232 research outputs found
District-level Spatial Analysis of Migration Flows in Ghana: Determinants and Implications for Policy
The present study investigates the determinants of inter-district migration flows over the 1995-2000 period in Ghana. A combination of socio-economic, natural and spatial âdistrict-levelâ attributes are considered as potential variables explaining the direction of migration flows. In addition to the ânetâ migration model, âinâ and âoutâ migration models are also employed within the context of the gravity model. Results in the three models consistently show that people move out of districts with less employment and choose districts with high employment rate as destinations. While shorter distance to roads encourages out-migration, districts with better water access seem to attract migrants. Generally, people move out of predominantly agrarian districts to relatively more urbanized districts.Gross migration, Net migration, Inter-district migration flows, spatial analysis, Ghana, Africa, Community/Rural/Urban Development, Labor and Human Capital,
Nutritient flow scenarios for sustainable smallholder faming systems in southwestern Burkino Faso : food security and better livelihoods for rural dryland communities
The report presents a study on nutrient flows of agricultural livelihood systems dominated by smallholder farms in South-western Burkina Faso. The material flow analysis of nitrogen, phosphorus, and potassium provides a detailed picture of current nutrient flows within, in to, and out of smallholder farms. Such a picture allows quantifying material potentials for sustainable intensification, that is, increasing the ratio of crop yield to mineral fertilizer inputs. Finally, in the pursuit of indicators for sustainable intensification, we propose combining indicators derived from material flow analysis with indicators of socio-economic nature to move from material potential assessments to sustainability assessments. The combination is informed by the criticality concept, a concept which denotes how important a specific material resource is to an anthropogenic system. Based on an existing criticality determination methodology for metals, we sketch the criticality indicator set for the case of nitrogen, phosphorus, and potassium and smallholder farms. Further research should include increasing temporal boundaries to capture cycles longer than a year, the applied temporal boundary in this study. A multi-scale study including villages and landscapes could provide additional insights on the role of water bodies or future .industrial activities in nutrient cycling. In turn, the multi-scale MFAs would provide the necessary indicator values to assess nutrient criticality not only at the smallholder farm level, but also at the village and landscape level. Finally, the material flows could be further characterized with respect to gender, cost/benefits, etc
Trends of degradation and improvement in biomass productivity in target countries of CGIAR Initiative in Sustainable Intensification of Mixed Farming Systems â An Interim Report
Trends of degradation and improvement in biomass productivity in the target countries of MFS Initiative using Trends.Earth tool. The calculation of the trends using global time-series of NDVI (MODIS) over the 2000-2015 period. Appropriate uses of the results for supporting other activities in MFS Initiative, as well as further validation with national experts are discussed and recommended
Provisional analytical procedures for mapping MFS, their socio-ecological context, and system performance
A methodological approach for mapping mixed farming systems (MFS) and typologies at national and sub-national levels is proposed and described, with concrete system-based analytical pathway and suggested data sources. The approach is under developing, will be finalized and adaptively used for MFS mapping in the target countries of the CGIAR Initiative on Sustainable Intensification of MFS (SI-MFS) in 2023
Synthesis of Block Copolymers to Deliver Ortho-Carborane for Proton Capture Therapy
https://openworks.mdanderson.org/sumexp22/1103/thumbnail.jp
Fetus Trafficking in Viet Nam â The New Criminal Method of Human Trafficking
When it comes to basic rights of the fetus, including the right to life, theoretical studies around the world on human rights of the fetus still have not reached an agreement on approaches and explanation. Criminal law at the international and national levels still leaves the possibility of protecting the unborn child. Viet Namâs criminal law is no exception to this trend. In addition, Viet Nam is currently facing human trafficking with new methods and tricks. Children are bought and paid for while still in the womb, then born abroad and given to traffickers. Children are only protected by criminal law for human trafficking if they are born, alive, and detected by the authorities. While the act of trafficking in fetuses is often easily detected by the authorities right from the stage of purchasing and paying, it is not feasible to prosecute this act for human trafficking under the criminal law of Viet Nam. This reduces the criminal lawâs ability to suppress crime, at the same time, leaves many fetuses unprotected. Should criminal law be left outside the legal mechanism to protect children while in the fetal stage? This article suggests considering fetus trafficking as a form of human trafficking and to criminalize fetus trafficking. Criminal law should recognize fetus trafficking as a sign of crime or an early stage in the criminal process of human trafficking, because children need special care and protection, including appropriate legal protection before and after birth, due to their physical and mental immaturity
