648 research outputs found
The stability paradox : why expansion of education for women has not delayed age at first union or childbearing in Latin America
Despite substantial improvements in women's education, the age atwhich Latin American women marry (cohabit) or become mothers for the first time has barely decreased over the past four decades. We refer to this as the "stability paradox." We examine the relationship between years of schooling and transitions to first union or child, analyzing retrospective information from 50 cohorts of women born between 1940 and 1989 in 12 Latin American countries. Absolute and relative measures of schooling are compared. Data is drawn from 38 Demographic Health Surveys (DHS) conducted between 1986 and 2012 in these countries. Results show that expected postponement in family transitions due to educational expansion was offset by a rise in union formation and childbearing within strata of absolute education, but stayed approximately constant within strata of relative education. The relative measure of education retains the stratifying power of education but neutralizes any effect attached to a specific number of years of schooling and the learning skills associated with them. This is consistent with the idea that access to education in Latin America reproduces existing patterns of socioeconomic advantage, rather than creating a more equitable distribution of learning opportunities and outcomes
Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study
Pathological cerebral white matter changes in Alzheimer’s disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer’s disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer’s disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants’ diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer’s disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer’s disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer’s disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer’s disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer’s disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter
DALC: Distributed Automatic LSTM Customization for Fine-Grained Traffic Speed Prediction
Over the past decade, several approaches have been introduced for short-term
traffic prediction. However, providing fine-grained traffic prediction for
large-scale transportation networks where numerous detectors are geographically
deployed to collect traffic data is still an open issue. To address this issue,
in this paper, we formulate the problem of customizing an LSTM model for a
single detector into a finite Markov decision process and then introduce an
Automatic LSTM Customization (ALC) algorithm to automatically customize an LSTM
model for a single detector such that the corresponding prediction accuracy can
be as satisfactory as possible and the time consumption can be as low as
possible. Based on the ALC algorithm, we introduce a distributed approach
called Distributed Automatic LSTM Customization (DALC) to customize an LSTM
model for every detector in large-scale transportation networks. Our experiment
demonstrates that the DALC provides higher prediction accuracy than several
approaches provided by Apache Spark MLlib.Comment: 12 pages, 5 figures, the 34th International Conference on Advanced
Information Networking and Applications (AINA 2020), Springe
Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System
Recent advancement in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility
Dissolved noble gases and stable isotopes as tracers of preferential fluid flow along faults in the Lower Rhine Embayment, Germany
Groundwater in shallow unconsolidated sedimentary aquifers close to the Bornheim fault in the Lower Rhine Embayment (LRE), Germany, has relatively low δ2H and δ18O values in comparison to regional modern groundwater recharge, and 4He concentrations up to 1.7 × 10−4 cm3 (STP) g–1 ± 2.2 % which is approximately four orders of magnitude higher than expected due to solubility equilibrium with the atmosphere. Groundwater age dating based on estimated in situ production and terrigenic flux of helium provides a groundwater residence time of ∼107 years. Although fluid exchange between the deep basal aquifer system and the upper aquifer layers is generally impeded by confining clay layers and lignite, this study’s geochemical data suggest, for the first time, that deep circulating fluids penetrate shallow aquifers in the locality of fault zones, implying that sub-vertical fluid flow occurs along faults in the LRE. However, large hydraulic-head gradients observed across many faults suggest that they act as barriers to lateral groundwater flow. Therefore, the geochemical data reported here also substantiate a conduit-barrier model of fault-zone hydrogeology in unconsolidated sedimentary deposits, as well as corroborating the concept that faults in unconsolidated aquifer systems can act as loci for hydraulic connectivity between deep and shallow aquifers. The implications of fluid flow along faults in sedimentary basins worldwide are far reaching and of particular concern for carbon capture and storage (CCS) programmes, impacts of deep shale gas recovery for shallow groundwater aquifers, and nuclear waste storage sites where fault zones could act as potential leakage pathways for hazardous fluids
Influence of training status and exercise modality on pulmonary O2 uptake kinetics in pre-pubertal girls
The limited available evidence suggests that endurance training does not influence the pulmonary oxygen uptake (V(O)(2)) kinetics of pre-pubertal children. We hypothesised that, in young trained swimmers, training status-related adaptations in the V(O)(2) and heart rate (HR) kinetics would be more evident during upper body (arm cranking) than during leg cycling exercise. Eight swim-trained (T; 11.4 +/- 0.7 years) and eight untrained (UT; 11.5 +/- 0.6 years) girls completed repeated bouts of constant work rate cycling and upper body exercise at 40% of the difference between the gas exchange threshold and peak V(O)(2). The phase II V(O)(2) time constant was significantly shorter in the trained girls during upper body exercise (T: 25 +/- 3 vs. UT: 37 +/- 6 s; P < 0.01), but no training status effect was evident in the cycle response (T: 25 +/- 5 vs. UT: 25 +/- 7 s). The V(O)(2) slow component amplitude was not affected by training status or exercise modality. The time constant of the HR response was significantly faster in trained girls during both cycle (T: 31 +/- 11 vs. UT: 47 +/- 9 s; P < 0.01) and upper body (T: 33 +/- 8 vs. UT: 43 +/- 4 s; P < 0.01) exercise. The time constants of the phase II V(O)(2)and HR response were not correlated regardless of training status or exercise modality. This study demonstrates for the first time that swim-training status influences upper body V(O)(2) kinetics in pre-pubertal children, but that cycle ergometry responses are insensitive to such differences
