Reconfigurable Intelligent Surface Enabled Joint Backscattering and Communication

Reconfigurable intelligent surface (RIS) as an essential topic in the sixth-generation (6G) communications aims to enhance communication performance or mitigate undesired transmission. However, the controllability of each reflecting element on RIS also enables it to act as a passive backscatter device (BD) and transmit its information to reader devices. In this paper, we propose a RIS-enabled joint backscattering and communication (JBAC) system, where the backscatter communication coexists with the primary communication and occupies no extra spectrum. Specifically, the RIS modifies its reflecting pattern to act as a passive BD and reflect its own information back to the base station (BS) in the backscatter communication, while helping the primary communication from the BS to the users simultaneously. We further present an iterative active beamforming and reflecting pattern design to maximize the user average transmission rate of the primary communication and the goodput of the backscatter communication by solving the formulated multi-objective optimization problem (MOOP). Numerical results fully uncover the impacts of the number of reflecting elements and the reflecting patterns on the system performance, and demonstrate the effectiveness of the proposed scheme. Important practical implementation remarks have also been discussed.Comment: 11 pages, 8 figures, published to IEEE TV

Exploiting Behavioral Consistence for Universal User Representation

User modeling is critical for developing personalized services in industry. A common way for user modeling is to learn user representations that can be distinguished by their interests or preferences. In this work, we focus on developing universal user representation model. The obtained universal representations are expected to contain rich information, and be applicable to various downstream applications without further modifications (e.g., user preference prediction and user profiling). Accordingly, we can be free from the heavy work of training task-specific models for every downstream task as in previous works. In specific, we propose Self-supervised User Modeling Network (SUMN) to encode behavior data into the universal representation. It includes two key components. The first one is a new learning objective, which guides the model to fully identify and preserve valuable user information under a self-supervised learning framework. The other one is a multi-hop aggregation layer, which benefits the model capacity in aggregating diverse behaviors. Extensive experiments on benchmark datasets show that our approach can outperform state-of-the-art unsupervised representation methods, and even compete with supervised ones.Comment: Preprint of accepted AAAI2021 pape

Improved Differential Cryptanalysis on SPECK Using Plaintext Structures

Plaintext structures are a commonly-used technique for improving differential cryptanalysis. Generally, there are two types of plaintext structures: multiple-differential structures and truncated-differential structures. Both types have been widely used in cryptanalysis of S-box-based ciphers while for SPECK, an Addition-Rotation-XOR (ARX) cipher, the truncated-differential structure has not been used so far. In this paper, we investigate the properties of modular addition and propose a method to construct truncated-differential structures for SPECK. Moreover, we show that a combination of both types of structures is also possible for SPECK. For recovering the key of SPECK, we propose dedicated algorithms and apply them to various differential distinguishers, which helps to obtain a series of improved attacks on all variants of SPECK. Notably, on SPECK128, the time complexity of the attack can be reduced by a factor up to 2^15. The results show that the combination of both structures helps to improve the data and time complexity at the same time, as in the cryptanalysis of S-box-based ciphers

The tumor suppressive role of CAMK2N1 in castration-resistant prostate cancer.

Prostate cancer at advanced stages including metastatic and castration-resistant cancer remains incurable due to the lack of effective therapies. The CAMK2N1 gene, cloned and characterized as an inhibitor of CaMKII (calcium/calmodulin-dependent protein kinase II), has been shown to affect tumorigenesis and tumor growth. However, it is still unknown whether CAMK2N1 plays a role in prostate cancer development. We first examined the protein and mRNA levels of CAMK2N1 and observed a significant decrease in human prostate cancers comparing to normal prostate tissues. Re-expression of CAMK2N1 in prostate cancer cells reduced cellular proliferation, arrested cells in G0/G1 phases, and induced apoptotic cell death accompanied by down-regulation of IGF-1, ErbB2, and VEGF downstream kinases PI3K/AKT, as well as the MEK/ERK-mediated signaling pathways. Conversely, knockdown of CAMK2N1 had a significant opposite effects on these phenotypes. Our analyses suggest that CAMK2N1 plays a tumor suppressive role in prostate cancer cells. Reduced CAMK2N1 expression correlates to human prostate cancer progression and predicts poor clinical outcome, indicating that CAMK2N1 may serve as a biomarker. The inhibition of tumor growth by expressing CAMK2N1 established a role of CAMK2N1 as a therapeutic target

CAMK2N1 inhibits prostate cancer progression through androgen receptor-dependent signaling.

