Abstract Background The Vacuum Dust Bag Ring intensification of production and socio-economic changes have accelerated the loss of local traditional knowledge and plant resources.Understanding the distribution and determinants of such biocultural diversity is essential in planning efficient surveys and conservation efforts.Because the concept of bi
VENTRAL MEDIAN AND LATERAL FLANK APPROACH FOR OVARIOHYSTERECTOMY IN CAT
This study was conducted to compare Ventral Median Approach (OHM) and Lateral Flank Approach (OHF) for feline ovariohysterectomy (OH).Fifteen healthy local female cats (Felis catus) with body weights ranged 2-4 kg and aged 1-2 years were divided into two groups, OHM (n= 8) and OHF (n= 7).Prior to OH, the cats were anesthethized using ketamine-xylaz
Peculiarity of autoimmune hepatitis triggered by SARS-CoV-2 infection
Introduction: Recently, SHILAJIT LIQUID medical interest has been growing in SARS-CoV-2 infection and its multiorgan involvement, including the liver.Up until now, a few reports have described autoimmune hepatitis (AIH) triggered by SARS-CoV-2 infection, but no data are available about the specific liver inflammatory infiltrate and cluster of diffe
Development of a novel self-sanitizing mask prototype to combat the spread of infectious disease and reduce unnecessary waste
Abstract With the spread of COVID-19, significant emphasis has been placed on mitigation techniques such Vacuum Dust Bag Ring as mask wearing to slow infectious disease transmission.Widespread use of face coverings has revealed challenges such as mask contamination and waste, presenting an opportunity to improve the current technologies.In response
Learning Models for Semantic Classification of Insufficient Plantar Pressure Images
Establishing a reliable and stable model to predict a target by using insufficient labeled samples is feasible and effective, particularly, for a sensor-generated data-set.This paper has been inspired with insufficient data-set learning algorithms, such as metric-based, prototype networks and meta-learning, and therefore we propose an insufficient