The Returns to Migration: The Influence of Education and Migration Type

We show the impact of migration type on real wages over time. We create a migration and earnings history from the National Longitudinal Survey of Youth over the period 1979-2002. We estimate the effects of primary, onward, and two types of return migration on real wages using a panel data model with individual, location, and time fixed effects. Panel data are well suited for the study of the returns to U.S. internal migration because the influence of migration on wages has been found to occur years after the event. We differentiate return migration into two types: return to a location with ties that form a geographical anchor (home) and return to a prior place of work. We find that real wage growth varies by migration type. Education attainment is a significant factor in real wage growth. Our results show that onward migration is an important channel by which the monetary rewards to a college education are manifested.

Tropospheric ozone and CO over North Atlantic for the past decade

We investigate how declines in US emissions of CO and O3 precursors have impacted the lower free troposphere over the North Atlantic. We use seasonal observations for O3 and CO from the PICO-NARE project for the period covering 2001 to 2010. Observations are used to verify model output generated by the GEOS-Chem 3-D global chemical transport model. Additional satellite data for CO from AIRS/Aqua and for O3 from TES/Aura were also used to provide additional comparisons; particularly for fall, winter, and spring when PICO-NARE coverage is sparse. We find GEOS-Chem captures the seasonal cycle for CO and O3 well compared to PICO-NARE data. For CO, GEOS-Chem is biased low, particularly in spring which is in agreement with findings from previous studies. GEOS-Chem is 24.7 +/- 5.2 ppbv (1-σ) low compared to PICO-NARE summer CO data while AIRS is 14.2 +/- 6.6 ppbv high. AIRS does not show nearly as much variation as seen with GEOS-Chem or the Pico data, and goes from being lower than PICO-NARE data in winter and spring, to higher in summer and fall. Both TES and GEOS-Chem match the seasonal ozone cycle well for all seasons when compared with observations. Model results for O3 show GEOS-Chem is 6.67 +/- 2.63 ppbv high compared to PICO-NARE summer measurements and TES was 3.91 +/- 4.2 ppbv higher. Pico data, model results, and AIRS all show declines in CO and O3 for the summer period from 2001 to 2010. Limited availability of TES data prevents us from using it in trend analysis. For summer CO Pico, GEOS-Chem, and AIRS results show declines of 1.32, 0.368, and 0.548 ppbv/year respectively. For summer O3, Pico and GEOS-Chem show declines of -0.726 and -0.583 ppbv/year respectively. In other seasons, both model and AIRS show declining CO, particularly in the fall. GEOS-Chem results show a fall decline of 0.798 ppbv/year and AIRS shows a decline of 0.8372 ppbv/year. Winter and spring CO declines are 0.393 and 0.307 for GEOS-Chem, and 0.455 and 0.566 for AIRS. GEOS-Chem shows declining O3 in other seasons as well; with fall being the season of greatest decrease and winter being the least. Model results for fall, winter, and spring are 0.856, 0.117, and 0.570 ppbv/year respectively. Given the availability of data we are most confident in summer results and thus find that summer CO and O3 have declined in lower free troposphere of the North Atlantic region of the Azores. Sensitivity studies for CO and O3 at Pico were conducted by turning off North American fossil fuel emissions in GEOS-Chem. Model results show that North America fossil fuel emissions contribute 8.57 ppbv CO and 4.03 ppbv O3 to Pico. The magnitude of modeled trends declines in all seasons without North American fossil fuel emissions except for summer CO. The increase in summer CO declines may be due to a decline of 5.24 ppbv/year trend in biomass burning emissions over the study period; this is higher than the 2.33 ppbv/year North American anthropogenic CO model decline. Winter O3 is the only season which goes from showing a negative trend to a positive trend.

