Wireless capsule endoscopes (WCEs) are pill-sized camera-embedded devices that can provide visualization of the gastrointestinal (GI) tract by capturing and transmitting images to an external receiver. Determination of the exact location of the WCE is crucial for the accurate navigation of the WCE through external guidance, tracking of the GI abnormality, and the treatment of the detected disease. Despite the enormous progress in the real-time tracking of the WCE, a well-calibrated analytical model is still missing for the accurate localization of WCEs by the measurements from different onboard sensing units. In this paper, a well-calibrated analytical model for the magnetic localization of the WCE was established by optimizing the magnetic moment in the magnetic dipole model. The Jacobian-based iterative method was employed to solve the position of the WCE. An error model was established and experimentally verified for the analysis and prediction of the localization errors caused by inaccurate measurements from the magnetic field sensor. The assessment of the real-time localization of the WCE was performed via experimental trials using an external permanent magnet (EPM) mounted on a robotic manipulator and a WCE equipped with a 3-axis magnetic field sensor and an inertial measurement unit (IMU). The localization errors were measured under different translational and rotational motion modes and working spaces. The results showed that the selection of workspace (distance relative to the EPM) could lead to different positioning errors. The proposed magnetic localization method holds great potential for the real-time localization of WCEs when performing complex motions during GI diagnosis.

Biomass content and turnover rate were estimated for a lowland wet rain forest in French Guiana. A regression model relating the biomass of a tree to its dbh (diameter at breast height) was deduced from previously published data. A power-law allometric relationship of the form AGTB = aDb was used to estimate the tree biomass, AGTB (Mg ha−1), from its dbh D (cm). Using direct measurements of tree biomass in the literature, the best-fit allometric exponent b = 2.42 (SD = 0.02) was found. The logarithm of the coefficient a was normally distributed with an average of −2.00 (SD = 0.27). This method was applied to two permanent research stations of the lowland tropical rain forest of French Guiana: the Nouragues and Piste de Saint-Elie. At the Nouragues, the biomass was estimated from trees 10 cm in diameter on two plots covering a total surface area of 22 ha and yielded an average biomass of 309 Mg ha−1 (± 32 Mg ha−1, 95% confidence interval). Spatial variability was also addressed at the Nouragues by estimating the biomass of trees ≥ 30 cm dbh over a total surface area of 82 ha. For the wet tropical forest vegetation type, an average of 284 Mg ha−1 was obtained (spatial variability ±55 Mg ha−1). Biomass turnover was evaluated at Piste de Saint-Elie from two transects (0.78 and 1 ha) on which all trees ≥5 cm in diameter were recorded and mapped twice in 10 y. Transect 1 showed a slight increase in biomass, from 245 to 260 Mg ha−1 (338 to 345 Mg ha−1 for transect 2), corresponding to a net increase of 1.9 Mg ha−1 y−1 (0.7 Mg ha−1 y−1), and the biomass ingrowth was 3.2 Mg ha−1 y−1 (2.8 Mg ha−1 y−1). These figures are discussed in the light of the natural recruitment dynamics of tropical forests.