Labor Migration and Social Networks Participation: Evidence from Southern Mozambique

This paper investigates how social networks in poor developing settings are af- fected if people migrate. By using an unique household survey from two southern regions in Mozambique, we test the role of labor mobility in shaping participation in groups and social networks by migrant sending households in village economies at origin. We find that households with successful migrants (i.e. those receiving either remittances or return migration) engage more in community based social networks. Our findings are robust to alternative definitions of social interaction and to endogeneity concerns suggesting that stable migration ties and higher income stability through remittances may decrease participation constraints and increase household commitment in cooperative arrangements in migrant-sending communities.International Migration, Social Capital, Networks, Group Participation, Mozambique

The impact of family size and sibling structure on the great Mexico-USA migration

We investigate the impact of fertility and demographic factors on the Great Mexico-USA immigration by assessing the causal effects of sibship size and structure on migration decisions within the household. We use a rich demographic survey on the population of Mexico and exploit presumably exogenous variation in family size induced by biological fertility and infertility shocks. We further exploit cross-sibling differences to identify the effects of birth order, siblings' sex, and siblings' ages on migration. We find that large families per se do not boost offspring's emigration. However, the likelihood of migrating is not equally distributed within a household. It is higher for sons and decreases sharply with birth order. The female migration disadvantage also varies with sibling composition by age and gender

The impact of family size and sibling structure on the great Mexico–USA migration

We investigate the impact of fertility and demographic factors on the Great Mexico\u2013USA immigration by assessing the causal effects of sibship size and structure on migration decisions within the household. We use a rich demographic survey on the population of Mexico and exploit presumably exogenous variation in family size induced by biological fertility and infertility shocks. We further exploit cross-sibling differences to identify the effects of birth order, siblings\u2019 sex, and siblings\u2019 ages on migration. We find that large families per se do not boost offspring\u2019s emigration. However, the likelihood of migrating is not equally distributed within a household. It is higher for sons and decreases sharply with birth order. The female migration disadvantage also varies with sibling composition by age and gender

Experimental investigation on tensile and shear bond behaviour of Basalt-FRCM composites for strengthening calcarenite masonry elements

The use of Fabric Reinforced Cementitious Matrix (FRCM) composites for structural retrofit has seen an increased interest among the scientific community, during the last decade. Various studies have revealed their effectiveness as external retrofitting technique of masonry elements, offering numerous advantages respect to the well know Fibre Reinforced Polymer (FRP) in terms of compatibility with masonry support, reversibility of intervention and sustainability. Despite the growing use, the characterization of FRCM mechanical behaviour is still an open issue, due to numerous uncertainties involved in test set-up adopted and fibre-mortar combination. The proposed experimental study aims to investigate the tensile and shear bond behaviour of Basalt-FRCM for strengthening calcarenite masonry elements. Calcarenite is a natural stone with sedimentary origin and it is widely present in existing buildings of the Mediterranean areas. Direct tensile tests are performed on two types of Basalt-FRCM coupons, with cement-based and lime-based mortar, adopting two different test-set-up based on clamping and clevis grip methods. Moreover, double shear bond tests are carried out to evaluate the adhesion properties of the two types of Basalt-FRCM with calcarenite support. Experimental outcomes are compared in terms of stress-strain curves, evaluating the influence of mortar grade and test set-up on the mechanical performances of Basalt-FRCM composites. The comparisons provide information about the mechanical stress transfer phenomena that occur at the fibre-to-matrix and FRCM-to-substrate interface level and the failure modes

Numerical Modelling of the Constitutive Behaviour of FRCM Composites through the Use of Truss Elements

The modeling of the mechanical behavior of Fabric Reinforced Cementitious Matrix (FRCM) composites is a difficult task due to the complex mechanisms established at the fibre-matrix and composite-support interface level. Recently, several modeling approaches have been proposed to simulate the mechanical response of FRCM strengthening systems, however a simple and reliable procedure is still missing. In this paper, two simplified numerical models are proposed to simulate the tensile and shear bond behavior of FRCM composites. Both models take advantage of truss and non-linear spring elements to simulate the material components and the interface. The proposed approach enables us to deduce the global mechanical response in terms of stress-strain or stress-slip relations. The accuracy of the proposed models is validated against the experimental benchmarks available in the literature