Atmospheric CO₂ response to volcanic eruptions: The role of ENSO, season, and variability

Tropical explosive volcanism is one of the most important natural factors that significantly impact the climate system and the carbon cycle on annual to multi-decadal time scales. The three largest explosive eruptions in the last 50�years�Agung, El Chichón, and Pinatubo�occurred in spring/summer in conjunction with El Niño events and left distinct negative signals in the observational temperature and CO2 records. However, confounding factors such as seasonal variability and El Niño-Southern Oscillation (ENSO) may obscure the forcing-response relationship. We determine for the first time the extent to which initial conditions, i.e., season and phase of the ENSO, and internal variability influence the coupled climate and carbon cycle response to volcanic forcing and how this affects estimates of the terrestrial and oceanic carbon sinks. Ensemble simulations with the Earth System Model (Climate System Model 1.4-carbon) predict that the atmospheric CO2 response is �60 larger when a volcanic eruption occurs during El Niño and in winter than during La Niña conditions. Our simulations suggest that the Pinatubo eruption contributed 11�±�6 to the 25�Pg terrestrial carbon sink inferred over the decade 1990�1999 and �2�±�1 to the 22�Pg oceanic carbon sink. In contrast to recent claims, trends in the airborne fraction of anthropogenic carbon cannot be detected when accounting for the decadal-scale influence of explosive volcanism and related uncertainties. Our results highlight the importance of considering the role of natural variability in the carbon cycle for interpretation of observations and for data-model intercomparison.

Development of dendritic tonic GABAergic inhibition regulates excitability and plasticity in CA1 pyramidal neurons

Synaptic plasticity rules change during development: while hippocampal synapses can be potentiated by a single action potential pairing protocol in young neurons, mature neurons require burst firing to induce synaptic potentiation. An essential component for spike timing-dependent plasticity is the backpropagating action potential (BAP). BAP along the dendrites can be modulated by morphology and ion channel composition, both of which change during late postnatal development. However it is unclear whether these dendritic changes can explain the developmental changes in synaptic plasticity induction rules. Here, we show that tonic GABAergic inhibition regulates dendritic action potential backpropagation in adolescent but not pre-adolescent CA1 pyramidal neurons. These developmental changes in tonic inhibition also altered the induction threshold for spike timing-dependent plasticity in adolescent neurons. This GABAergic regulatory effect upon backpropagation is restricted to distal regions of apical dendrites (>200 μm) and mediated by α5-containing GABA(A) receptors. Direct dendritic recordings demonstrate α5-mediated tonic GABA(A) currents in adolescent neurons which can modulate backpropagating action potentials. These developmental modulations in dendritic excitability could not be explained by concurrent changes in dendritic morphology. To explain our data, model simulations propose a distally-increasing or localized distal expression of dendritic α5 tonic inhibition in mature neurons. Overall, our results demonstrate that dendritic integration and plasticity in more mature dendrites are significantly altered by tonic α5 inhibition in a dendritic region-specific and developmentally-regulated manner.

The geography of large-scale land acquisitions: Analysing socio-ecological patterns of target contexts in the global South

This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

Synergistic User <-> Context Analytics

Various avours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semantically-rich insights from people's low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental (e.g. weather, infrastructure) and application-specific data, to better capture the interactions between users and their context, in addition to those among users. To illustrate our proposed concept of synergistic user <-> context analytics, we first provide some example use cases. Then, we present our ongoing work towards a synergistic analytics platform: a testbed, based on mobile crowdsensing and the Internet of Things (IoT), a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.

Computational fluid dynamics modelling in cardiovascular medicine.

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.

