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 ‘district-level’ attributes are considered as potential variables explaining the direction of migration flows. In addition to the ‘net’ migration model, ‘in’ and ‘out’ 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

Dielectric modelling of human skin and breast tissue in terahertz frequencies : potential application to cancer detection

University of Technology Sydney. Faculty of Engineering and Information Technology.Growing developments in the generation and detection of terahertz (THz) radiation over more than two decades have created a strong incentive for researchers to study the biomedical applications of terahertz imaging. Contrasts in the THz images of various types of cancer, especially skin and breast cancer, are associated with changes in the dielectric properties of cancerous tissues. In fact, dielectric models can explain the interaction between terahertz radiation and human tissue at a molecular level just as their parameters have the potential for becoming indicators of cancer. However, dielectric modelling of various forms of human tissue remains limited due to a number of factors, especially suboptimal fitting algorithms and tissue heterogeneity. Thanks to the high water content of human skin, its dielectric response to terahertz radiation can be described by the double Debye model. The existing fitting method using a nonlinear least square algorithm can extract the model parameters which track their measurements accurately at frequencies higher than one THz but poorly at lower frequencies. However, the majority of dielectric contrast between normal and cancerous skin tissues has been observed in the low THz range. Accordingly, this research has developed two global optimization algorithms which are capable of globally accurate tracking thereby supporting the full validity of the double Debye model in simulating the dielectric spectra of human skin in the THz frequencies. Numerical results confirm their superiority over the conventional methods. Furthermore, the next goal of the study is to apply statistical analysis to the parameters of the double Debye model in order to test their discrimination capability of skin cancer from normal tissue. Linear programming and support vector machine algorithms have also been employed using these parameters to classify normal skin tissue and basal cell carcinoma. By combining the double Debye parameters, the classification accuracy has shown significant improvement. The encouraging outcomes confirm the classification potential of the double Debye parameters. The double Debye model, however, has been shown to be not suitable for simulating human breast tissue due to its low water content and heterogeneous structure, thus limiting the understanding of the THz dielectric response of breast tissue. To overcome this problem, this study proposes a new non-Debye dielectric model to fit the dielectric spectra of human breast tissue. Due to the mathematical complexity of the fitting procedure, a sampling gradient algorithm of non-smooth optimization is used to optimize the fitting solution. Simulation results confirm applicability of the non-Debye model through its exceptional ability to fit the examined data. Statistical measures have also been used to analyse the possibility of using the parameters of this model to differentiate breast tumours from healthy breast tissue. Based on the statistical analysis, popular classification methods such as support vector machines and Bayesian neural network have also been applied to examine these parameters and their combinations for breast cancer classification. The obtained classification accuracies indicate the classification potential of the model parameters as well as highlighting several valuable features of the parameter combinations

Trends of degradation and improvement in biomass productivity in target countries of CGIAR Initiative in Sustainable Intensification of Mixed Farming Systems – 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

THE CUISINE OF THE EDE PEOPLE IN KMRONG PRŎNG VILLAGE, BUON MA THUOT (DAK LAK PROVINCE)

The Ede are a Malayo-Polynesian language-speaking ethnic group residing primarily in Dak Lak, Dak Nong, Phu Yen, and Khanh Hoa provinces. They have a rich and unique tangible and intangible culture. From 2017 to 2020, the authors carried out many field trips to Kmrong Prŏng A and Kmrong Prŏng B villages (Ea Tu Commune, Buon Ma Thuot) to research, collect, and inventory the material and spiritual cultural heritage of the Ede for conservation and exhibition at the Dak Lak provincial museum. In this article, we introduce some traditional dishes of the Ede in Krmong Prŏng village, research and evaluate traditional aspects of their cuisine, and propose some recommendations and solutions to preserve and promote the unique Ede cuisine in the current period of development and integration

Differentiable Bayesian Structure Learning with Acyclicity Assurance

Score-based approaches in the structure learning task are thriving because of their scalability. Continuous relaxation has been the key reason for this advancement. Despite achieving promising outcomes, most of these methods are still struggling to ensure that the graphs generated from the latent space are acyclic by minimizing a defined score. There has also been another trend of permutation-based approaches, which concern the search for the topological ordering of the variables in the directed acyclic graph in order to limit the search space of the graph. In this study, we propose an alternative approach for strictly constraining the acyclicty of the graphs with an integration of the knowledge from the topological orderings. Our approach can reduce inference complexity while ensuring the structures of the generated graphs to be acyclic. Our empirical experiments with simulated and real-world data show that our approach can outperform related Bayesian score-based approaches.Comment: Accepted as a regular paper (9.37%) at the 23rd IEEE International Conference on Data Mining (ICDM 2023