Identification of Chimera using Machine Learning

Chimera state refers to coexistence of coherent and non-coherent phases in identically coupled dynamical units found in various complex dynamical systems. Identification of Chimera, on one hand is essential due to its applicability in various areas including neuroscience, and on other hand is challenging due to its widely varied appearance in different systems and the peculiar nature of its profile. Therefore, a simple yet universal method for its identification remains an open problem. Here, we present a very distinctive approach using machine learning techniques to characterize different dynamical phases and identify the chimera state from given spatial profiles generated using various different models. The experimental results show that the performance of the classification algorithms varies for different dynamical models. The machine learning algorithms, namely random forest, oblique random forest based on tikhonov, parallel-axis split and null space regularization achieved more than $96\%$ accuracy for the Kuramoto model. For the logistic-maps, random forest and tikhonov regularization based oblique random forest showed more than $90\%$ accuracy, and for the H\'enon-Map model, random forest, null-space and axis-parallel split regularization based oblique random forest achieved more than $80\%$ accuracy. The oblique random forest with null space regularization achieved consistent performance (more than $83\%$ accuracy) across different dynamical models while the auto-encoder based random vector functional link neural network showed relatively lower performance. This work provides a direction for employing machine learning techniques to identify dynamical patterns arising in coupled non-linear units on large-scale, and for characterizing complex spatio-temporal patterns in real-world systems for various applications.Comment: 20 Pages, 4 Figures; Comments welcom

The role of ecotypic variation and the environment on biomass and nitrogen in a dominant prairie grass

Citation: Mendola, M. L., Baer, S. G., Johnson, L. C., & Maricle, B. R. (2015). The role of ecotypic variation and the environment on biomass and nitrogen in a dominant prairie grass. Ecology, 96(9), 2433-2445. doi:10.1890/14-1492.1Knowledge of the relative strength of evolution and the environment on a phenotype is required to predict species responses to environmental change and decide where to source plant material for ecological restoration. This information is critically needed for dominant species that largely determine the productivity of the central U.S. grassland. We established a reciprocal common garden experiment across a longitudinal gradient to test whether ecotypic variation interacts with the environment to affect growth and nitrogen (N) storage in a dominant grass. We predicted plant growth would increase from west to east, corresponding with increasing precipitation, but differentially among ecotypes due to local adaptation in all ecotypes and a greater range of growth response in ecotypes originating from west to east. We quantified aboveground biomass, root biomass, belowground net primary production (BNPP), root C:N ratio, and N storage in roots of three ecotypes of Andropogon gerardii collected from and reciprocally planted in central Kansas, eastern Kansas, and southern Illinois. Only the ecotype from the most mesic region (southern Illinois) exhibited more growth from west to east. There was evidence for local adaptation in the southern Illinois ecotype by means of the local vs. foreign contrast within a site and the home vs. away contrast when growth in southern Illinois was compared to the most distant site in central Kansas. Root biomass of the eastern Kansas ecotype was higher at home than at either away site. The ecotype from the driest region, central Kansas, exhibited the least response across the environmental gradient, resulting in a positive relationship between the range of biomass response and precipitation in ecotype region of origin. Across all sites, ecotypes varied in root C: N ratio (highest in the driest-origin ecotype) and N storage in roots (highest in the most mesic-origin ecotype). The low and limited range of biomass, higher C: N ratio of roots, and lower N storage in the central Kansas ecotype relative to the southern Illinois ecotype suggests that introducing ecotypes of A. gerardii from much drier regions into highly mesic prairie would reduce productivity and alter belowground ecosystem processes under a wide range of conditions

The role of copper (Ii) on kininogen binding to tropomyosin in the presence of a histidine–proline-rich peptide

The antiangiogenic activity of the H/P domain of histidine–proline-rich glycoprotein is mediated by its binding with tropomyosin, a protein exposed on endothelial cell-surface during the angiogenic switch, in presence of zinc ions. Although it is known that copper ion serum concentration is significantly increased in cancer patients, its role in the interaction of H/P domain with tropomyosin, has not yet been studied. In this paper, by using ELISA assay, we determined the modulating effect of TetraHPRG peptide, a sequence of 20 aa belonging to H/P domain, on the binding of Kininogen (HKa) with tropomyosin, both in absence and presence of copper and zinc ions. A potentiometric study was carried out to characterize the binding mode adopted by metal ions with TetraHPRG, showing the formation of complex species involving imidazole amide nitrogen atoms in metal binding. Moreover, circular dichroism showed a conformational modification of ternary systems formed by TetraHPRG, HKa and copper or zinc. Interestingly, slight pH variation influenced the HKa-TetraHPRG-tropomyosin binding. All these results indicate that both metal ions are crucial in the interaction between TetraHPRG, tropomyosin and HKa