Experimental study on pulse radar target probing in RFS based on interrupted transmitting and receiving

Radar target probing and measurement are challenging tasks for Radio Frequency Simulation（RFS） with pulse radar signal. Due to the long-time duration of pulse radar signal and the limited space of anechoic chamber, the reflected signal returns before pulse radar signal is fully transmitted in RFS. As a consequence, the transmitted and reflected signals are coupled at the receiver. To handle this problem, the Interrupted Transmitting and Receiving（ITR） experiment system is constructed in this paper by dividing the pulse radar signal into sub-pulses. The target echo can be obtained by transmitting and receiving the sub-pulses intermittently. Furthermore, the principles of ITR are discussed and the target probing experiments are performed with the ITR system. It is demonstrated that the ITR system can overcome the coupling between the reflected and transmitted signals. Based on the target probing results, the performance of pulse radar target probing and measurement can be verified in RFS with the ITR system.

The Effect of Circulation Fan on Energy Consumption in Nature Convective Refrigerator-Freezer

The effect of the circulation fan installed in fresh food compartment on energy consumption of natural convective refrigerator/freezers (RFs) was experimentally studied. Five different RF models with different cycles were tested. The experimental results showed that the energy consumption of the single-loop cycle RF increased by 2.4%~3.8%, that of the bypass two-circuit cycle RF decreased by 1.0%, and that of the two-circuit cycle RF with its evaporators in parallel when the geometry parameters of refrigeration system and the refrigerant charge were not changed after the circulation fan was installed decreased by 3.3%. When the optimization on the refrigerant charge and the evaporator was carried out, the energy consumption of the single-loop cycle RF , the bypass two-circuit cycle RF and the two-circuit cycle RF with its evaporators in parallel, decreased by 1.0%~6.4%, 3.25% and 3.26% respectively. The present conclusions will provide a guideline to the optimum design for the RF with the circulation fan.

Prognostic value of cancer stem cell markers CD133, ALDH1 and nuclear β-catenin in colon cancer

Objective： Colon cancer is one of the most common human malignancies. Cancer stem cells （CSCs）, despite being only a small subset of cancer cells, have the capability to self-renew and sustain the tumor. They also have the ability to proliferate. Multiple CSCs-associated markers have been identified in colon cancer including CD133, ALDH1 and β-catenin. The aim of the work was to study the prognostic value of CSCs markers （CD133, ALDH 1 and β-catenin）, as well as their rela- tionship to clinicopathological features of colon cancer. Methods： CD133, ALDH1 and β-catenin proteins expression was as- sessed immunohistochemically in a series of colon cancers and their prognostic significance was evaluated. Results： CD133 expression showed significant relationship to tumor stage and lymph node metastasis （P-value 0.004 ＆ 〈 0.001 respectively）, and near significant relationship to liver metastasis （P-value 0.092）. ALDH1 was significantly associated with tumor grade, stage and nodal metastasis （P-value 0.021,0.001 and 0.026 respectively）, but its relationship to liver metastasis was near sig- nificant （P-value 0.068）. Nuclear β-catenin was significantly related to tumor grade, stage, nodal and liver metastasis （P-value 0.001, 〈 0.001, 〈 0.001 and 0.008 respectively）. Overall survival （OS） was associated inversely with CD133, ALDH1 positivity, and directly with nuclear 13-catenin posiUvity （P-value 〈 0.001,0.0001 and 〈 0.001 respectively）. Also recurrence free survival （RFS） was associated inversely with CD133, ALDH1 and directly with nuclearβ-catenin positivity （P-value 0.0001,0.001 and 〈 0.001 respectively）. Conclusion： CD133, ALDH1 and β-catenin expressions of tumor cells have significant impact upon malignant progression of colon cancer and thus patient survival and tumor recurrence. Hence they can be used to predict outcome of colon cancer patients.

A novel SMC-PHD filter based on particle compensation

As a typical implementation of the probability hypothesis density(PHD) filter, sequential Monte Carlo PHD(SMC-PHD) is widely employed in highly nonlinear systems. However, the particle impoverishment problem introduced by the resampling step, together with the high computational burden problem, may lead to performance degradation and restrain the use of SMC-PHD filter in practical applications. In this work, a novel SMC-PHD filter based on particle compensation is proposed to solve above problems. Firstly, according to a comprehensive analysis on the particle impoverishment problem, a new particle generating mechanism is developed to compensate the particles. Then, all the particles are integrated into the SMC-PHD filter framework. Simulation results demonstrate that, in comparison with the SMC-PHD filter, proposed PC-SMC-PHD filter is capable of overcoming the particle impoverishment problem, as well as improving the processing rate for a certain tracking accuracy in different scenarios.

Convolution Kernels Implementation of Cardinalized Probability Hypothesis Density Filter

The probability hypothesis density （PHD） propagates the posterior intensity in place of the poste- rior probability density of the multi-target state. The cardinalized PHD （CPHD） recursion is a generalization of PHD recursion, which jointly propagates the posterior intensity function and posterior cardinality distribution. A number of sequential Monte Carlo （SMC） implementations of PHD and CPHD filters （also known as SMC- PHD and SMC-CPHD filters, respectively） for general non-linear non-Gaussian models have been proposed. However, these approaches encounter the limitations when the observation variable is analytically unknown or the observation noise is null or too small. In this paper, we propose a convolution kernel approach in the SMC-CPHD filter. The simuIation results show the performance of the proposed filter on several simulated case studies when compared to the SMC-CPHD filter.