MuCHLoc: Indoor ZigBee Localization System Utilizing Inter-Channel Characteristics

The deployment of a large-scale indoor sensor network faces a sensor localization problem because we need to manually locate significantly large numbers of sensors when Global Positioning System (GPS) is unavailable in an indoor environment. Fingerprinting localization is a popular indoor localization method relying on the received signal strength (RSS) of radio signals, which helps to solve the sensor localization problem. However, fingerprinting suffers from low accuracy because of an RSS instability, particularly in sensor localization, owing to low-power ZigBee modules used on sensor nodes. In this paper, we present MuCHLoc, a fingerprinting sensor localization system that improves the localization accuracy by utilizing channel diversity. The key idea of MuCHLoc is the extraction of channel diversity from the RSS of Wi-Fi access points (APs) measured on multiple ZigBee channels through fingerprinting localization. MuCHLoc overcomes the RSS instability by increasing the dimensions of the fingerprints using channel diversity. We conducted experiments collecting the RSS of Wi-Fi APs in a practical environment while switching the ZigBee channels, and evaluated the localization accuracy. The evaluations revealed that MuCHLoc improves the localization accuracy by approximately 15% compared to localization using a single channel. We also showed that MuCHLoc is effective in a dynamic radio environment where the radio propagation channel is unstable from the movement of objects including humans

LC-ESI/MS/MS analysis of neonicotinoids in urine of very low birth weight infants at birth.

OBJECTIVES:Neonicotinoid insecticides are widely used systemic pesticides with nicotinic acetylcholine receptor agonist activity that are a concern as environmental pollutants. Neonicotinoids in humans and the environment have been widely reported, but few studies have examined their presence in fetuses and newborns. The objective of this study is to determine exposure to neonicotinoids and metabolites in very low birth weight (VLBW) infants. METHODS:An analytical method for seven neonicotinoids and one neonicotinoid metabolite, N-desmethylacetamiprid (DMAP), in human urine using LC-ESI/MS/MS was developed. This method was used for analysis of 57 urine samples collected within 48 hours after birth from VLBW infants of gestational age 23-34 weeks (male/female = 36/21, small for gestational age (SGA)/appropriate gestational age (AGA) = 6/51) who were admitted to the neonatal intensive care unit of Dokkyo Hospital from January 2009 to December 2010. Sixty-five samples collected on postnatal day 14 (M/F = 37/22, SGA/AGA = 7/52) were also analyzed. RESULTS:DMAP, a metabolite of acetamiprid, was detected in 14 urine samples collected at birth (24.6%, median level 0.048 ppb) and in 7 samples collected on postnatal day 14 (11.9%, median level 0.09 ppb). The urinary DMAP detection rate and level were higher in SGA than in AGA infants (both p<0.05). There were no correlations between the DMAP level and infant physique indexes (length, height, and head circumference SD scores). CONCLUSION:These results provide the first evidence worldwide of neonicotinoid exposure in newborn babies in the early phase after birth. The findings suggest a need to examine potential neurodevelopmental toxicity of neonicotinoids and metabolites in human fetuses