Towards assessing the resource criticality of agricultural livelihood systems
Despite the many advantages of sustainable intensification (SI), the level of adoption of SI practices in African smallholding farms is still very low, highlighting the need for adequate methods for monitoring farm sustainability. Research on SI and related poverty alleviation strategies focus either on the âproblemsâ or on the âsolutionsâ for agricultural livelihood systems (ALS) with separate sets of indicators developed accordingly. Bridging the two approaches, we propose an indicator set to assess the criticality of a resource to ALSs in order to support smallholders, decision-makers, and practitioners in the process of SI. The set indicates what problems an ALS faces in the form of resource supply risks and the ALSâs ability to successfully cope with such problems, i.e., how resilient it is to these supply risks. We apply the ALS criticality approach (ALSCA) to macronutrients in three different ALS types in the village cluster of Pontieba, Ioba Province, Burkina Faso. Two criticality indicators are highlighted. First, the three ALS types are not facing equal nitrogen supply risks, when the latter is informed by depletion time. The depletion time indicates the time until which a resource stock is depleted at the current mining rate. The average depletion time of soil nitrogen stocks ranges from some 10 to 165 years. Second, the reliance on own resources is an indicator measuring resilience to supply restriction. In Pontieba, regardless of macronutrient, reliance on own nutrients never surpasses 50% when ALS averages are considered. The study showed that the ALSCA can contribute to the implementation of SI practices through support at four levels: 1) providing a holistic view on the ALS to avoid problem-shifting and enable prioritization, 2) providing options to reduce resource criticality, 3) mutual learning between ALSCA practitioners and smallholder farmers through knowledge integration, and 4) facilitating policy coherence from local to national levels thanks to the ALSCAâs applicability on different scales
Constructing consistent multiscale scenarios by transdisciplinary processes : the case of mountain regions facing global change
Alpine regions in Europe, in particular, face demanding local challenges, e.g., the decline in the agriculture and timber industries, and are also prone to global changes, such as in climate, with potentially severe impacts on tourism. We focus on the Visp region in the Upper Valais, Switzerland, and ask how the process of stakeholder involvement in research practice can contribute to a better understanding of the specific challenges and future development of mountainous regions under global change. Based on a coupled human-environment system (HES) perspective, we carried out a formative scenario analysis to develop a set of scenarios for the future directions of the Visp region. In addition, we linked these regional scenarios to context scenarios developed at the global and Swiss levels via an external consistency analysis. This method allows the coupling of both the scenario building process and the scenarios as such. We used a functional-dynamic approach to theory-practice cooperation, i.e., the involvement of key stakeholders from, for example, tourism, forestry, and administration, differed in type and intensity during the steps of the research process. In our study, we experienced strong problem awareness among the stakeholders concerning the impacts of global change and local challenges. The guiding research question was commonly defined and problem ownership was more or less balanced. We arrived at six multiscale scenarios that open up future trajectories for the Visp region, and present generic strategies to cope with global and local challenges. The results show that local identity, spatial planning, community budget, and demographic development are important steering elements in the regionâs future development. We suggest that method-guided transdisciplinary processes result in a richer picture and a more systemic understanding, which enable a discussion of critical and surprising issues
HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System
Measuring the confidence of AI models is critical for safely deploying AI in
real-world industrial systems. One important application of confidence
measurement is information extraction from scanned documents. However, there
exists no solution to provide reliable confidence score for current
state-of-the-art deep-learning-based information extractors. In this paper, we
propose a complete and novel architecture to measure confidence of current deep
learning models in document information extraction task. Our architecture
consists of a Multi-modal Conformal Predictor and a Variational
Cluster-oriented Anomaly Detector, trained to faithfully estimate its
confidence on its outputs without the need of host models modification. We
evaluate our architecture on real-wold datasets, not only outperforming
competing confidence estimators by a huge margin but also demonstrating
generalization ability to out-of-distribution data.Comment: Document Intelligence @ KDD 2021 Worksho
- âŠ