Tensor-Based Reduced-Dimension MUSIC Method for Parameter Estimation in Monostatic FDA-MIMO Radar

Frequency diverse array (FDA) radar has attracted much attention due to the angle and range dependence of the beam pattern. Multiple-input-multiple-output (MIMO) radar has high degrees of freedom (DOF) and spatial resolution. The FDA-MIMO radar, a hybrid of FDA and MIMO radar, can be used for target parameter estimation. This paper investigates a tensor-based reduced-dimension multiple signal classification (MUSIC) method, which is used for target parameter estimation in the FDA-MIMO radar. The existing subspace methods deteriorate quickly in performance with small samples and a low signal-to-noise ratio (SNR). To deal with the deterioration difficulty, the sparse estimation method is then proposed. However, the sparse algorithm has high computation complexity and poor stability, making it difficult to apply in practice. Therefore, we use tensor to capture the multi-dimensional structure of the received signal, which can optimize the effectiveness and stability of parameter estimation, reduce computation complexity and overcome performance degradation in small samples or low SNR simultaneously. In our work, we first obtain the tensor-based subspace by the high-order-singular value decomposition (HOSVD) and establish a two-dimensional spectrum function. Then the Lagrange multiplier method is applied to realize a one-dimensional spectrum function, estimate the direction of arrival (DOA) and reduce computation complexity. The transmitting steering vector is obtained by the partial derivative of the Lagrange function, and automatic pairing of target parameters is then realized. Finally, the range can be obtained by using the least square method to process the phase of transmitting steering vector. Method analysis and simulation results prove the superiority and reliability of the proposed method.

Parametric instability in the expanding solar wind

<p>Recent measurments of Parker Solar Probe show that alfvenic fluctuations in the solar wind often appear in the form of swithcback with constant total magnetic field. Our aim is to understand if and how such fluctuations can contribute to the heating or acceleration of the solar wind, via the Parametric Instability. The intability of one dimensional Alfvénic fluctuations has been extensively studied in both homogenoeus plasma and in the expanding solar wind, less so for the two-dimensional case which is closer to expected three-dimensional nature of switchbacks. In this work we study under which condition an Alfvén wave with a two dimensional spectrum (as introduced in Primavera et al ApJ 2019) can decay in the expanding solar wind and we will present preliminary results.</p>

High-throughput phenotypic screen and transcriptional analysis identify new compounds and targets for macrophage reprogramming

Macrophages are plastic and, in response to different local stimuli, can polarize toward multi-dimensional spectrum of phenotypes, including the pro-inflammatory M1-like and the anti-inflammatory M2-like states. Using a high-throughput phenotypic screen in a library of ~4000 FDA-approved drugs, bioactive compounds and natural products, we find ~300 compounds that potently activate primary human macrophages toward either M1-like or M2-like state, of which ~30 are capable of reprogramming M1-like macrophages toward M2-like state and another ~20 for the reverse repolarization. Transcriptional analyses of macrophages treated with 34 non-redundant compounds identify both shared and unique targets and pathways through which the tested compounds modulate macrophage activation. One M1-activating compound, thiostrepton, is able to reprogram tumor-associated macrophages toward M1-like state in mice, and exhibit potent anti-tumor activity. Our compound-screening results thus help to provide a valuable resource not only for studying the macrophage biology but also for developing therapeutics through modulating macrophage activation.

Validation of a Chinese Version of the Attitudes Toward Prisoners Scale

Using a Hong Kong–sourced sample of participants, this study set out to validate the Chinese version of the Attitudes Toward Prisoners (ATP-C) Scale and evaluate its psychometric properties. To provide further evidence for the ATP-C Scale’s validity, it was then administered to three groups varying in their volunteering experience in Hong Kong. Exploratory factor analysis revealed a four-factor structure that differs from the unidimensional model proposed by the scale developers. Cronbach’s alpha values were satisfactory for all four subscales, and construct validity of the ATP-C Scale was also assessed with a second sample of participants. Implications for the assessment of attitudes toward prisoners away from a one-dimensional spectrum and further directions for cross-cultural studies on related topics are discussed.