Relationship between dietary patterns and body mass index in Hispanic children ages 4--19 years of age

Background. In over 30 years, the prevalence of overweight for children and adolescents has increased across the United States (Barlow et al., 2007; Ogden, Flegal, Carroll, & Johnson, 2002). Childhood obesity is linked with adverse physiological and psychological issues in youth and affects ethnic/minority populations in disproportionate rates (Barlow et al., 2007; Butte et al., 2006; Butte, Cai, Cole, Wilson, Fisher, Zakeri, Ellis, & Comuzzie, 2007). More importantly, overweight in children and youth tends to track into adulthood (McNaughton, Ball, Mishra, & Crawford, 2008; Ogden et al., 2002). Childhood obesity affects body functions such as the cardiovascular, respiratory, gastrointestinal, and endocrine systems, including emotional health (Barlow et al., 2007, Ogden et al., 2002). Several dietary factors have been associated with the development of obesity in children; however, these factors have not been fully elucidated, especially in ethnic/minority children. In particular, few studies have been done to determine the effects of different meal patterns on the development of obesity in children. Purpose. The purpose of the study is to examine the relationships between daily proportions of energy consumed and energy derived from fat across breakfast, lunch, dinner, and snack, and obesity among Hispanic children and adolescents. Methods. A cross-sectional design was used to evaluate the relationship between dietary patterns and overweight status in Hispanic children and adolescents 4-19 years of age who participated in the Viva La Familia Study. The goal of the Viva La Familia Study was to evaluate genetic and environmental factors affecting childhood obesity and its co-morbidities in the Hispanic population (Butte et al., 2006, 2007). The study enrolled 1030 Hispanic children and adolescents from 319 families and examined factors related to increased body weight by focusing on a multilevel analysis of extensive sociodemographic, genetic, metabolic, and behavioral data. Baseline dietary intakes of the children were collected using 24-hour recalls, and body mass index was calculated from measured height and weight, and classified using the CDC standards. Dietary data were analyzed using a GEE population-averaged panel-data model with a cluster variable family identifier to include possible correlations within related data sets. A linear regression model was used to analyze associations of dietary patterns using possible covariates, and to examine the percentage of daily energy coming from breakfast, lunch, dinner, and snack while adjusting for age, sex, and BMI z-score. Random-effects logistic regression models were used to determine the relationship of the dietary variables with obesity status and to understand if the percent energy intake (%EI) derived from fat from all meals (breakfast, lunch, dinner, and snacks) affected obesity. Results. Older children (age 4-19 years) consumed a higher percent of energy at lunch and dinner and less percent energy from snacks compared to younger children. Age was significantly associated with percentage of total energy intake (%TEI) for lunch, as well as dinner, while no association was found by gender. Percent of energy consumed from dinner significantly differed by obesity status, with obese children consuming more energy at dinner (p = 0.03), but no associations were found between percent energy from fat and obesity across all meals. Conclusions. Information from this study can be used to develop interventions that target dietary intake patterns in obesity prevention programs for Hispanic children and adolescents. In particular, intervention programs for children should target dietary patterns with energy intake that is spread throughout the day and earlier in the day. These results indicate that a longitudinal study should be used to further explore the relationship of dietary patterns and BMI in this and other populations (Dubois et al., 2008; Rodriquez & Moreno, 2006; Thompson et al., 2005; Wilson et al., in review, 2008). ^

