Spatio-temporal distribution of apoptosis and the modulators thereof following a cortical microinfarct in rat brain

2007 ◽  
Vol 57 (3) ◽  
pp. 354-361 ◽  
Author(s):  
José V. Lafuente ◽  
Bernardo Mitre ◽  
Enrike G. Argandoña
Keyword(s):  
Rat Brain ◽  
Temporal Distribution ◽  
Spatio Temporal

scholarly journals Spatio-temporal distribution of reactive sulfur species during methylmercury exposure in the rat brain

2022 ◽  
Vol 47 (1) ◽  
pp. 31-37
Author(s):  
Takamitsu Unoki ◽  
Masahiro Akiyama ◽  
Yasuhiro Shinkai ◽  
Yoshito Kumagai ◽  
Masatake Fujimura
Keyword(s):  
Rat Brain ◽  
Temporal Distribution ◽  
Sulfur Species ◽  
Methylmercury Exposure ◽  
Reactive Sulfur Species ◽  
Spatio Temporal

Influence of Planting Density on Root Spatio-Temporal Distribution of Different Types of Maize under High-Yielding Cultivation Conditions

2013 ◽  
Vol 38 (7) ◽  
pp. 1286-1294 ◽  
Author(s):  
Zong-Xin LI ◽  
Yuan-Quan CHEN ◽  
Qing-Cheng WANG ◽  
Kai-Chang LIU ◽  
Wang-Sheng GAO ◽  
...  
Keyword(s):  
Temporal Distribution ◽  
Planting Density ◽  
Cultivation Conditions ◽  
Different Types ◽  
Spatio Temporal

SPATIO-TEMPORAL DISTRIBUTION OF URANIUM CONCENTRATION IN SHALLOW AQUIFERS OF ARAVALLI TERRANE (NORTH GUJARAT), INDIA

2019 ◽  
Author(s):  
Rudra Mohan Pradhan ◽  
◽  
Karrie A. Weber ◽  
Karrie A. Weber ◽  
Daniel Snow ◽  
...  
Keyword(s):  
Uranium Concentration ◽  
Temporal Distribution ◽  
Shallow Aquifers ◽  
Spatio Temporal ◽  
North Gujarat

scholarly journals Variation Characteristics and Transportation of Aerosol, NO2, SO2, and HCHO in Coastal Cities of Eastern China: Dalian, Qingdao, and Shanghai

2021 ◽  
Vol 13 (5) ◽  
pp. 892
Author(s):  
Xiaomei Li ◽  
Pinhua Xie ◽  
Ang Li ◽  
Jin Xu ◽  
Zhaokun Hu ◽  
...  
Keyword(s):  
Eastern China ◽  
Temporal Distribution ◽  
Correlation Coefficients ◽  
Optical Absorption Spectroscopy ◽  
Near Surface ◽  
Mixing Ratios ◽  
Variation Characteristics ◽  
Spatio Temporal ◽  
Gas Volume ◽  
Transport Flux

This paper studied the method for converting the aerosol extinction to the mass concentration of particulate matter (PM) and obtained the spatio-temporal distribution and transportation of aerosol, nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations in Dalian (38.85°N, 121.36°E), Qingdao (36.35°N, 120.69°E), and Shanghai (31.60°N, 121.80°E) from 2019 to 2020. The PM2.5 measured by the in situ instrument and the PM2.5 simulated by the conversion formula showed a good correlation. The correlation coefficients R were 0.93 (Dalian), 0.90 (Qingdao), and 0.88 (Shanghai). A regular seasonality of the three trace gases is found, but not for aerosols. Considerable amplitudes in the weekly cycles were determined for NO2 and aerosols, but not for SO2 and HCHO. The aerosol profiles were nearly Gaussian, and the shapes of the trace gas profiles were nearly exponential, except for SO2 in Shanghai and HCHO in Qingdao. PM2.5 presented the largest transport flux, followed by NO2 and SO2. The main transport flux was the output flux from inland to sea in spring and winter. The MAX-DOAS and the Copernicus Atmosphere Monitoring Service (CAMS) models’ results were compared. The overestimation of NO2 and SO2 by CAMS is due to its overestimation of near-surface gas volume mixing ratios.

Sign in / Sign up

Export Citation Format

Share Document