Classification and analysis of emission-line galaxies using mean field independent component analysis

We present an analysis of the optical spectra of narrow emission-line galaxies, based on mean field independent component analysis (MFICA). Samples of galaxies were drawn from the Sloan Digital Sky Survey (SDSS) and used to generate compact sets of `continuum' and `emission-line' component spectra. These components can be linearly combined to reconstruct the observed spectra of a wider sample of galaxies. Only 10 components - five continuum and five emission line - are required to produce accurate reconstructions of essentially all narrow emission-line galaxies; the median absolute deviations of the reconstructed emission-line fluxes, given the signal-to-noise ratio (S/N) of the observed spectra, are 1.2-1.8 sigma for the strong lines. After applying the MFICA components to a large sample of SDSS galaxies we identify the regions of parameter space that correspond to pure star formation and pure active galactic nucleus (AGN) emission-line spectra, and produce high S/N reconstructions of these spectra. The physical properties of the pure star formation and pure AGN spectra are investigated by means of a series of photoionization models, exploiting the faint emission lines that can be measured in the reconstructions. We are able to recreate the emission line strengths of the most extreme AGN case by assuming the central engine illuminates a large number of individual clouds with radial distance and density distributions, f(r) ~ r^gamma and g(n) ~ n^beta, respectively. The best fit is obtained with gamma = -0.75 and beta = -1.4. From the reconstructed star formation spectra we are able to estimate the starburst ages. These preliminary investigations serve to demonstrate the success of the MFICA-based technique in identifying distinct emission sources, and its potential as a tool for the detailed analysis of the physical properties of galaxies in large-scale surveys.Comment: MNRAS accepted. 29 pages, 24 figures, 3 table

Interpreting the Ionization Sequence in AGN Emission-Line Spectra

We investigate the physical cause of the great range in the ionization level seen in the spectra of narrow lined active galactic nuclei (AGN). Mean field independent component analysis identifies examples of individual SDSS galaxies whose spectra are not dominated by emission due to star formation (SF), which we designate as AGN. We assembled high S/N ratio composite spectra of a sequence of these AGN defined by the ionization level of their narrow-line regions (NLR), extending down to very low-ionization cases. We used a local optimally emitting cloud (LOC) model to fit emission-line ratios in this AGN sequence. These included the weak lines that can be measured only in the co-added spectra, providing consistency checks on strong line diagnostics. After integrating over a wide range of radii and densities our models indicate that the radial extent of the NLR is the major parameter in determining the position of high to moderate ionization AGN along our sequence, providing a physical interpretation for their systematic variation. Higher ionization AGN contain optimally emitting clouds that are more concentrated towards the central continuum source than in lower ionization AGN. Our LOC models indicate that for the objects that lie on our AGN sequence, the ionizing luminosity is anticorrelated with the NLR ionization level, and hence anticorrelated with the radial concentration and physical extent of the NLR. A possible interpretation that deserves further exploration is that the ionization sequence might be an age sequence where low ionization objects are older and have systematically cleared out their central regions by radiation pressure. We consider that our AGN sequence instead represents a mixing curve of SF and AGN spectra, but argue that while many galaxies do have this type of composite spectra, our AGN sequence appears to be a special set of objects with negligible SF excitation.Comment: 57 pages; 18 figures, accepted by MNRA

Triacylglycerol synthesis during nitrogen stress involves the prokaryotic lipid synthesis pathway and acyl chain remodeling in the microalgae \u3ci\u3eCoccomyxa subellipsoidea\u3c/i\u3e

Triglyceride (TAG) synthesis during nitrogen starvation and recovery was addressed using Coccomyxa subellipsoidea by analyzing acylchain composition and redistribution using a bioreactor-controlled time course. Galactolipids, phospholipids and TAGs were profiled using liquid chromatography tandem mass spectroscopy (LC–MS/MS). TAG levels increased linearly through 10 days of N starvation to a final concentration of 12.6% dry weight (DW), while chloroplast membrane lipids decreased from 5% to 1.5% DW. The relative quantities of TAG molecular species, differing in acyl chain length and glycerol backbone position, remained unchanged from 3 to 10 days of N starvation. Six TAG species comprised approximately half the TAG pool. An average of 16.5% of the acyl chains had two or more double bonds consistent with their specific transfer from membrane lipids to TAGs during N starvation. The addition of nitrate following 10 days of N starvation resulted in a dramatic shift from chloroplast-derived to endoplasmic reticulum-derived galactolipids (from \u3c12% to \u3e40%). A model for TAG synthesis in C. subellipsoidea was developed based on the acquired data and known plant pathways and data presented

Carbon and Acyl Chain Flux during Stress-induced Triglyceride Accumulation by Stable Isotopic Labeling of the Polar Microalga \u3ci\u3eCoccomyxa subellipsoidea\u3c/i\u3e C169

