New Constructions of 2-D Golay Complementary Array Sets With Highly Flexible Array Sizes for Massive MIMO Omni-directional Transmission

This letter is concerned with efficient design of two-dimensional (2-D) Golay complementary array sets (GCASs) with ideal aperiodic sums for two correlation directions. Two new direct constructions of 2-D GCASs with highly flexible array sizes are proposed. The core idea is to truncate certain columns from large arrays generated by 2-D extended generalized Boolean functions (EGBFs). We show that these 2-D GCASs lead to highly flexible uniform rectangular array (URA) configurations for precoding matrices in omni-directional massive multi-input multi-output (MIMO) transmission

Gravitation-Based Edge Detection in Hyperspectral Images

Edge detection is one of the key issues in the field of computer vision and remote sensing image analysis. Although many different edge-detection methods have been proposed for gray-scale, color, and multispectral images, they still face difficulties when extracting edge features from hyperspectral images (HSIs) that contain a large number of bands with very narrow gap in the spectral domain. Inspired by the clustering characteristic of the gravitational theory, a novel edge-detection algorithm for HSIs is presented in this paper. In the proposed method, we first construct a joint feature space by combining the spatial and spectral features. Each pixel of HSI is assumed to be a celestial object in the joint feature space, which exerts gravitational force to each of its neighboring pixel. Accordingly, each object travels in the joint feature space until it reaches a stable equilibrium. At the equilibrium, the image is smoothed and the edges are enhanced, where the edge pixels can be easily distinguished by calculating the gravitational potential energy. The proposed edge-detection method is tested on several benchmark HSIs and the obtained results were compared with those of four state-of-the-art approaches. The experimental results confirm the efficacy of the proposed method

Study on the constructions of optimal almost quaternary sequences with period 2q

Based on the Chinese remainder theorem and cyclotomic classes of order 4,the constructions of almost quaternary sequences with period N=2q (where q is an odd prime) was studied.According to the number of “0” in the two positions y(0) and y(q),three types of optimal almost quaternary sequences with optimal balance property and out-of-phase autocorrelation values as{0,-2},{0,2,-2} and {0,-2,-2i,2i} were constructed respectively.Through these constructions,all the almost quaternary sequences constructed are balanced and optimal.These constructed sequences extend the existence range of the balanced optimal quaternary sequences and provide more optimal sequences for practical applications

Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances

Remote sensing object detection (RSOD), one of the most fundamental and challenging tasks in the remote sensing field, has received longstanding attention. In recent years, deep learning techniques have demonstrated robust feature representation capabilities and led to a big leap in the development of RSOD techniques. In this era of rapid technical evolution, this review aims to present a comprehensive review of the recent achievements in deep learning based RSOD methods. More than 300 papers are covered in this review. We identify five main challenges in RSOD, including multi-scale object detection, rotated object detection, weak object detection, tiny object detection, and object detection with limited supervision, and systematically review the corresponding methods developed in a hierarchical division manner. We also review the widely used benchmark datasets and evaluation metrics within the field of RSOD, as well as the application scenarios for RSOD. Future research directions are provided for further promoting the research in RSOD.Comment: Accepted with IEEE Geoscience and Remote Sensing Magazine. More than 300 papers relevant to the RSOD filed were reviewed in this surve

New construction of enhanced cross Z-complementary set for generalized spatial modulation

In order to expand the existence space of enhanced cross Z-complementary set (E-CZCS), based on the extended generalized Boolean function (EGBF), the direct construction method of enhanced cross Z-complementary sets was proposed. The constructed q-ary E-CZCS had flexible and variable size, and their length was no longer limited to the traditional power of two. At the same time, the obtained enhanced cross Z-complementary sets was used as the training sequence of the generalized spatial modulation (GSM) system for channel estimation. The simulation results show that the enhanced cross Z-complementary sets can achieve optimal channel estimation. This presumably provides greater flexibility in the selection of training sequences in generalized spatial modulation systems

Balanced optimal almost binary sequence pairs of period N≡1（mod4）

Based on the combinatorial design theory， the constructions of balanced optimal almost binary sequence pairs of period N≡1（mod 4）were researched.The maximal cross-correlation values θc were obtained by different combinations of （almost） binary sequence pairs.Furthermore， three new bounds on the autocorrelation values under the precondition of the value of θc=1，2，3 were presented individually.Meanwhile，four types of balanced（almost）optimal almost binary sequence pairs were generated， which satisfied the cross-correlation values and autocorrelation theory bounds.Through the constructions， the range of the cross-correlation values is expanded and the cross-correlation value of the optimal binary sequence pairs is further reduced.More than odd， the value of sequence length parameter f can be any integer， which enriches the existence space of the optimal binary sequence pair

