A Torsion Relative Angle Measurement Method Based on Fiber-Loop Ring-Down with Intra-Cavity Amplification

Background: The fiber-loop ring-down spectroscopy technique has the benefits of optical fiber sensors and also has many unique advantages. Combined with various sensor structures, the FLRD system can achieve different physical, chemical, and biological sensors. Objective: To find a way to solve the problems of light fluctuation and low sensitivity, a high sensitivity and reliability torsion relative angle measurement system is necessary. Methods: The torsion relative angle measurement is achieved by using the fiber loop ring-down intra-cavity amplification. The sensitivity, correlation coefficient, and repeatability are analyzed with the experiment. Results: The sensitivity and correlation coefficient of the proposed system are 4.05 μs/° and 0.9996, respectively. The repeated experiments show that the standard deviation is 9.592×10-4. Conclusion: The proposed measurement method provides a way to solve the problems of light fluctuation and low sensitivity and has promising applications in the optically active solutions, fiber radial stress birefringence, and polarization state measurement of fiber lasers.

Blue Light Acclimation Reduces the Photoinhibition of Phalaenopsis aphrodite (Moth Orchid)

The moth orchid is an important ornamental crop. It is very sensitive to high light irradiation due to photoinhibition. In this study, young orchid tissue culture seedlings and 2.5” potted plants pretreated under blue light (BL, λmax = 450 nm) at 100 µmol m−2 s−1 for 12 days (BL acclimation) were found to have an increased tolerance to high light irradiation. After BL acclimation, orchids had an increased anthocyanin accumulation, enhanced chloroplast avoidance, and increased chlorophyll fluorescence capacity whenever they were exposed to high light of 1000 μmol m−2 s−1 for two weeks (HL). They had higher Fv/Fm, electron transport rate (ETR), chlorophyll content, catalase activity and sucrose content when compared to the control without BL acclimation. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) showed that transcript levels of phototropins, D1, RbcS, PEPCK, Catalase and SUT2 were upregulated in the BL-acclimated orchids. Consequently, BL acclimation orchids had better growth when compared to the control under long-term high light stress. In summary, this study provides a solution, i.e., BL acclimation, to reduce moth orchid photoinhibition and enhance growth before transplantation of the young tissue culture seedlings and potted plants into greenhouses, where they usually suffer from a high light fluctuation problem.

Automatic Individual Pig Detection and Tracking in Pig Farms

Individual pig detection and tracking is an important requirement in many video-based pig monitoring applications. However, it still remains a challenging task in complex scenes, due to problems of light fluctuation, similar appearances of pigs, shape deformations, and occlusions. In order to tackle these problems, we propose a robust on-line multiple pig detection and tracking method which does not require manual marking or physical identification of the pigs and works under both daylight and infrared (nighttime) light conditions. Our method couples a CNN-based detector and a correlation filter-based tracker via a novel hierarchical data association algorithm. In our method, the detector gains the best accuracy/speed trade-off by using the features derived from multiple layers at different scales in a one-stage prediction network. We define a tag-box for each pig as the tracking target, from which features with a more local scope are extracted for learning, and the multiple object tracking is conducted in a key-points tracking manner using learned correlation filters. Under challenging conditions, the tracking failures are modelled based on the relations between responses of the detector and tracker, and the data association algorithm allows the detection hypotheses to be refined; meanwhile the drifted tracks can be corrected by probing the tracking failures followed by the re-initialization of tracking. As a result, the optimal tracklets can sequentially grow with on-line refined detections, and tracking fragments are correctly integrated into respective tracks while keeping the original identifications. Experiments with a dataset captured from a commercial farm show that our method can robustly detect and track multiple pigs under challenging conditions. The promising performance of the proposed method also demonstrates the feasibility of long-term individual pig tracking in a complex environment and thus promises commercial potential.