The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation

Complex cognitive functions are widely recognized to be the result of a number of brain regions working together as large-scale networks. Recently, complex network analysis has been used to characterize various structural properties of the large scale network organization of the brain. For example, the human brain has been found to have a modular architecture i.e. regions within the network form communities (modules) with more connections between regions within the community compared to regions outside it. The aim of this study was to examine the modular and overlapping modular architecture of the brain networks using complex network analysis. We also examined the association between neighborhood level deprivation and brain network structure – modularity and grey nodes. We compared network structure derived from anatomical MRI scans of 42 middle-aged neurologically healthy men from the least (LD) and the most deprived (MD) neighborhoods of Glasgow with their corresponding random networks. Cortical morphological covariance networks were constructed from the cortical thickness derived from the MRI scans of the brain. For a given modularity threshold, networks derived from the MD group showed similar number of modules compared to their corresponding random networks, while networks derived from the LD group had more modules compared to their corresponding random networks. The MD group also had fewer grey nodes – a measure of overlapping modular structure. These results suggest that apparent structural difference in brain networks may be driven by differences in cortical thicknesses between groups. This demonstrates a structural organization that is consistent with a system that is less robust and less efficient in information processing. These findings provide some evidence of the relationship between socioeconomic deprivation and brain network topology

Smelly maps: the digital life of urban smellscapes

Smell has a huge influence over how we perceive places. Despite its importance, smell has been crucially overlooked by urban planners and scientists alike, not least because it is difficult to record and analyze at scale. One of the authors of this paper has ventured out in the urban world and conducted ``smellwalks'' in a variety of cities: participants were exposed to a range of different smellscapes and asked to record their experiences. As a result, smell-related words have been collected and classified, creating the first dictionary for urban smell. Here we explore the possibility of using social media data to reliably map the smells of entire cities. To this end, for both Barcelona and London, we collect geo-referenced picture tags from Flickr and Instagram, and geo-referenced tweets from Twitter. We match those tags and tweets with the words in the smell dictionary. We find that smell-related words are best classified in ten categories. We also find that specific categories (e.g., industry, transport, cleaning) correlate with governmental air quality indicators, adding validity to our study

The enumeration of finite rings

Let $p$ be a fixed prime. We show that the number of isomorphism classes of finite rings of order $p^n$ is $p^\alpha$, where $\alpha=\frac{4}{27}n^3+O(n^{5/2})$. This result was stated (with a weaker error term) by Kruse and Price in 1969; a problem with their proof was pointed out by Knopfmacher in 1973. We also show that the number of isomorphism classes of finite commutative rings of order $p^n$ is $p^\beta$, where $\beta=\frac{2}{27}n^3+O(n^{5/2})$. This result was stated (again with a weaker error term) by Poonen in 2008, with a proof that relies on the problematic step in Kruse and Price's argument.Comment: 31 pages. Change of title, revised appendix, and various other small changes since previous versio

Erratum to “Regularity theory for time-fractional advection-diffusion-reaction equations” [Comput. Math. Appl. 79 (2020) 947–961] (Computers and Mathematics with Applications (2020) 79(4) (947–961), (S0898122119304055), (10.1016/j.camwa.2019.08.008))

In this note, we correct the statement of Theorem 12 from the paper in the title above (McLean et al., 2020) and fill some gaps in the proof

Retrospective Barrier Placements for a Skunk Rabies Epizootic in NW Wyoming

Striped skunks (Mephitis mephitis) are the most important reservoir of rabies on the Great Plains. In August, 1988 a skunk rabies epizootic proceeded from the index case west of Cowley, WY. By 1991, epizootic had reached nearly all areas in the Shoshone River Basin (SRB), and it ended in 1993. This area and the remainder of the SRB had been previously considered rabies-free. The USDA\u27s Wildlife Services (WS) cooperated with state and local officials in a rabies monitoring and control program starting in 1990. Using information from the literature, signs, tracks, and radio-telemetry of normal and rabid skunks, WS decided to trap mainly riparian and irrigated agricultural habitats in the valley\u27s floor. Here, a mosaic of irrigation ditches (e.g., Buffalo Bill Cody\u27s circa 1908) was shown to be travel corridors for skunks. Trapped species (\u3e1,000 skunks) were sent to the Wyoming State Veterinary Laboratory for rabies testing using immuno-fluorescent of brain tissues. The study area extended from the Bighorn Canyon and Lake on the east up river to Buffalo Bill Reservoir on the west. The study area and subsequent epizootic encompassed a portion of the Shoshone River ~90 km in length and an area of ~ 85,000 ha (54 mi2). Traditional surveillance data composed \u3c10% of the sample -public referrals of suspiciously acting wildlife and road kills. We analyzed 215 rabid skunk locations and dates together with GIS hydrology and land use information. Hypothetical barriers were modeled using potential synergisms formed among restricted habitat, depopulation, and vaccine (if one had been available), combined with the natural epizootiology of this rabies strain with high virulence. Two dates for barrier locations were identified that may have halted the spreading epizootic: 1) before April 1989, when the rabies epizootic might have been limited to Polecat and Sage Creeks, and 2) June 1989, when the epizootic may have been stopped before it entered the majority of SRB including the larger population centers of Byron, Powell, and Cody