Role of Symbiotic Auxotrophy in the Rhizobium-Legume Symbioses
Symbiotic auxotrophy occurs in both determinate pea and indeterminate bean nodules demonstrating its importance for bacteroid formation and nodule function in legumes with different developmental programmes. However, only small quantities of branched chain amino acids are needed and symbiotic auxotrophy did not occur in the Sinorhizobium meliloti-alfalfa symbiosis under the conditions measured. The contrasting symbiotic phenotypes of aap bra mutants inoculated on different legumes probably reflects altered timing of amino acid availability, development of symbiotic auxotrophy and nodule developmental programmes
Paleotemperature Proxies from Leaf Fossils Reinterpreted in Light of Evolutionary History
Present-day correlations between leaf physiognomic traits (shape and size) and climate are widely used to estimate paleoclimate using fossil floras. For example, leaf-margin analysis estimates paleotemperature using the modern relation of mean annual temperature (MAT) and the site-proportion of untoothed-leaf species (NT). This uniformitarian approach should provide accurate paleoclimate reconstructions under the core assumption that leaf-trait variation principally results from adaptive environmental convergence, and because variation is thus largely independent of phylogeny it should be constant through geologic time. Although much research acknowledges and investigates possible pitfalls in paleoclimate estimation based on leaf physiognomy, the core assumption has never been explicitly tested in a phylogenetic comparative framework. Combining an extant dataset of 21 leaf traits and temperature with a phylogenetic hypothesis for 569 species-site pairs at 17 sites, we found varying amounts of non-random phylogenetic signal in all traits. Phylogenetic vs. standard regressions generally support prevailing ideas that leaf-traits are adaptively responding to temperature, but wider confidence intervals, and shifts in slope and intercept, indicate an overall reduced ability to predict climate precisely due to the non-random phylogenetic signal. Notably, the modern-day relation of proportion of untoothed taxa with mean annual temperature (NT-MAT), central in paleotemperature inference, was greatly modified and reduced, indicating that the modern correlation primarily results from biogeographic history. Importantly, some tooth traits, such as number of teeth, had similar or steeper slopes after taking phylogeny into account, suggesting that leaf teeth display a pattern of exaptive evolution in higher latitudes. This study shows that the assumption of convergence required for precise, quantitative temperature estimates using present-day leaf traits is not supported by empirical evidence, and thus we have very low confidence in previously published, numerical paleotemperature estimates. However, interpreting qualitative changes in paleotemperature remains warranted, given certain conditions such as stratigraphically closely-spaced samples with floristic continuity
Immunomodulatory factors in cervicovaginal secretions from pregnant and non-pregnant women: A cross-sectional study
<p>Abstract</p> <p>Background</p> <p>Pregnant women are at an increased risk for HIV infection due to unknown biological causes. Given the strong effect of sex-hormones on the expression of immunomuodulatory factors, the central role of mucosal immunity in HIV pathogenesis and the lack of previous studies, we here tested for differences in immunomuodulatory factors in cervico-vaginal secretions between pregnant and non-pregnant women.</p> <p>Methods</p> <p>We compared concentrations of 39 immunomodulatory factors in cervicovaginal lavages (CVL) from 21 pregnant women to those of 24 non-pregnant healthy women from the US. We used Bonferroni correction to correct for multiple testing and linear regression modeling to adjust for possible confounding by plasma cytokine concentration, cervical ectopy, total protein concentration, and other possible confounders. Cervical ectopy was determined by planimetry. Concentration of immunomodulatory factors were measured by a multiplex assay, protein concentration by the Bradford Method.</p> <p>Results</p> <p>Twenty six (66%) of the 39 measured immunomodulatory factors were detectable in at least half of the CVL samples included in the study. Pregnant women had threefold lower CVL concentration of CCL22 (geometric mean: 29.6 pg/ml versus 89.7 pg/ml, p = 0.0011) than non-pregnant women. CVL CCL22 concentration additionally correlated negatively with gestational age (Spearman correlation coefficient [R<sub>S</sub>]: -0.49, p = 0.0006). These associations remained significant when corrected for multiple testing.</p> <p>CCL22 concentration in CVL was positively correlated with age and negatively correlated with time since last coitus and the size of cervical ectopy. However, none of these associations could explain the difference of CCL22 concentration between pregnant and non-pregnant women in this study, which remained significant in adjusted analysis.</p> <p>Conclusions</p> <p>In this study population, pregnancy is associated with reduced concentrations of CCL22 in cervicovaginal secretions. The role of CCL22 on HIV transmission should now be investigated in prospective studies.</p
Classification of river morphology and hydrology to support management and restoration
The work leading to this paper has received funding from the European Union’s FP7 programme under Grant Agreement No. 282656 (REFORM
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