Number Of Detectable Targets Research Articles

Interpolation-Based Direction-of-Arrival Estimation for Coprime Arrays via Covariance Matrix Fitting

Coprime arrays can highly increase degree-of-freedom (DOF) by exploiting the equivalent virtual signal. However, since the corresponding virtual array constructed by the coprime array is always a non-uniform linear array (non-ULA), most existing direction-of-arrival (DOA) estimation algorithms fail to utilize all received information and result in performance degradation. To address this issue, we propose a novel interpolation approach for coprime arrays to convert the virtual array into a ULA with which all received information can be efficiently utilized. In this paper, we consider a weighted covariance matrix fitting criterion to formulate a semi-definite programming (SDP) problem with respect to the interpolated virtual signal. After that, we can reconstruct a Hermitian Toeplitz covariance matrix corresponding to the interpolated ULA in a gridless manner, and the number of detectable targets is ulteriorly increased with the reconstructed covariance matrix. The proposed approach is hyperparameter-free so that the tedious process of selecting regularization parameters is avoided. Numerical experiments validate the superiority of the proposed interpolation-based DOA estimation algorithm in terms of DOF characteristic, resolution ability and estimation accuracy compared with several existing techniques.

Cell-Free DNA Analysis Demonstrates Comprehensive Genomic Profiling and a Facile Method to Sensitively in Multiple Myeloma

Background: Multiple myeloma (MM) is a plasma cell malignancy characterized by complex cytogenetic and molecular abnormalities including translocations involving the immunoglobin heavy chain locus and mutations involving numerous oncogenic signaling pathways. Fluorescence in situ hybridization (FISH) has emerged as the most useful current cytogenetic assessment and provide a new level of insight into the correlation of myeloma prognosis risk model. However, the identification or sorting of malignant cells is required before FISH probes and only involved expansion of the types of probe and number of detectable targets is reached. Cell-free DNA (cfDNA) offers the potential for minimally invasive genome-wide profiling of tumor alterations without tumor biopsy and may be associated with cancer precision medicine and patient prognosis.Methods: In this retrospective cohort study, we identified 37 patients from 9 relapsed/refractory (RR) and 33 newly diagnosed (ND) patients were analyzed for chromosomal copy number imbalance using the ultrasensitive chromosomal aneuploidy detector (UCAD) platform.Results: Chromosome copy number aberration (CNA) were frequently (82.6%, N=46) detected in MM plasma cell free DNA. Applying UCAD to cfDNA, FISH in CD138 purified bone marrow aspirates, and some matched bone marrow biopsies, we find concordance in copy number alterations (~81%) between liquid and tumor biopsies. Significant copy number changes, including 1q gains, 13q deletion and 17p deletion could be found in 57.89%, 54.05%, and 16.67% in plasma of MM, which is higher percentage than FISH assay (46.81%, 28.26%, and 8.89%), respectively. Besides, chromosome 6p and 6q were determined the higher frequency aberration from UCAD. Moreover, a higher frequency of copy number aberrations and variations was detected in RR patients than ND (100% vs 78.4%, respectively), obviously CNAs heterogeneity displayed in advanced disease. In the inconsistent some samples, UCAD from the plasma and bone marrow showed the similar results, which indicated the FISH is underdetermined and insensitivity in some patients' routine inspection.Conclusion: We conclude that cfDNA analysis as an adjunct to BM biopsy represents a noninvasive and broaden the applicability strategy for comprehensive genomic profiling and therapeutic monitoring of MM. DisclosuresNo relevant conflicts of interest to declare.

Analysis of sparse MIMO radar

We consider a multiple-input–multiple-output radar system and derive a theoretical framework for the recoverability of targets in the azimuth–range domain and the azimuth–range–Doppler domain via sparse approximation algorithms. Using tools developed in the area of compressive sensing, we prove bounds on the number of detectable targets and the achievable resolution in the presence of additive noise. Our theoretical findings are validated by numerical simulations.