Retrospective Barrier Placements for a Skunk Rabies Epizootic in NW Wyoming

Striped skunks (Mephitis mephitis) are the most important reservoir of rabies on the Great Plains. In August, 1988 a skunk rabies epizootic proceeded from the index case west of Cowley, WY. By 1991, epizootic had reached nearly all areas in the Shoshone River Basin (SRB), and it ended in 1993. This area and the remainder of the SRB had been previously considered rabies-free. The USDA\u27s Wildlife Services (WS) cooperated with state and local officials in a rabies monitoring and control program starting in 1990. Using information from the literature, signs, tracks, and radio-telemetry of normal and rabid skunks, WS decided to trap mainly riparian and irrigated agricultural habitats in the valley\u27s floor. Here, a mosaic of irrigation ditches (e.g., Buffalo Bill Cody\u27s circa 1908) was shown to be travel corridors for skunks. Trapped species (\u3e1,000 skunks) were sent to the Wyoming State Veterinary Laboratory for rabies testing using immuno-fluorescent of brain tissues. The study area extended from the Bighorn Canyon and Lake on the east up river to Buffalo Bill Reservoir on the west. The study area and subsequent epizootic encompassed a portion of the Shoshone River ~90 km in length and an area of ~ 85,000 ha (54 mi2). Traditional surveillance data composed \u3c10% of the sample -public referrals of suspiciously acting wildlife and road kills. We analyzed 215 rabid skunk locations and dates together with GIS hydrology and land use information. Hypothetical barriers were modeled using potential synergisms formed among restricted habitat, depopulation, and vaccine (if one had been available), combined with the natural epizootiology of this rabies strain with high virulence. Two dates for barrier locations were identified that may have halted the spreading epizootic: 1) before April 1989, when the rabies epizootic might have been limited to Polecat and Sage Creeks, and 2) June 1989, when the epizootic may have been stopped before it entered the majority of SRB including the larger population centers of Byron, Powell, and Cody

Influence of pore-scale disorder on viscous fingering during drainage

We study viscous fingering during drainage experiments in linear Hele-Shaw cells filled with a random porous medium. The central zone of the cell is found to be statistically more occupied than the average, and to have a lateral width of 40% of the system width, irrespectively of the capillary number $Ca$. A crossover length $w_f \propto Ca^{-1}$ separates lower scales where the invader's fractal dimension $D\simeq1.83$ is identical to capillary fingering, and larger scales where the dimension is found to be $D\simeq1.53$. The lateral width and the large scale dimension are lower than the results for Diffusion Limited Aggregation, but can be explained in terms of Dielectric Breakdown Model. Indeed, we show that when averaging over the quenched disorder in capillary thresholds, an effective law $v\propto (\nabla P)^2$ relates the average interface growth rate and the local pressure gradient.Comment: 4 pages, 4 figures, submitted to Phys Rev Letter

A Review of Network and Computer Analysis of Epileptiform Discharge Free EEG to Characterize and Detect Epilepsy.

Objectives. There is emerging evidence that network/computer analysis of epileptiform discharge free electroencephalograms (EEGs) can be used to detect epilepsy, improve diagnosis and resource use. Such methods are automated and can be performed on shorter recordings of EEG. We assess the evidence and its strength in the area of seizure detection from network/computer analysis of epileptiform discharge free EEG. Methods. A scoping review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance was conducted with a literature search of Embase, Medline and PsychINFO. Predesigned inclusion/exclusion criteria were applied to selected articles. Results. The initial search found 3398 articles. After duplicate removal and screening, 591 abstracts were reviewed, 64 articles were selected and read leading to 20 articles meeting the requisite inclusion/exclusion criteria. These were 9 reports and 2 cross-sectional studies using network analysis to compare and/or classify EEG. One review of 17 reports and 10 cross-sectional studies only aimed to classify the EEGs. One cross-sectional study discussed EEG abnormalities associated with autism. Conclusions. Epileptiform discharge free EEG features derived from network/computer analysis differ significantly between people with and without epilepsy. Diagnostic algorithms report high accuracies and could be clinically useful. There is a lack of such research within the intellectual disability (ID) and/or autism populations, where epilepsy is more prevalent and there are additional diagnostic challenges

1-1.4 Micron Spectral Atlas of Stars

We present a catalog of J-band (1.08 um to 1.35 um) stellar spectra at low resolution (R ~ 400). The targets consist of 105 stars ranging in spectral type from O9.5 to M7 and luminosity classes I through V. The relatively featureless spectra of hot stars, earlier than A4, can be used to remove the atmospheric features which dominate ground-based J-band spectroscopy. We measure equivalent widths for three absorption lines and nine blended features which we identify in the spectra. Using detailed comparison with higher resolution spectra, we demonstrate that low resolution data can be used for stellar classification, since several features depend on the effective temperature and gravity. For example The CN index (1.096 - 1.104 um) decreases with temperature, but the strength of a blended feature at 1.28 um (consisting of primarily P beta) increases. The slope of a star's spectrum can also be used to estimate its effective temperature. The luminosity class of a star correlates with the ratio of the Mg I (1.1831 um) line to a blend of several species at 1.16 um. Using these indicators, a star can be classified to within several subclasses. Fifteen stars with particularly high and low metal abundances are included in the catalog and some spectral dependence on metal abundance is also found.Comment: 35 pages, 10 figures (3a-e are in gif format. For complete high resolution figures, go to http://www.astro.ucla.edu/~malkan/newjspec/) ; Accepted for published in ApJS; For associated spectra files, see http://www.astro.ucla.edu/~malkan/newjspec