Prediction and Prevention of Preeclampsia

2022 ◽  
pp. 405-417
Author(s):  
Anne Cathrine Staff ◽  
Jason G. Umans ◽  
Arun Jeyabalan
Keyword(s):  
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. 

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.

scholarly journals Patients, clinicians and researchers working together to improve cardiovascular health: a qualitative study of barriers and priorities for patient-oriented research

BMJ Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. e031187 ◽  
Author(s):  
Maria-Jose Santana ◽  
Sandra Zelinsky ◽  
Sadia Ahmed ◽  
Chelsea Doktorchik ◽  
Matthew James ◽  
...  
Keyword(s):  
Health Research ◽  
Heart Diseases ◽  
Research Priorities ◽  
Research Programme ◽  
Advisory Council ◽  
Future Research ◽  
Prediction And Prevention ◽  
Participatory Health Research ◽  
Working Together ◽  
Oriented Research

ObjectivesThe overall goal of this study is to identify priorities for cardiovascular (CV) health research that are important to patients and clinician-researchers. We brought together a group of CV patients and clinician-researchers new to patient-oriented research (POR), to build a multidisciplinary POR team and form an advisory committee for the Libin Cardiovascular Institute of Alberta.DesignThis qualitative POR used a participatory health research paradigm to work with participants in eliciting their priorities. Therefore, participants were involved in priority setting, and analysis of findings. Participants also developed a plan for continued engagement to support POR in CV health research.SettingLibin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Canada.ParticipantsA total of 23 participants, including patients and family caregivers (n=12) and clinician-researchers (n=11).ResultsParticipants identified barriers and facilitators to POR in CV health (lack of awareness of POR and poor understanding on the role of patients) and 10 research priorities for improving CV health. The CV health research priorities include: (1) CV disease prediction and prevention, (2) access to CV care, (3) communication with providers, (4) use of eHealth technology, (5) patient experiences in healthcare, (6) patient engagement, (7) transitions and continuity of CV care, (8) integrated CV care, (9) development of structures for patient-to-patient support and (10) research on rare heart diseases.ConclusionsIn this study, research priorities were identified by patients and clinician-researchers working together to improve CV health. Future research programme and projects will be developed to address these priorities. A key output of this study is the creation of the patient advisory council that will provide support and will work with clinician-researchers to improve CV health.

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