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AXiR Engine® tells you the risk of future disease in your body.Until today we’ ve been ignoring small signal in our body if we feel that the pain is a split second or very short period.In Japan we see the number of deaths by cancer like 370,000 people and the number is similar in the past 6 years.Maybe the fatalities number will be similar in 2018 and this causes the next guess like that the next year candidate370,000 are waiting for cancer death order because of invisible reason today.The total number of individuals affected by cancer in Japan is about 1,000,000 and the number means 37% peoplemight be going to die. Medical doctor is focusing on patients who are clearly suffering from actual diseases like cancer.AXiON Research Inc., we assume the invisible path to reach those diseases and some reason with scientific backgroundmust be there to meet the numbers repeated every year. In The “Compass to Healthy Life”Research Complex Program organized by RIKEN and supported by JST, in July 2018, AXiON Research Inc. showsthe performance of Replica Generator III to increase data of healthcare on 415 people data up to 4,150.It’ s really good result and succeeded in increase of 4 initial disease risk categories up to 7 ones after the data generationwith keeping the original statistical feature and accuracy. It also keeps the probability density, the dispersion and thedistribution of the original data increasing the number per different age and gender. It contributes the future analysisof 10,000 people data and analyzes health indices and invisible disease risk prediction for pre-disease state.
AXiON Research Inc. is introducing newmethodology to identifythe health indices / position in pre-disease state groupand how quickly getting worse by checking autonomic nervesactivities or up / down parameters related to individual immunity.Heatmap of health condition/disease risk level helps theidentification of the risk and vector-map of diseaserisk level works howmuch, how quickly getting worseor shifting the next stage of future diseases.The challenge started a few years ago and various technologies /research results are accelerating the analysis process and its accuracy.Today medical service is often using X-ray, MRI, CT or PET andit can identify the disease itself at very high rate. However,it does usually work as an answer like you have no problem at all, at least today.Some of pre-disease state people might be waiting for new technologyto make some advice or estimation of future disease risk at very early stage.We introduce AXiR Engine® for howmuch healthy you are or we are.We’ re going to the next pre-service stage with strategic partners torun the service into the real world and commercial service.
We’ re seeking the next fundraisingSeries A in 2019. Series A 1st will bebetween Jan. and Apr. 2019.Series A 2nd will be between June andOct. 2019. Welcome, Early Entries.
In modern day agriculture, high inputs of nitrogen are being used to
gain high crop yields. Of this nitrogen, 50-70% is lost from the soil (1)
with devastating environmental effects. An IT solutions provider, PS
Solutions, is taking part in an ambitious project in Colombia to build
efficient cultivation management practices. The project is using
internet of things (IoT) solutions designed by PS Solutions to
maximize the crop production and minimize the environmental
impact of nitrogen.
Nitrogen in water contamination and greenhouse gasemission
Urea is one of the world’s most commonly used nitrogen-based
fertilizers. When applied to soil, nitrifying bacteria transform urea
into nitrite (NO2-) and then to nitrate (NO3-). As NO3-, nitrogen easily
moves from soil to water (1, 3), with approximately 30-50% of the
nitrogen in fertilizer leaching into the ocean.
Nitrification also contributes to global warming by emitting nitrous
oxide (N2O) and other nitrogen oxides (NOx). These molecules can
destroy the ozone layer and trap heat with 300 times more efficiency
than CO2 (1).
The total economic losses from environmental pollution related to
nitrogen-based fertilizers are estimated to be €70~€320 billion,
which more than doubles the agricultural revenues gained (2).
Biological Nitrification Inhibition (BNI) to reduce thenitrogen footprint
Many native tropical grasslands are highly nitrifying ecosystems,
rapidly transforming nitrogen into very mobile forms. As explained
above, these forms have negative environmental effects, reducing
agriculture productivity and stocking capacity of agropastoral
systems. On the other hand, some tropical grasses have high BNI.
These plants release nitrification inhibitors and have the potential to
enhance crop productivity and improve the use of nitrogen in crop
rotations (3, 4). With the ultimate aim to develop productive and
environmentally friendly agropastoral systems, the Ministry of
Agriculture, Forestry and Fisheries (MAFF) of Japan is supporting a
research project run by Dr. Manabu Ishitani, a primary investigator
at the International Center for Tropical Agriculture (CIAT, Colombia),
that is replacing native grass in farm fields with Brachiaria humidicola,
a tropical grass with high BNI.
The project goals are twofold. First is to show that nitrification
suppression significantly reduces the environmental footprint of
farming, and second is to improve agronomic practices by
implementing IoT to exploit BNI functions.
e-kakashi, an agricultural IoT
The effective use of tropical grasses with strong BNI function for
efficient agricultural productivity largely depends on the field
environment and farming practice. Thus, the first step in the project is
to collect a large amount of cultivation and environmental data from
the field. These data are collected by e-kakashi, a powerful IoT tool
designed by PS Solutions for the purpose of enhancing farming
practices.
e-kakashi has been selected because of its proven data perfor-
mance. Reliable data is critical for translating field observations and
agricultural theories into practical farming. Connected to e-kakashi
are new soil sensors with high sensitivity and accuracy manufactured
by Murata Manufacturing Co., Ltd. e-kakashi will collect the sensor
data, which includes soil temperature and soil moisture. Scientists
will then analyze the data to estimate bacterial activity and nitrogen
loss which enable them to assess the effects of BNI grasses on
nitrogen retention and propose effective agricultural practice.
e-kakashi is an example of how IoT can benefit both agriculture and
the environment. Dr. Takashi Togami, the developer of e-kakashi,
sees it as a way to bring scientific solutions to everyday farming. ÒI
look forward to a day when farmers use e-kakashi like we use TVs
and smartphones.Ó
Note 1. The names and logos of "e-kakashi" are registered
trademarks or trademarks of PS Solutions Corp. in Japan.
Note 2. Names of any other product, company or organization are
registered trademarks or trademarks of the relevant company.
IoT for environmentalconservation andsustainable agriculture
1 Coskun D, et al. Nitrogen transformations in modern agriculture and the role of biological
nitrification inhibition. Nat Plants. 2017;3:17074. doi: 10.1038/nplants.2017.74.
2 Sutton M, et al. Too much of a good thing. Nature. 2011;472(7342):159-61.
doi: 10.1038/472159a.
3 Subbarao GV, et al. Evidence for biological nitrification inhibition in Brachiaria pastures.
Proc Natl Acad Sci U S A. 2009;106(41):17302-7. doi: 10.1073/pnas.0903694106.
4 Karwat H, et al. Residual effect of BNI by Brachiaria humidicola pasture on nitrogen
recovery and grain yield of subsequent maize. Plant Soil. 2017; 420(1-2):389-406.
https://doi.org/10.1007/s11104-017-3381-z
(Source: JIRCAS)
Patía, CaucaPatía, Cauca
BNI grassland
Native grassland(control)
BNI grassland
Native grassland(control)
e-kakashie-kakashi Data-driven
farming practices
Farmers
Farming andenvironmental data
collection andanalysis
Introduction of
high BNI grass
1314 14 DECEMBER 2018 • VOL 362 ISSUE 6420 sciencemag.org/custom-publishing SCIENCE
new products: automation
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