The Constructions of Almost Binary Sequence Pairs and Binary Sequence Pairs with Three-Level Autocorrelation

In this letter, a new class of almost binary sequence pairs with a single zero element and three autocorrelation values is presented. The new almost binary sequence pairs are based on cyclic difference sets and difference set pairs. By applying the method to the binary sequence pairs, new binary sequence pairs with three-level autocorrelation are constructed. It is shown that new sequence pairs from our constructions are balanced or almost balanced and have optimal three-level autocorrelation when the characteristic sequences or sequence pairs of difference sets or difference set pairs are balanced or almost balanced and have optimal autocorrelations

A modified Ranson score to predict disease severity, organ failure, pancreatic necrosis, and pancreatic infection in patients with acute pancreatitis

BackgroundAlthough there are several scoring systems currently used to predict the severity of acute pancreatitis, each of them has limitations. Determine the accuracy of a modified Ranson score in predicting disease severity and prognosis in patients with acute pancreatitis (AP).MethodsAP patients admitted or transferred to our institution were allocated to a modeling group (n = 304) or a validation group (n = 192). A modified Ranson score was determined by excluding the fluid sequestration parameter and including the modified computed tomography severity index (CTSI). The diagnostic performance of the modified Ranson score was compared with the Ranson score, modified CTSI, and bedside index of severity in acute pancreatitis (BISAP) score in predicting disease severity, organ failure, pancreatic necrosis and pancreatic infection.ResultsThe modified Ranson score had significantly better accuracy that the Ranson score in predicting all four outcome measures in the modeling group and in the validation group (all p < 0.05). For the modeling group the modified Ranson score had the best accuracy for predicting disease severity and organ failure, and second-best accuracy for predicting pancreatic necrosis and pancreatic infection. For the verification group, it had the best accuracy for predicting organ failure, second-best accuracy for predicting disease severity and pancreatic necrosis, and third-best accuracy for predicting pancreatic infection.ConclusionThe modified Ranson score provided better accuracy than the Ranson score in predicting disease severity, organ failure, pancreatic necrosis and pancreatic infection. Relative to the other scoring systems, the modified Ranson system was superior in predicting organ failure

The failure to express a protein disulphide isomerase-like protein results in a floury endosperm and an endoplasmic reticulum stress response in rice

The rice somaclonal mutant T3612 produces small grains with a floury endosperm, caused by the loose packing of starch granules. The positional cloning of the mutation revealed a deletion in a gene encoding a protein disulphide isomerase-like enzyme (PDIL1-1). In the wild type, PDIL1-1 was expressed throughout the plant, but most intensely in the developing grain. In T3612, its expression was abolished, resulting in a decrease in the activity of plastidial phosphorylase and pullulanase, and an increase in that of soluble starch synthase I and ADP-glucose pyrophosphorylase. The amylopectin in the T3612 endosperm showed an increase in chains with a degree of polymerization 8–13 compared with the wild type. The expression in the mutant's endosperm of certain endoplasmic reticulum stress-responsive genes was noticeably elevated. PDIL1-1 appears to play an important role in starch synthesis. Its absence is associated with endoplasmic reticulum stress in the endosperm, which is likely to underlie the formation of the floury endosperm in the T3612 mutant

Systematic Analysis of Survival-Associated Alternative Splicing Signatures in Thyroid Carcinoma

Alternative splicing (AS) is a key mechanism involved in regulating gene expression and is closely related to tumorigenesis. The incidence of thyroid cancer (THCA) has increased during the past decade, and the role of AS in THCA is still unclear. Here, we used TCGA and to generate AS maps in patients with THCA. Univariate analysis revealed 825 AS events related to the survival of THCA. Five prognostic models of AA, AD, AT, ES, and ME events were obtained through lasso and multivariate analyses, and the final prediction model was established by integrating all the AS events in the five prediction models. Kaplan–Meier survival analysis revealed that the overall survival rate of patients in the high-risk group was significantly shorter than that of patients in the low-risk group. The ROC results revealed that the prognostic capabilities of each model at 3, 5, and 8 years were all greater than 0.7, and the final prognostic capabilities of the models were all greater than 0.9. By reviewing other databases and utilizing qPCR, we verified the established THCA gene model. In addition, gene set enrichment analysis showed that abnormal AS events might play key roles in tumor development and progression of THCA by participating in changes in molecular structure, homeostasis of the cell environment and in cell energy. Finally, a splicing correlation network was established to reveal the potential regulatory patterns between the predicted splicing factors and AS event candidates. In summary, AS should be considered an important prognostic indicator of THCA. Our results will help to elucidate the underlying mechanism of AS in the process of THCA tumorigenesis and broaden the prognostic and clinical application of molecular targeted therapy for THCA