paper proposes an adaptation of the Q-Learning reinforcement learning algorithm, for the identification of the most probable scenario that a player may face, under different contexts, when negotiating bilateral contracts. For that purpose, the proposed methodology is integrated in a Decision Support System that is capable to generate several different scenarios for each negotiation context. With this complement, the tool can also identify the most probable scenario for the identified negotiation context. A realistic case study is conducted, based on real contracts data, which confirms the learning capabilities of the proposed methodology. It is possible to identify the most probable scenario for each context over the learned period. Nonetheless, the identified scenario might not always be the real negotiation scenario, given the variable nature of such negotiations. However, this work greatly reduces the frequency of such unexpected scenarios, contributing to a greater success of the supported player over time.This work has received funding from National Funds through FCT (Fundaçao da Ciencia e Tecnologia) under the project SPET – 29165, call SAICT 2017.info:eu-repo/semantics/publishedVersio

Author Correction: High-resolution cryo-EM structure of urease from the pathogen Yersinia enterocolitica

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19845-z

Gender-sensitive Risks and Options Assessment for Decision making (ROAD) to support WiF2

The Gender-Sensitive Risks and Options Assessment for Decision Making (ROAD) to Support WiF-2 (ROAD migration project), a partnership coordinated by the International Food Policy Research Institute (IFPRI), Australian National University, American University Beirut, Lincoln University, and University of Dhaka, evaluated the ILO-DFID Partnership Programme on Fair Recruitment and Decent Work for Women Migrant Workers in South Asia and the Middle East (Work in Freedom, Phase 2 project [WiF-2]), which operated from 2018 to 2023. The WiF-2 project specifically aimed “to reduce vulnerability to trafficking and forced labour of women and girls across migration pathways leading to the care sector and textiles, clothing, leather and footwear industries (TCLFI) of South Asia and Arab States” (ToC WiF-2)