The Experts below are selected from a list of 449541 Experts worldwide ranked by ideXlab platform

Vijaya Krishna Tadekoru - One of the best experts on this subject based on the ideXlab platform.

Hezhong Tian - One of the best experts on this subject based on the ideXlab platform.

  • temporal spatial characteristics and source apportionment of pm2 5 as well as its associated Chemical Species in the beijing tianjin hebei region of china
    Environmental Pollution, 2018
    Co-Authors: Jiajia Gao, Kun Wang, Yong Wang, Shuhan Liu, Chuanyong Zhu, Jiming Hao, Huanjia Liu, Shenbing Hua, Hezhong Tian
    Abstract:

    Abstract PM2.5 and its major Chemical compositions were sampled and analyzed in January, April, July and October of 2014 at Beijing (BJ), Tianjin (TJ), Langfang (LF) and Baoding (BD) in order to probe the temporal and spatial characteristics as well as source apportionment of PM2.5 in the Beijing-Tianjin-Hebei (BTH) region. The results showed that PM2.5 pollution was severe in the BTH region. The average annual concentrations of PM2.5 at four sampling sites were in the range of 126–180 μg/m3, with more than 95% of sampling days exceeding 35 μg/m3, the limit ceiling of average annual concentration of PM2.5 regulated in the Chinese National Ambient Air Quality Standards (GB3095-2012). Additionally, concentrations of PM2.5 and its major Chemical Species were seasonally dependent and demonstrated spatially similar variation characteristics in the BTH region. Concentration of toxic heavy metals, such as As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, Se, and Zn, were higher in winter and autumn. Secondary inorganic ions (SO42−, NO3−, and NH4+) were the three-major water-soluble inorganic ions (WSIIs) of PM2.5 and their mass ratios to PM2.5 were higher in summer and autumn. The organic carbon (OC) and elemental carbon (EC) concentrations were lower in spring and summer than in autumn and winter. Five factors were selected in Positive Matrix Factorization (PMF) model analysis, and the results showed that PM2.5 pollution was dominated by vehicle emissions in Beijing, combustion emissions including coal burning and biomass combustion in Langfang and Baoding, and soil and construction dust emissions in Tianjin, respectively. The air mass that were derived from the south and southeast local areas around BTH regions reflected the features of short-distant and small-scale air transport. Shandong, Henan, and Hebei were identified the major potential sources-areas of secondary aerosol emissions to PM2.5.

  • temporal spatial characteristics and source apportionment of pm 2 5 as well as its associated Chemical Species in the beijing tianjin hebei region of china
    Environmental Pollution, 2018
    Co-Authors: Jiajia Gao, Kun Wang, Yong Wang, Shuhan Liu, Chuanyong Zhu, Jiming Hao, Huanjia Liu, Shenbing Hua, Hezhong Tian
    Abstract:

    Abstract PM2.5 and its major Chemical compositions were sampled and analyzed in January, April, July and October of 2014 at Beijing (BJ), Tianjin (TJ), Langfang (LF) and Baoding (BD) in order to probe the temporal and spatial characteristics as well as source apportionment of PM2.5 in the Beijing-Tianjin-Hebei (BTH) region. The results showed that PM2.5 pollution was severe in the BTH region. The average annual concentrations of PM2.5 at four sampling sites were in the range of 126–180 μg/m3, with more than 95% of sampling days exceeding 35 μg/m3, the limit ceiling of average annual concentration of PM2.5 regulated in the Chinese National Ambient Air Quality Standards (GB3095-2012). Additionally, concentrations of PM2.5 and its major Chemical Species were seasonally dependent and demonstrated spatially similar variation characteristics in the BTH region. Concentration of toxic heavy metals, such as As, Cd, Cr, Cu, Mn, Ni, Pb, Sb, Se, and Zn, were higher in winter and autumn. Secondary inorganic ions (SO42−, NO3−, and NH4+) were the three-major water-soluble inorganic ions (WSIIs) of PM2.5 and their mass ratios to PM2.5 were higher in summer and autumn. The organic carbon (OC) and elemental carbon (EC) concentrations were lower in spring and summer than in autumn and winter. Five factors were selected in Positive Matrix Factorization (PMF) model analysis, and the results showed that PM2.5 pollution was dominated by vehicle emissions in Beijing, combustion emissions including coal burning and biomass combustion in Langfang and Baoding, and soil and construction dust emissions in Tianjin, respectively. The air mass that were derived from the south and southeast local areas around BTH regions reflected the features of short-distant and small-scale air transport. Shandong, Henan, and Hebei were identified the major potential sources-areas of secondary aerosol emissions to PM2.5.

Yi Wang - One of the best experts on this subject based on the ideXlab platform.

  • bone quantitative susceptibility mapping using a Chemical Species specific r2 signal model with ultrashort and conventional echo data
    Magnetic Resonance in Medicine, 2018
    Co-Authors: Alexey Dimov, Pascal Spincemaille, Martin R Prince, Jiang Du, Yi Wang
    Abstract:

    To develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.Three-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the Chemical Species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.Compared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2  = 0.77). Bone QSM was successfully generated in all subjects.The QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

  • bone quantitative susceptibility mapping using a Chemical Species specific r2 signal model with ultrashort and conventional echo data
    Magnetic Resonance in Medicine, 2018
    Co-Authors: Alexey Dimov, Pascal Spincemaille, Martin R Prince, Zhe Liu, Yi Wang
    Abstract:

    Author(s): Dimov, Alexey V; Liu, Zhe; Spincemaille, Pascal; Prince, Martin R; Du, Jiang; Wang, Yi | Abstract: PurposeTo develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.MethodsThree-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the Chemical Species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.ResultsCompared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2 = 0.77). Bone QSM was successfully generated in all subjects.ConclusionsThe QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Prasad Ghanta - One of the best experts on this subject based on the ideXlab platform.

Alexey Dimov - One of the best experts on this subject based on the ideXlab platform.

  • bone quantitative susceptibility mapping using a Chemical Species specific r2 signal model with ultrashort and conventional echo data
    Magnetic Resonance in Medicine, 2018
    Co-Authors: Alexey Dimov, Pascal Spincemaille, Martin R Prince, Jiang Du, Yi Wang
    Abstract:

    To develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.Three-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the Chemical Species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.Compared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2  = 0.77). Bone QSM was successfully generated in all subjects.The QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

  • bone quantitative susceptibility mapping using a Chemical Species specific r2 signal model with ultrashort and conventional echo data
    Magnetic Resonance in Medicine, 2018
    Co-Authors: Alexey Dimov, Pascal Spincemaille, Martin R Prince, Zhe Liu, Yi Wang
    Abstract:

    Author(s): Dimov, Alexey V; Liu, Zhe; Spincemaille, Pascal; Prince, Martin R; Du, Jiang; Wang, Yi | Abstract: PurposeTo develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.MethodsThree-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the Chemical Species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.ResultsCompared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2 = 0.77). Bone QSM was successfully generated in all subjects.ConclusionsThe QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.