Financialization, price risks, and global commoditychains: Distributional implications on cotton sectorsin Sub-Saharan Africa

The functioning of commodity markets has changed related to processes of financialization that involve two major developments – the rise of financial interest on commodity derivative markets through the increasing presence of financial investors and the changing business models of international commodity trading houses and the increasing importance of these markets in price setting and risk management since the liberalization of national commodity sectors. A critical question is how these global financialization processes affect commodity producers in low income countries via the operational dynamics of global commodity chains and distinct national market structures. This paper investigates how global financialization processes influence how prices are set and transmitted and how risks are distributed and managed in the cotton sectors in Burkina Faso, Mozambique and Tanzania. It concludes that uneven exposure to price instability and access to price risk management have important distributional implications. Whilst international traders have the capacity to deal with price risks through hedging in addition to expanding their profit possibilities through financial activities on commodity derivative markets, local actors in producer countries face the challenge of price instability and increased short-termism – albeit to different extents deepening on local market structures – with limited access to risk management

Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network

This study demonstrates the utilization of deep learning techniques for binary semantic segmentation of pores in carbon fiber reinforced polymers (CFRP) using X-ray computed tomography (XCT) datasets. The proposed workflow is designed to generate efficient segmentation models with reasonable execution time, applicable even for users using consumer-grade GPU systems. First, U-Net, a convolutional neural network, is modified to handle the segmentation of XCT datasets. In the second step, suitable hyperparameters are determined through a parameter analysis (hyperparameter tuning), and the parameter set with the best result was used for the final training. In the final step, we report on our efforts of implementing the testing stage in open_iA, which allows users to segment datasets with the fully trained model within reasonable time. The model performs well on datasets with both high and low resolution, and even works reasonably for barely visible pores with different shapes and size. In our experiments, we could show that U-Net is suitable for pore segmentation. Despite being trained on a limited number of datasets, it exhibits a satisfactory level of prediction accuracy

Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization

This work evaluates and compares the accuracy of different fiber orientation prediction models for a short fiber reinforced injection molded Venturi-shaped part which displays variable thickness. The experimental characterization of the specimen fiber orientation distribution (FOD) was carried out by the micro computed tomography technique (micro-CT). The computational study of fiber orientation predictions was performed using Moldex3D. All the possible combinations of the Folgar-Tucker (FT) and improved Anisotropic Rotary Diffusion (iARD) rotary diffusion models and the Hybrid (Hyb), Orthotropic (ORE), and Invariant Based Optimal Fitting (IBOF) closure approximations were considered. The relevance of the Retardant Principal Rate (RPR) model on predictions results was also evaluated. The values of the fiber-fiber (Ci), matrix-fiber (Cm) interaction coefficients and the alpha-RPR parameter were varied in a significant range in order to find the set of parameters that better fits the experimental fiber orientation data. The parameters' sensitivity effect over the second order orientation tensor components was quantified via the Analysis of Variance (ANOVA) statistical method. The experimental micro-CT results show an increase in the fiber orientation degree at the specimen constriction region due to the narrowed cavity and the Venturi effect. The comparison of the experimental and predicted orientation profiles demonstrates that the predictions of the iARD model, in combination with the IBOF closure approximation, are the most accurate for the case studied. However, simulations fail to estimate the change in orientation caused by variable thickness and section. ANOVA results prove that the orientation tensor component in the flow direction (a11) is more sensitive to changes in alpha-RPR and Ci coefficient, while the perpendicular components (a22, a33) are also significantly affected by Cm. From the predictive error analysis it is seen that the optimal parameters set to capture the orientation state of the specimen is: (i) for the FT model, Ci = 0.005, alpha-RPR = 0.7 and (ii) for the iARD model, Ci = 0.005, Cm = 0.2, and alpha-RPR = 0.7.Fil: Quintana, María Camila. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; ArgentinaFil: Frontini, Patricia Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnología de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones en Ciencia y Tecnología de Materiales; ArgentinaFil: Arriaga, Aitor. Johannes Kepler University Linz; AustriaFil: Plank, Bernhard. University of Applied Sciences Upper; AustriaFil: Major, Zoltan. Johannes Kepler University Linz; Austri

Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network

This study demonstrates the utilization of deep learning techniques for binary semantic segmentation of pores in carbon fiber reinforced polymers (CFRP) using X-ray computed tomography (XCT) datasets. The proposed workflow is designed to generate efficient segmentation models with reasonable execution time, applicable even for users using consumer-grade GPU systems. First, U-Net, a convolutional neural network, is modified to handle the segmentation of XCT datasets. In the second step, suitable hyperparameters are determined through a parameter analysis (hyperparameter tuning), and the parameter set with the best result was used for the final training. In the final step, we report on our efforts of implementing the testing stage in open_iA, which allows users to segment datasets with the fully trained model within reasonable time. The model performs well on datasets with both high and low resolution, and even works reasonably for barely visible pores with different shapes and size. In our experiments, we could show that U-Net is suitable for pore segmentation. Despite being trained on a limited number of datasets, it exhibits a satisfactory level of prediction accuracy

An online authoring and publishing platform for field guides and identification tools

Various implementation approaches are available for digital field guides and identification tools that are created for the web and mobile devices. The architecture of the “biowikifarm” publishing platform and some technical and social advantages of a document- and author-centric approach based on the MediaWiki open source software over custom-developed, database driven software are presented

Desire for biological parenthood and patient counseling on the risk of infertility among adolescents and adults with hemoglobinopathies.