Castration resistance is a major obstacle to hormonal therapy for prostate cancer patients. Although androgen independence of prostate cancer growth is a known contributing factor to endocrine resistance, the mechanism of androgen receptor deregulation in endocrine resistance is still poorly understood. Herein, the CAMK2N1 was shown to contribute to the human prostate cancer cell growth and survival through AR-dependent signaling. Reduced expression of CAMK2N1 was correlated to recurrence-free survival of prostate cancer patients with high levels of AR expression in their tumor. CAMK2N1 and AR signaling form an auto-regulatory negative feedback loop: CAMK2N1 expression was down-regulated by AR activation; while CAMK2N1 inhibited AR expression and transactivation through CAMKII and AKT pathways. Knockdown of CAMK2N1 in prostate cancer cells alleviated Casodex inhibition of cell growth, while re-expression of CAMK2N1 in castration-resistant cells sensitized the cells to Casodex treatment. Taken together, our findings suggest that CAMK2N1 plays a tumor suppressive role and serves as a crucial determinant of the resistance of prostate cancer to endocrine therapies

Genome-Wide SNP Data Revealed the Extent of Linkage Disequilibrium, Persistence of Phase and Effective Population Size in Purebred and Crossbred Buffalo Populations

Linkage disequilibrium (LD) is a useful parameter for guiding the accuracy and power of both genome-wide association studies (GWAS) and genomic selection (GS) among different livestock species. The present study evaluated the extent of LD, persistence of phase and effective population size (Ne) for the purebred (Mediterranean buffalo; n = 411) and crossbred [Mediterranean × Jianghan × Nili-Ravi buffalo, n = 9; Murrah × Nili-Ravi × local (Xilin or Fuzhong) buffalo, n = 36] buffalo populations using the 90K Buffalo SNP genotyping array. The results showed that the average square of correlation coefficient (r2) between adjacent SNP was 0.13 ± 0.19 across all autosomes for purebred and 0.09 ± 0.13 for crossbred, and the most rapid decline in LD was observed over the first 200 kb. Estimated r2 ≥ 0.2 extended up to ~50 kb in crossbred and 170 kb in purebred populations, while average r2 values ≥0.3 were respectively observed in the ~10 and 60 kb in the crossbred and purebred populations. The largest phase correlation (RP, C = 0.47) was observed at the distance of 100 kb, suggesting that this phase was not actively preserved between the two populations. Estimated Ne for the purebred and crossbred population at the current generation was 387 and 113 individuals, respectively. These findings may provide useful information to guide the GS and GWAS in buffaloes

Dynamic response analysis of the rotating blade of horizontal axis wind turbine

This paper presents a dynamic response analysis of the blade of horizontal axis wind turbines using finite element method. The blade is treated as a cantilever and modeled with two-node beam element. The blade element-momentum theory is applied to calculate the aerodynamic loads. Dynamic inflow and dynamic stall are taken into account to reflect the transient aerodynamics. The centrifugal stiffening is introduced to consider the restoring effects of centrifugal force. An aerodynamic damping model is presented for calculating the overall damping ratio instantaneously during time-domain simulation. The structural dynamic equation is solved using Newmark method and the overall dynamic response of the blade is obtained based on the modal superposition principle. Applying the proposed method, the power production load case of a 1.0 MW wind turbine operating in turbulent wind field is simulated. The simulation results indicate that the blades of large-scale horizontal axis wind turbines undergo significant vibration and deflection during operation, and the centrifugal stiffening and aerodynamic damping both considerably affect the structural response of the blade