Feature Selection of Post-Graduation Income of College Students in the United States

This study investigated the most important attributes of the 6-year post-graduation income of college graduates who used financial aid during their time at college in the United States. The latest data released by the United States Department of Education was used. Specifically, 1,429 cohorts of graduates from three years (2001, 2003, and 2005) were included in the data analysis. Three attribute selection methods, including filter methods, forward selection, and Genetic Algorithm, were applied to the attribute selection from 30 relevant attributes. Five groups of machine learning algorithms were applied to the dataset for classification using the best selected attribute subsets. Based on our findings, we discuss the role of neighborhood professional degree attainment, parental income, SAT scores, and family college education in post-graduation incomes and the implications for social stratification.Comment: 14 pages, 6 tables, 3 figure

From evidence-base to practice: implementation of the Nurse Family Partnership programme in England

The aims of this article are to highlight the issues that are relevant to the implementation of a rigorously evidence-based programme of support, the Nurse Family Partnership programme, into a national system of care. Methods used are semi-structured interviews with families in receipt of the programme in the first 10 sites, with the nursing staff, with members of the central team guiding the initiative and with other professionals. Analyses of data collected during programme delivery evaluate fidelity of delivery. The results indicate that the programme is perceived in a positive light and take-up is high, with delivery close to the stated US objectives. Issues pertaining to sustainability are highlighted - in particular, local concerns about cost set against long-term rather than immediate gains. However, local investment is predominantly strong, with creative methods being planned for the future. Overall, the study shows that within an NHS system of care it is possible to deliver a targeted evidence-based programme

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Influence of severe plastic deformation on the precipitation hardening of a FeSiTi steel

The combined strengthening effects of grain refinement and high precipitated volume fraction (~6at.%) on the mechanical properties of FeSiTi alloy subjected to SPD processing prior to aging treatment were investigated by atom probe tomography and scanning transmission electron microscopy. It was shown that the refinement of the microstructure affects the precipitation kinetics and the spatial distribution of the secondary hardening intermetallic phase, which was observed to nucleate heterogeneously on dislocations and sub-grain boundaries. It was revealed that alloys successively subjected to these two strengthening mechanisms exhibit a lower increase in mechanical strength than a simple estimation based on the summation of the two individual strengthening mechanisms

The chemistry of protoplanetary fragments formed via gravitational instabilities

In this paper, we model the chemical evolution of a 0.25 M$_{\odot}$ protoplanetary disc surrounding a 1 M$_{\odot}$ star that undergoes fragmentation due to self-gravity. We use Smoothed Particle Hydrodynamics including a radiative transfer scheme, along with time-dependent chemical evolution code to follow the composition of the disc and resulting fragments over approximately 4000 yrs. Initially, four quasi-stable fragments are formed, of which two are eventually disrupted by tidal torques in the disc. From the results of our chemical modelling, we identify species that are abundant in the fragments (e.g. H$_{\rm 2}$O, H$_{\rm 2}$S, HNO, N$_{\rm 2}$, NH$_{\rm 3}$, OCS, SO), species that are abundant in the spiral shocks within the disc (e.g. CO, CH$_{\rm 4}$, CN, CS, H$_{\rm 2}$CO), and species which are abundant in the circumfragmentary material (e.g. HCO$^{\rm +}$). Our models suggest that in some fragments it is plausible for grains to sediment to the core before releasing their volatiles into the planetary envelope, leading to changes in, e.g., the C/O ratio of the gas and ice components. We would therefore predict that the atmospheric composition of planets generated by gravitational instability should not necessarily follow the bulk chemical composition of the local disc material

First Evidence of Dinosaurian Secondary Cartilage in the Post-Hatching Skull of Hypacrosaurus stebingeri (Dinosauria, Ornithischia)

Bone and calcified cartilage can be fossilized and preserved for hundreds of millions of years. While primary cartilage is fairly well studied in extant and fossilized organisms, nothing is known about secondary cartilage in fossils. In extant birds, secondary cartilage arises after bone formation during embryonic life at articulations, sutures and muscular attachments in order to accommodate mechanical stress. Considering the phylogenetic inclusion of birds within the Dinosauria, we hypothesized a dinosaurian origin for this “avian” tissue. Therefore, histological thin sectioning was used to investigate secondary chondrogenesis in disarticulated craniofacial elements of several post-hatching specimens of the non-avian dinosaur Hypacrosaurus stebingeri (Ornithischia, Lambeosaurinae). Secondary cartilage was found on three membrane bones directly involved with masticatory function: (1) as nodules on the dorso-caudal face of a surangular; and (2) on the bucco-caudal face of a maxilla; and (3) between teeth as islets in the alveolar processes of a dentary. Secondary chondrogenesis at these sites is consistent with the locations of secondary cartilage in extant birds and with the induction of the cartilage by different mechanical factors - stress generated by the articulation of the quadrate, stress of a ligamentous or muscular insertion, and stress of tooth formation. Thus, our study reveals the first evidence of “avian” secondary cartilage in a non-avian dinosaur. It pushes the origin of this “avian” tissue deep into dinosaurian ancestry, suggesting the creation of the more appropriate term “dinosaurian” secondary cartilage

