Impact of Asian continental outflow on the concentrations of O3, CO, NMHCs and halocarbons on Jeju Island, South Korea during March 2005

As part of ABC-EAREX2005 experiment, numerous trace gases were measured at Gosan on Jeju Island, South Korea in March 2005 to characterize the impact of recent outflow from the Asian continent and to inter-compare measurement techniques used by participating groups. Here we present measurements of O3, CO, and whole air samples of methane, C2-C8 non-methane hydrocarbons (NMHCs) and C1-C2 halocarbons obtained during the study. The large temporal variations in the measured trace gas concentrations at Gosan were due to the transport of background marine air and of regional pollution mainly from the Chinese subcontinent. Average mixing ratios (± s.d.) were 54.6 (± 9.0) ppbv and 283 (± 100) ppbv for O3 and CO, respectively. CO showed good correlations (r2 = 0.62-0.81) with combustion tracers such as ethyne and benzene but poorly correlated (r2 = 0.11-0.29) with light alkanes, suggesting that the latter were contributed by non-combustion source(s). Back trajectory analysis showed that air masses mainly originated from the North China Plains and northeastern China, which together accounted for 64% of the total trajectories. The highest mean mixing ratios of O3 and combustion-derived species were found in air masses from eastern China and Korea, indicating the significant impact of emissions from these regions. Interestingly, air masses from northeast China contained elevated levels of light alkanes and the smallest ratios of ethyne/propane and benzene/propane among the air-mass groups, suggesting contribution from natural gas leakage in the upwind region, possibly from Siberia. © 2007 Elsevier Ltd. All rights reserved

Chemical characteristics of air from different source regions during the second Pacific Exploratory Mission in the Tropics (PEM-Tropics B)

Ten-day backward trajectories are used to determine the origins of air parcels arriving at locations of airborne DC-8 chemical measurements during NASA's second Pacific Exploratory Mission in the Tropics B that was conducted during February-April 1999. Chemical data at sites where the trajectories had a common geographical origin and transport history are grouped together, and statistical measures of chemical characteristics are computed. Temporal changes in potential temperature are used to determine whether trajectories experienced a significant convective influence during the 10-day period. Trajectories describing the aged marine Southern Hemispheric category remain over the South Pacific Ocean during the 10-day period, and their corresponding chemical signature indicates very clean air. The category aged marine air in the Northern Hemisphere is found to be somewhat dirtier. Subdividing its trajectories based on the direction from which the air had traveled is found to be important in explaining the various chemical signatures. Similarly, long-range northern hemispheric trajectories passing over Asia are subdivided depending on whether they had followed a mostly zonal path, had originated near the Indian Ocean, or had originated near Central or South America and subsequently experienced a stratospheric influence. Results show that the chemical signatures of these subcategories are different from each other. The chemical signature of the southern hemispheric long-range transport category apparently exhibits the effects of pollution from Australia, southern Africa, and South America. Parcels originating over Central and northern South America are found to contain the strongest pollution signature of all categories, due to biomass burning and other sources. The convective category exhibits enhanced values of nitrogen species, probably due to emissions from lightning associated with the convection. Values of various species, including peroxides and acids, confirm that parcels were influenced by the removal of soluble gas and particle species due to precipitation. Finally, current results are compared with those from the first PEM-Tropics mission that was conducted in the same region during the southern hemispheric dry season (August-October 1996) when extensive biomass burning occurred. Results show that air samples during PEM-Tropics B are considerably cleaner than those of its dry season counterpart. Copyright 2001 by the American Geophysical Union

Van Allen Probes, THEMIS, GOES, and Cluster Observations of EMIC waves, ULF pulsations, and an electron flux dropout