Heat flow values in the Sea of Okhotsk region

Tectonic structure and anomalous distributions of geophysical fields of the Sea of Okhotsk region are considered; the lack of reliable data on age of the lithosphere beneath basins of various origin in the Sea of Okhotsk is noted. Model calculations based on geological and geophysical data yielded 65 Ma (Cretaceous-Paleocene boundary) age for the Central Okhotsk rise underlain by the continental lithosphere. This estimate agrees with the age (the end of Cretaceous) derived from seismostratigraphic data. A comparative analysis of theoretical and measured heat flows in the Akademii Nauk Rise, underlain by the thinned continental crust, is performed. The analysis points to a higher (by 20%) value of the measured thermal background of the rise, which is consistent with high negative gradient of gravity anomalies in this area. Calculations yielded 36 Ma (Early Oligocene) age and lithosphere thickness of 50 km for the South Okhotsk depression, whose seafloor was formed by processes of back-arc spreading. The estimated age of the depression is supported by kinematic data on the region; the calculated thickness of the lithosphere coincides with the value estimated from data of magnetotelluric sounding here. This indicates that formation time (36 Ma) of the South Okhotsk depression was estimated correctly. Numerical modeling performed for determination of the basement age of rifting basins in the Sea of Okhotsk gave the following estimates: 18 Ma (Early Miocene) for the Deryugin Basin, 12 Ma (Middle Miocene) for the TINRO Basin, and 23 Ma (Late Oligocene) for the West Kamchatka Trough. These estimates agree with formation time (Oligocene-Quaternary) of the sedimentary cover in rifting basins of the Sea of Okhotsk derived from geological and geophysical data. Model temperature estimates are obtained for lithologic and stratigraphic boundaries of the sedimentary cover in the Deryugin and TINRO Basins and the West Kamchatka Trough; the temperature analysis indicates that the latter two structures are promising for oil and hydrocarbon gas generation; the West Kamchatka Trough possesses better reservoir properties compared to the TINRO and Deryugin Basins. The latter is promising for generation of hydrocarbon gas. Paleogeodynamic reconstructions of the Sea of Okhotsk region evolution are obtained for times of 90, 66, and 36 Ma on the base of kinematic, geomagnetic, structural, tectonic, geothermal, and other geological and geophysical data.

Global compilation of last glacial maximum oxygen isotopic ratios for planktonic and benthic foraminifera

We use the fully coupled atmosphere-ocean three-dimensional model of intermediate complexity iLOVECLIM to simulate the climate and oxygen stable isotopic signal during the Last Glacial Maximum (LGM, 21 000 yr). By using a model that is able to explicitly simulate the sensor (d18O), results can be directly compared with data from climatic archives in the different realms. Our results indicate that iLOVECLIM reproduces well the main feature of the LGM climate in the atmospheric and oceanic components. The annual mean d18O in precipitation shows more depleted values in the northern and southern high latitudes during the LGM. The model reproduces very well the spatial gradient observed in ice core records over the Greenland ice-sheet. We observe a general pattern toward more enriched values for continental calcite d18O in the model at the LGM, in agreement with speleothem data. This can be explained by both a general atmospheric cooling in the tropical and subtropical regions and a reduction in precipitation as confirmed by reconstruction derived from pollens and plant macrofossils. Data-model comparison for sea surface temperature indicates that iLOVECLIM is capable to satisfyingly simulate the change in oceanic surface conditions between the LGM and present. Our data-model comparison for calcite d18O allows investigating the large discrepancies with respect to glacial temperatures recorded by different microfossil proxies in the North Atlantic region. The results argue for a trong mean annual cooling between the LGM and present (>6°C), supporting the foraminifera transfer function reconstruction but in disagreement with alkenones and dinocyst reconstructions. The data-model comparison also reveals that large positive calcite d18O anomaly in the Southern Ocean may be explained by an important cooling, although the driver of this pattern is unclear. We deduce a large positive d18Osw anomaly for the north Indian Ocean that contrasts with a large negative d18Osw anomaly in the China Sea between the LGM and present. This pattern may be linked to changes in the hydrological cycle over these regions. Our simulation of the deep ocean suggests that changes in d18Osw between the LGM and present are not spatially homogenous. This is supported by reconstructions derived from pore fluids in deep-sea sediments. The model underestimates the deep ocean cooling thus biasing the comparison with benthic calcite d18O data. Nonetheless, our data-model comparison support a heterogeneous cooling of few degrees (2-4°C) in the LGM Ocean.

Can FDI promote export diversification and sophistication of host countries? : dynamic panel system GMM analysis

Recent trade literature highlights the importance of export diversification and upgrading in fostering faster and sustainable economic growth. This study investigates the impact of FDI inflow and stock on the level of export diversification and sophistication in host country's export baskets. By utilizing the dynamic panel data model, we find that the five-year lagged FDI inflow correlates positively with both export diversification and sophistication, and FDI stock makes the positive contribution to export sophistication. These findings provide support for the possibility of successful capabilities transfer to and building by local firms. We also find that these positive impacts of FDI exist only in developing countries.