A multi-scale brain map derived from whole-brain volumetric reconstructions

Animal nervous system organization is crucial for all body functions and its disruption can lead to severe cognitive and behavioural impairment1. This organization relies on features across scales—from the localization of synapses at the nanoscale, through neurons, which possess intricate neuronal morphologies that underpin circuit organization, to stereotyped connections between different regions of the brain2. The sheer complexity of this organ means that the feat of reconstructing and modelling the structure of a complete nervous system that is integrated across all of these scales has yet to be achieved. Here we present a complete structure–function model of the main neuropil in the nematode Caenorhabditis elegans—the nerve ring—which we derive by integrating the volumetric reconstructions from two animals with corresponding3 synaptic and gap-junctional connectomes. Whereas previously the nerve ring was considered to be a densely packed tract of neural processes, we uncover internal organization and show how local neighbourhoods spatially constrain and support the synaptic connectome. We find that the C. elegans connectome is not invariant, but that a precisely wired core circuit is embedded in a background of variable connectivity, and identify a candidate reference connectome for the core circuit. Using this reference, we propose a modular network architecture of the C. elegans brain that supports sensory computation and integration, sensorimotor convergence and brain-wide coordination. These findings reveal scalable and robust features of brain organization that may be universal across phyla

New 10Be exposure ages improve Holocene ice sheet thinning history near the grounding line of Pope Glacier, Antarctica

Evidence for the timing and pace of past grounding line retreat of the Thwaites Glacier system in the Amundsen Sea embayment (ASE) of Antarctica provides constraints for models that are used to predict the future trajectory of the West Antarctic Ice Sheet (WAIS). Existing cosmogenic nuclide surface exposure ages suggest that Pope Glacier, a former tributary of Thwaites Glacier, experienced rapid thinning in the early to mid-Holocene. There are relatively few exposure ages from the lower ice-free sections of Mount Murphy (< 300 m asl) that are uncomplicated by either nuclide inheritance or scattering due to localised topographic complexities; this makes the trajectory for the latter stages of deglaciation uncertain. This paper presents 12 new 10Be exposure ages from erratic cobbles collected from the western flank of Mt Murphy, within 160 m of the modern ice surface and 1 km from the present grounding line. The ages comprise two tightly clustered populations with mean deglaciation ages of 7.1 ± 0.1 ka and 6.4 ± 0.1 ka (1SE). Linear regression analysis applied to the age-elevation array of all available exposure ages from Mt Murphy indicates that the median rate of thinning of Pope Glacier was 0.27 m yr-1 between 8.1–6.3 ka, occurring 1.5 times faster than previously thought. Furthermore, this analysis better constrains the uncertainty (95 % confidence interval) in the timing of deglaciation at the base of the Mt Murphy vertical profile (~80 m above the modern ice surface), shifting it to earlier in the Holocene (from 5.2 ± 0.7 ka to 6.3 ± 0.4 ka). Taken together, the results presented here suggest that early–mid Holocene thinning of Pope Glacier occurred over a shorter interval than previously assumed and permit a longer duration over which subsequent late Holocene rethickening could have occurred

On the Dynamics of the Deployment of Renewable Energy Production Capacities

This chapter falls within the context of modeling the deployment of renewable en-ergy production capacities in the scope of the energy transition. This problem is addressed from an energy point of view, i.e. the deployment of technologies is seen as an energy investment under the constraint that an initial budget of non-renewable energy is provided. Using the Energy Return on Energy Investment (ERoEI) characteristics of technologies, we propose MODERN, a discrete-time formalization of the deployment of renewable energy production capacities. Be-sides showing the influence of the ERoEI parameter, the model also underlines the potential benefits of designing control strategies for optimizing the deployment of production capacities, and the necessity to increase energy efficiency.Peer reviewe

A novel pathway producing dimethylsulphide in bacteria is widespread in soil environments

The volatile compound dimethylsulphide (DMS) is important in climate regulation, the sulphur cycle and signalling to higher organisms. Microbial catabolism of the marine osmolyte dimethylsulphoniopropionate (DMSP) is thought to be the major biological process generating DMS. Here we report the discovery and characterisation of the first gene for DMSP-independent DMS production in any bacterium. This gene, mddA, encodes a methyltransferase that methylates methanethiol (MeSH) and generates DMS. MddA functions in many taxonomically diverse bacteria including sediment-dwelling pseudomonads, nitrogen-fixing bradyrhizobia and cyanobacteria, and mycobacteria, including the pathogen Mycobacterium tuberculosis. The mddA gene is present in metagenomes from varied environments, being particularly abundant in soil environments, where it is predicted to occur in up to 76% of bacteria. This novel pathway may significantly contribute to global DMS emissions, especially in terrestrial environments, and could represent a shift from the notion that DMSP is the only significant precursor of DMS