Boundary effects on image reconstruction in photoacoustic tomography

Exact photoacoustic tomography requires scanning over a 4π solid angle in 3D. The ultrasound detection window, however, is often limited, which makes a full scan impossible. For example, when a boundary lies closely to an object, the scanning region can cover only less than 4π in 3D. Because of incomplete information, the resolution, SNR, and fidelity of the resulting image deteriorate. Boundaries, however, can be used to our advantage; we proposed post-processing algorithms in image reconstruction to make partially scanned data complete. Here, we show the efficacy of the post-processing algorithms with both numerical and experimental results. Indeed, the algorithms can improve the resolution, SNR, and fidelity

Fighting against fast speckle decorrelation for light focusing inside live tissue by photon frequency shifting

Light focusing inside live tissue by digital optical phase conjugation (DOPC) has drawn increasing interest due to its potential biomedical applications in optogenetics, microsurgery, phototherapy, and deep-tissue imaging. However, fast physiological motions in a live animal, including blood flow and respiratory motions, produce undesired photon perturbation and thus inevitably deteriorate the performance of light focusing. Here, we develop a photon-frequency-shifting DOPC method to fight against fast physiological motions by switching the states of a guide star at a distinctive frequency. Therefore, the photons tagged by the guide star are well detected at the specific frequency, separating them from the photons perturbed by fast motions. Light focusing was demonstrated in both phantoms in vitro and mice in vivo with substantially improved focusing contrast. This work puts a new perspective on light focusing inside live tissue and promises wide biomedical applications

Evaluation on the Efficiency of Crop Insurance in China's Major Grain-Producing Area

AbstractIn China, crop insurance is just a pilot program characterized by material cost-based coverage level and government-subsidized premium. To identify the efficiency of the crop insurance, we use the nonparametric density function model and estimate the probability of yield loss rate at 3 proposed levels for grain crop, wheat, corn, rice and cotton respectively from 13 provinces in the Major Grain-Producing Area. Besides, we point out some unfavorable factors for crop insurance management based on the Second National Agricultural Census data (2006). Our finding is: the coverage level is on average no larger than 50% of the per hectare crop production value while the probability of yield loss for each crop approaches to zero if the proposed yield loss rate is larger than 40%, so the yield damage compensations are not necessary unless the huge catastrophes occur with the yield loss rate over 50%. Farmers could buy crop insurance to avoid big crop failure other than to maximize their returns. Therefore, the current crop insurance coverage level under normal years could not create an effective inducement for farmers to purchase insurance contracts. To expand crop insurance participation, we consider that it is necessary to carry out positive and conditional forced insurance, provide a larger portion of premium subsidy to the Major Grain-Producing Area by central government and improve the basic agricultural production conditions