Accuracy-Complexity Tradeoff Analysis and Complexity Reduction Methods for Non-Stationary IMT-A MIMO Channel Models

open access journalHigh-mobility wireless communication systems have attracted growing interests in recent years. For the deployment of these systems, one fundamental work is to build accurate and efficient channel models. In high-mobility scenarios, it has been shown that the standardized channel models, e.g., IMT-Advanced (IMT-A) multiple-input multiple-output (MIMO) channel model, provide noticeable longer stationary intervals than measured results and the wide-sense stationary (WSS) assumption may be violated. Thus, the non-stationarity should be introduced to the IMT-A MIMO channel model to mimic the channel characteristics more accurately without losing too much efficiency. In this paper, we analyze and compare the computational complexity of the original WSS and non-stationary IMT-A MIMO channel models. Both the number of real operations and simulation time are used as complexity metrics. Since introducing the nonstationarity to the IMT-A MIMO channel model causes extra computational complexity, some computation reduction methods are proposed to simplify the non-stationary IMT-A MIMO channel model while retaining an acceptable accuracy. Statistical properties including the temporal autocorrelation function, spatial cross-correlation function, and stationary interval are chosen as the accuracy metrics for verifications. It is shown that the tradeoff between the computational complexity and modeling accuracy can be achieved by using these proposed complexity reduction methods

A Non-Stationary IMT-Advanced MIMO Channel Model for High-Mobility Wireless Communication Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.With the recent developments of high-mobility wireless communication systems, e.g., high-speed train (HST) and vehicle-to-vehicle (V2V) communication systems, the ability of conventional stationary channel models to mimic the underlying channel characteristics has widely been challenged. Measurements have demonstrated that the current standardized channel models, like IMT-Advanced (IMT-A) and WINNER II channel models, offer stationary intervals that are noticeably longer than those in measured HST channels. In this paper, we propose a non-stationary channel model with time-varying parameters including the number of clusters, the powers and the delays of the clusters, the angles of departure (AoDs), and the angles of arrival (AoAs). Based on the proposed non-stationary IMT-A channel model, important statistical properties, i.e., the local spatial cross-correlation function (CCF) and local temporal autocorrelation function (ACF) are derived and analyzed. Simulation results demonstrate that the statistical properties vary with time due to the non-stationarity of the proposed channel model. An excellent agreement is achieved between the stationary interval of the developed non-stationary IMT-A channel model and that of relevant HST measurement data, demonstrating the utility of the proposed channel model

HEAD: an FHE-based Privacy-preserving Cloud Computing Protocol with Compact Storage and Efficient Computation

Fully homomorphic encryption (FHE) provides a natural solution for privacy-preserving cloud computing, but a straightforward FHE protocol may suffer from high computational overhead and a large ciphertext expansion rate, especially for computation-intensive tasks over large data, which are the main obstacles toward practical privacy-preserving cloud computing. In this paper, we present HEAD, a generic privacy-preserving cloud computing protocol that can be based on most mainstream (typically a BGV or GSW style scheme) FHE schemes with more compact storage and less computational costs than the straightforward FHE counterpart. In particular, our protocol enjoys a ciphertext/plaintext expansion rate of 1 (i.e., no expansion) in a cloud computing server, instead of a factor of hundreds of thousands. This is achieved by means of ``pseudorandomly masked\u27\u27 ciphertexts, and the efficient transformations of them into FHE ciphertexts to facilitate privacy-preserving cloud computing. Depending on the underlying FHE in use, our HEAD protocol can be instantiated with the three masking techniques, namely modulo-subtraction-masking, modulo-division-masking, and XOR-masking, to support the decimal integer, real, or binary messages. Thanks to these masking techniques, various homomorphic computation tasks are made more efficient and less prone to noise accumulation. Furthermore, our multi-input masking and unmasking operations are more flexible than the FHE SIMD-batching, by supporting an on-demand configuration of FHE during each cloud computing request. We evaluate the performance of HEAD protocols on BFV, BGV, CKKS, and FHEW schemes based on the PALISADE and SEAL libraries, which confirms the theoretical analysis of the storage savings, the reduction in terms of computational complexity and noise accumulation. For example, in the BFV computation optimization, the sum or product of eight ciphertexts overhead is reduced from 336.3 ms to 6.3 ms, or from 1219.4 ms to 9.5 ms, respectively. We also embed HEAD into a mainstream database, PostgreSQL, in a client-server cloud storage and computing style. Compared with a straightforward FHE protocol, our experiments show that HEAD does not incur ciphertext expansion, and exhibits at least an order of magnitude saving in computing time at the server side for various tasks (on a hundred ciphertexts), by paying a reasonable price in client pre-processing time and communication. Our storage advantage not only gets around the database storage limitation but also reduces the I/O overhead

Biosynthesis of depsipeptides with a 3-hydroxybenzoate moiety and selective anticancer activities involves a chorismatase.

Neoantimycins are anticancer compounds of 15-membered ring antimycin-type depsipeptides. They are biosynthesized by a hybrid multimodular protein complex of nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS), typically from the starting precursor 3-formamidosalicylate. Examining fermentation extracts of Streptomyces conglobatus, here we discovered four new neoantimycin analogs, unantimycins B-E, in which 3-formamidosalicylates are replaced by an unusual 3-hydroxybenzoate (3-HBA) moiety. Unantimycins B-E exhibited levels of anticancer activities similar to those of the chemotherapeutic drug cisplatin in human lung cancer, colorectal cancer, and melanoma cells. Notably, they mostly displayed no significant toxicity toward noncancerous cells, unlike the serious toxicities generally reported for antimycin-type natural products. Using site-directed mutagenesis and heterologous expression, we found that unantimycin productions are correlated with the activity of a chorismatase homolog, the nat-hyg5 gene, from a type I PKS gene cluster. Biochemical analysis confirmed that the catalytic activity of Nat-hyg5 generates 3-HBA from chorismate. Finally, we achieved selective production of unantimycins B and C by engineering a chassis host. On the basis of these findings, we propose that unantimycin biosynthesis is directed by the neoantimycin-producing NRPS-PKS complex and initiated with the starter unit of 3-HBA. The elucidation of the biosynthetic unantimycin pathway reported here paves the way to improve the yield of these compounds for evaluation in oncotherapeutic applications