Deriving biofuels and other lipoid products from algae is a promising future technology directly addressing global issues of atmospheric CO2 balance. To better understand the metabolism of triglyceride synthesis in algae, we examined their metabolic origins in the model species, Coccomyxa subellipsoidea C169, using stable isotopic labeling. Labeling patterns arising from [U-13C]glucose, 13CO2, or D2O supplementation were analyzed by GC-MS and/or LC-MS over time courses during nitrogen starvation to address the roles of catabolic carbon recycling, acyl chain redistribution, and de novo fatty acid (FA) synthesis during the expansion of the lipid bodies. The metabolic origin of stress-induced triglyceride was found to be a continuous 8:2 ratio between de novo synthesized FA and acyl chain transfer from pre-stressed membrane lipids with little input from lipid remodeling. Membrane lipids were continually synthesized with associated acyl chain editing during nitrogen stress, in contrast to an overall decrease in total membrane lipid. The incorporation rates of de novo synthesized FA into lipid classes were measured over a time course of nitrogen starvation. The synthesis of triglycerides, phospholipids, and galactolipids followed a two-stage pattern where nitrogen starvation resulted in a 2.5-fold increase followed by a gradual decline. Acyl chain flux into membrane lipids was dominant in the first stage followed by triglycerides. These data indicate that the level of metabolic control that determines acyl chain flux between membrane lipids and triglycerides during nitrogen stress relies primarily on the Kennedy pathway and de novo FA synthesis with limited, defined input from acyl editing reactions

Triacylglycerol synthesis during nitrogen stress involves the prokaryotic lipid synthesis pathway and acyl chain remodeling in the microalgae \u3ci\u3eCoccomyxa subellipsoidea\u3c/i\u3e

Triglyceride (TAG) synthesis during nitrogen starvation and recovery was addressed using Coccomyxa subellipsoidea by analyzing acylchain composition and redistribution using a bioreactor-controlled time course. Galactolipids, phospholipids and TAGs were profiled using liquid chromatography tandem mass spectroscopy (LC–MS/MS). TAG levels increased linearly through 10 days of N starvation to a final concentration of 12.6% dry weight (DW), while chloroplast membrane lipids decreased from 5% to 1.5% DW. The relative quantities of TAG molecular species, differing in acyl chain length and glycerol backbone position, remained unchanged from 3 to 10 days of N starvation. Six TAG species comprised approximately half the TAG pool. An average of 16.5% of the acyl chains had two or more double bonds consistent with their specific transfer from membrane lipids to TAGs during N starvation. The addition of nitrate following 10 days of N starvation resulted in a dramatic shift from chloroplast-derived to endoplasmic reticulum-derived galactolipids (from \u3c12% to \u3e40%). A model for TAG synthesis in C. subellipsoidea was developed based on the acquired data and known plant pathways and data presented

Interpreting the Ionization Sequence in Star-Forming Galaxy Emission-Line Spectra

High ionization star forming (SF) galaxies are easily identified with strong emission line techniques such as the BPT diagram, and form an obvious ionization sequence on such diagrams. We use a locally optimally emitting cloud model to fit emission line ratios that constrain the excitation mechanism, spectral energy distribution, abundances and physical conditions along the star-formation ionization sequence. Our analysis takes advantage of the identification of a sample of pure star-forming galaxies, to define the ionization sequence, via mean field independent component analysis. Previous work has suggested that the major parameter controlling the ionization level in SF galaxies is the metallicity. Here we show that the observed SF- sequence could alternatively be interpreted primarily as a sequence in the distribution of the ionizing flux incident on gas spread throughout a galaxy. Metallicity variations remain necessary to model the SF-sequence, however, our best models indicate that galaxies with the highest and lowest observed ionization levels (outside the range -0.37 < log [O III]/H\b{eta} < -0.09) require the variation of an additional physical parameter other than metallicity, which we determine to be the distribution of ionizing flux in the galaxy.Comment: 41 pages, 17 figures, 9 tables, accepted to MNRA

Using connectivity-based real-time fMRI neurofeedback to modulate attentional and resting state networks in people with high trait anxiety

High levels of trait anxiety are associated with impaired attentional control, changes in brain activity during attentional control tasks and altered network resting state functional connectivity (RSFC). Specifically, dorsolateral prefrontal cortex to anterior cingulate cortex (DLPFC - ACC) functional connectivity, thought to be crucial for effective and efficient attentional control, is reduced in high trait anxious individuals. The current study examined the potential of connectivity-based real-time functional magnetic imaging neurofeedback (rt-fMRI-nf) for enhancing DLPFC - ACC functional connectivity in trait anxious individuals. We specifically tested if changes in DLPFC - ACC connectivity were associated with reduced anxiety levels and improved attentional control. Thirty-two high trait anxious participants were assigned to either an experimental group (EG), undergoing veridical rt-fMRI-nf, or a control group (CG) that received sham (yoked) feedback. RSFC (using resting state fMRI), anxiety levels and Stroop task performance were assessed pre- and post-rt-fMRI-nf training. Post-rt-fMRI-nf training, relative to the CG, the EG showed reduced anxiety levels and increased DLPFC-ACC functional connectivity as well as increased RSFC in the posterior default mode network. Moreover, in the EG, changes in DLPFC - ACC functional connectivity during rt-fMRI-nf training were associated with reduced anxiety levels. However, there were no group differences in Stroop task performance. We conclude that rt-fMRI-nf targeting DLPFC - ACC functional connectivity can alter network connectivity and interactions and is a feasible method for reducing trait anxiety

It Takes a Village: Understanding the Collective Security Efficacy of Employee Groups

An organization’s ability to successfully manage information security incidents is determined by the actions of its employees, as well as the actions of various groups of employees within its organizational boundaries. To date, information security research has primarily focused on individual-level phenomena and has not yet explored group-level phenomena such as how employee groups recognize and respond to security incidents in a way that is consistent with the organization’s security goals and objectives. The current study addresses this gap, thereby answering the research call for group-level security research perspectives. The present study explores how employee groups formulate their collective security efficacy, which influences how group members recognize and respond to information security incidents. Using a case study of a large healthcare research organization (HRO), we analyze two security incidents, a malware attack, and a physical security breach, to identify a unique set of ecological and social properties of employee groups that are salient to their collective security efficacy