We examined an electron flux dropout during the 12-14 November 2012 geomagnetic storm using observations from seven spacecraft: the two Van Allen Probes, Time History of Events and Macroscale Interactions during Substorms (THEMIS)-A (P5), Cluster 2, and Geostationary Operational Environmental Satellites (GOES) 13, 14, and 15. The electron fluxes for energies greater than 2.0 MeV observed by GOES 13, 14, and 15 at geosynchronous orbit and by the Van Allen Probes remained at or near instrumental background levels for more than 24 h from 12 to 14 November. For energies of 0.8 MeV, the GOES satellites observed two shorter intervals of reduced electron fluxes. The first interval of reduced 0.8 MeV electron fluxes on 12-13 November was associated with an interplanetary shock and a sudden impulse. Cluster, THEMIS, and GOES observed intense He+ electromagnetic ion cyclotron (EMIC) waves from just inside geosynchronous orbit out to the magnetopause across the dayside to the dusk flank. The second interval of reduced 0.8 MeV electron fluxes on 13-14 November was associated with a solar sector boundary crossing and development of a geomagnetic storm with Dst<100 nT. At the start of the recovery phase, both the 0.8 and 2.0 MeV electron fluxes finally returned to near prestorm values, possibly in response to strong ultralow frequency (ULF) waves observed by the Van Allen Probes near dawn. A combination of adiabatic effects, losses to the magnetopause, scattering by EMIC waves, and acceleration by ULF waves can explain the observed electron behavior

A de novo dominant mutation in KIF1A associated with axonal neuropathy, spasticity and autism spectrum disorder

Mutations in the kinesin family member 1A (KIF1A) gene have been associated with a wide range of phenotypes including recessive mutations causing hereditary sensory neuropathy and hereditary spastic paraplegia and de novo dominant mutations causing a more complex neurological disorder affecting both the central and peripheral nervous system. We identified by exome sequencing a de novo dominant missense variant, (c.38G>A, p.R13H), within an ATP binding site of the kinesin motor domain in a patient manifesting a complex phenotype characterized by autism spectrum disorder (ASD), spastic paraplegia and axonal neuropathy. The presence of ASD distinguishes this case from previously reported patients with de novo dominant mutations in KIF1A

Fingerprinting and tracing the sources of soils and sediments: Earth and ocean science, geoarchaeological, forensic, and human health applications

publisher: Elsevier articletitle: Fingerprinting and tracing the sources of soils and sediments: Earth and ocean science, geoarchaeological, forensic, and human health applications journaltitle: Earth-Science Reviews articlelink: http://dx.doi.org/10.1016/j.earscirev.2016.08.012 content_type: article copyright: © 2016 Elsevier B.V. All rights reserved

An Overview of the Use of Neural Networks for Data Mining Tasks

In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks

SIGMAR1 mutation associated with autosomal recessive Silver-like syndrome

OBJECTIVE: To describe the genetic and clinical features of a simplex patient with distal hereditary motor neuropathy (dHMN) and lower limb spasticity (Silver-like syndrome) due to a mutation in the sigma nonopioid intracellular receptor-1 gene (SIGMAR1) and review the phenotypic spectrum of mutations in this gene. METHODS: We used whole-exome sequencing to investigate the proband. The variants of interest were investigated for segregation in the family using Sanger sequencing. Subsequently, a larger cohort of 16 unrelated dHMN patients was specifically screened for SIGMAR1 mutations. RESULTS: In the proband, we identified a homozygous missense variant (c.194T>A, p.Leu65Gln) in exon 2 of SIGMAR1 as the probable causative mutation. Pathogenicity is supported by evolutionary conservation, in silico analyses, and the strong phenotypic similarities with previously reported cases carrying coding sequence mutations in SIGMAR1. No other mutations were identified in 16 additional patients with dHMN. CONCLUSIONS: We suggest that coding sequence mutations in SIGMAR1 present clinically with a combination of dHMN and pyramidal tract signs, with or without spasticity, in the lower limbs. Preferential involvement of extensor muscles of the upper limbs may be a distinctive feature of the disease. These observations should be confirmed in future studies