The prediction and prevention of intrapartum fetal asphyxia in preterm pregnancies

2002 ◽  
Vol 186 (2) ◽  
pp. 279-282 ◽  
Author(s):  
James A. Low ◽  
Helen Killen ◽  
E.Jane Derrick
Keyword(s):  
Fetal Asphyxia ◽  
Prediction And Prevention

The prediction and prevention of intrapartum fetal asphyxia in term pregnancies

2001 ◽  
Vol 184 (4) ◽  
pp. 724-730 ◽  
Author(s):  
James A. Low ◽  
Heather Pickersgill ◽  
Helen Killen ◽  
E.Jane Derrick
Keyword(s):  
Fetal Asphyxia ◽  
Prediction And Prevention

PREDICTION AND PREVENTION OF GEODYNAMIC EVENTS DURING PREPARATION OF AN OREBODY BLOCK FOR EXTRACTION AT TASHTAGOL DEPOSIT

2018 ◽  
Vol 5 ◽  
pp. 74-80
Author(s):  
V.N. Filippov ◽  
◽  
A.A. Eremenko ◽  
A.N. Aleksandrov ◽  
I.F. Matveev ◽  
...  
Keyword(s):  
Prediction And Prevention

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

Naloxone reverses neonatal depression caused by fetal asphyxia

Science ◽  
1982 ◽  
Vol 216 (4551) ◽  
pp. 1252-1253 ◽  
Author(s):  
V Chernick ◽  
R. Craig
Keyword(s):  
Fetal Asphyxia

scholarly journals Are Climate Factors Driving the Contemporary Wildfire Occurrence in China?

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 392
Author(s):  
Zige Lan ◽  
Zhangwen Su ◽  
Meng Guo ◽  
Ernesto C. Alvarado ◽  
Futao Guo ◽  
...  
Keyword(s):  
Human Factors ◽  
Large Scale ◽  
Fire Occurrence ◽  
Climate Factors ◽  
Wildfire Occurrence ◽  
Prediction And Prevention ◽  
Data Resolution ◽  
Main Driver ◽  
Landscape Factors ◽  
Modelling Approach

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

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