BACKGROUND Both diagnosis and treatment of hemoglobinopathies have been associated with an increased risk of fertility impairment. German guidelines recommend annual monitoring of fertility parameters to enable early detection of fertility impairment and/or to offer fertility preservation (FP) when indicated. We explored the general desire for parenthood, the frequency of recalling fertility counseling and testing, and the utilization of FP in adolescents and adults with hemoglobinopathies. PROCEDURE In a cross-sectional study, patients aged 12-50 years, treated in Germany, Austria, or Switzerland, were surveyed on fertility-related aspects. Medical data, including fertility testing results, were collected from patient records. RESULTS Overall, 116/121 eligible patients, diagnosed with sickle cell disease (70.7%), thalassemia (27.6%), or other hemoglobinopathy (1.7%), participated in our study (57.8% female, median age 17.0 years, range 12-50 years). All participants required treatment of the underlying hemoglobinopathy: 68.1% received hydroxyurea, 25.9% required regular blood transfusions, and 6.0% underwent hematopoietic stem cell transplantation (HSCT). Most patients (82/108, 75.9%) stated a considerable to strong desire for (future) parenthood, independent of sex, education, diagnosis, or subjective health status. Fertility counseling was only recalled by 32/111 patients (28.8%) and least frequently by younger patients (12-16 years) or those treated with regular blood transfusions or hydroxyurea. While fertility testing was documented for 59.5% (69/116) in medical records, only 11.6% (13/112) recalled previous assessments. FP was only used by 5.4% (6/111) of patients. CONCLUSION Most patients with hemoglobinopathies wish to have biological children, yet only few recalled fertility counseling and testing. Adequate patient counseling should be offered to all patients at risk for infertility

Continental bedrock and riverine fluxes of strontium and neodymium isotopes to the oceans

Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 11 (2010): Q03016, doi:10.1029/2009GC002869.Realistic models of past climate and ocean chemistry depend on reconstructions of the Earth's surface environments in the geologic past. Among the critical parameters is the geologic makeup of continental drainage. Here we show, for the present, that the isotope composition of dissolved strontium in rivers increases linearly with the age of bedrock in drainage basins, with the notable exception of the drainage area of Arabia, India, and Southeast Asia that is affected by unusually radiogenic dissolved Sr from the Himalaya. We also demonstrate that the neodymium isotope compositions of suspended matter in rivers as well as clastic sediments deposited along the ocean margins decrease linearly with the bedrock ages of river drainage basins and large-scale continental drainage regions, as determined from digital geologic maps. These correlations are used to calculate the present-day input of dissolved Sr (4.7 × 1010 mol yr−1, 87Sr/86Sr of ∼0.7111) and particulate Nd isotopes (ɛNd of approximately −7.3 ± 2.2) to the oceans. The fact that the regionally averaged ɛNd of the global detrital input to the global coastal ocean is identical to globally averaged seawater (ɛNd of −7.2 ± 0.5) lends credence to the importance of “boundary exchange” for the Nd isotope composition of water masses. Regional biases in source areas of detrital matter and runoff are reflected by the observation that the average age of global bedrock, weighted according to the riverine suspended sediment flux, is significantly younger (∼336 Myr) than the age of global bedrock weighted according to water discharge (394 Myr), which is younger than the average bedrock age of the nonglaciated, exorheic portions of the continents (453 Myr). The observation that the bedrock age weighted according to Sr flux is younger (339 Myr) than that weighted according to water flux reflects the disproportionate contribution from young sedimentary and volcanic rocks to the dissolved Sr load. Neither the isotope composition of the dissolved nor the particulate continental inputs to the ocean provide unbiased perspectives of the lithologic makeup of the Earth's surface. Temporal changes in bedrock geology as well as the shifting focal points of physical erosion and water discharge will undoubtedly have exerted strong controls on temporal and spatial changes in the isotope chemistry of past global runoff and thus seawater.NSF grants EAR‐ 0125873, EAR‐0519387, and OCE‐0851015 to B.P.‐E. and a CNRS‐funded “poste rouge” position for B.P.‐E. at the Observatoire Midi‐Pyrénées in Toulouse supported this work