PINK1 Protects Against Gentamicin-Induced Sensory Hair Cell Damage: Possible Relation to Induction of Autophagy and Inhibition of p53 Signal Pathway

Phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1) is a gatekeeper of mitochondrial quality control. The present study was aimed to examine whether PINK1 possesses a protective function against gentamicin (GM)-induced sensory hair cell (HC) damage in vitro. The formation of parkin particles (a marker revealing the activation of PINK1 pathway which is a substrate of PINK1 and could signal depolarized mitochondria for clearance) and autophagy were determined by immunofluorescence staining. The expressions of PINK1, LC3B, cleaved-caspase 3 and p53 were measured by Western blotting. The levels of reactive oxygen species (ROS) and apoptosis were respectively evaluated by DCFH-DA staining, Annexin V Apoptosis Detection Kit and TUNEL staining. Cell viability was tested by a CCK8 kit. We found that treatment of 400 μM GM elicited the formation of ROS, which, in turn, led to PINK1 degradation, parkin recruitment, autophagy formation, an increase of p53 and cleaved-caspase 3 in HEI-OC1 cells and murine HCs. In contrast, co-treatment with ROS scavenger N-acetyl-L-cysteine (NAC) inhibited parkin recruitment, alleviated autophagy and p53 pathway-related damaged-cell elimination. Moreover, PINK1 interference contributed to a decrease of autophagy but an increase of p53 level in HEI-OC1 cells in response to GM stimulus. Findings from this work indicate that PINK1 alleviates the GM-elicited ototoxicity via induction of autophagy and resistance the increase of p53 in HCs

Characteristics of pathology and transcriptome profiling reveal features of immune response of acutely infected and asymptomatic infected of carp edema virus in Koi

Koi sleepy disease (KSD) is a high mortality and infection viral disease caused by carp edema virus (CEV), which was a serious threat to aquaculture of common carp and export trade of Koi worldwide. Asymptomatic infection is an important cause of the difficulty in preventing KSD and its worldwide spread, because asymptomatic infection can be activated under appropriate condition. However, the understanding of the molecular correlates of these infections is still unknown. The purpose of this study was to compare the pathology change, enzyme activity, immunoglobulin activity, host and viral gene expression differences in acutely infected and cohabiting asymptomatic Koi infected with CEV. Healthy Koi were used as a control. The gross pathology, histopathology and ultrastructural pathology showed the difference and characteristics damage to the tissues of Koi under different infection conditions. Periodic Acid-Schiff stain (PAS), enzyme activity and immunoglobulin activity revealed changes in the immune response of gill tissue between acutely infected, asymptomatic infected and healthy Koi. A total of 111 and 2484 upregulated genes and 257 and 4940 downregulated genes were founded in healthy Koi vs asymptomatic infected Koi and healthy Koi vs acutely infected Koi, respectively. Additionally, 878 upregulated genes and 1089 downregulated genes were identified in asymptomatic vs. acutely infected Koi. Immune gene categories and their corresponding genes in different comparison groups were revealed. A total of 3, 59 and 28 immune-related genes were identified in the group of healthy Koi vs asymptomatic infected Koi, healthy Koi vs acutely infected Koi and asymptomatic infected Koi vs acutely infected Koi, respectively. Nineteen immune-related genes have the same expression manner both in healthy Koi vs acutely infected Koi and asymptomatic Koi vs acutely infected Koi, while 9 immune-related genes were differentially expressed only in asymptomatic Koi vs acutely infected Koi, which may play a role in viral reactivation. In addition, 8 differentially expressed genes (DEGs) were validated by quantitative reverse transcription PCR (RT-qPCR), and the results were consistent with the RNA-Seq results. In conclusion, the data obtained in this study provide new evidence for further elucidating CEV-host interactions and the CEV infection mechanism and will facilitate the implementation of integrated strategies for controlling CEV infection and spread

Estimating aboveground green biomass in desert steppe using band depth indices

Estimation of aboveground green biomass is essential for evaluating grassland productivity and functioning. This study aimed to explore the potential of band depth indices for estimating aboveground green biomass in grassland with low canopy cover. Field spectral and biomass measurements were conducted during 2009 and 2010 growing seasons in desert steppe of Inner Mongolia. Band depth (BD), band depth ratio (BDR), normalised band depth index (NBDI), band depth normalised to area (BNA), maximum band depth (EDmax), and area of absorption region (BDarea) extracted from red absorption region (650-740 nm) were utilised as band depth indices. Results indicated that: (1) BD at individual bands between 655 and 716 nm showed good accuracy for aboveground green biomass estimation; (2) BD at 698 nm yielded the best accuracy (R-2 = 0.7, RMSECV = 29.6 g m(-2) for calibration; RMSE = 32.4 g m(-2), rRMSE = 26.9% for validation); (3) BDR, NBDI, and BNA at all bands were not reliable estimators of aboveground green biomass (R-2 45 g m(-2) for calibration; RMSE > 46 g m(-2), rRMSE > 39% for validation); (4) although the performance of BDmax (R-2 = 0.65, RMSECV = 32.1 g m(-2) for calibration; RMSE = 34.5 g m(-2), rRMSE = 28.7% for validation) and BDarea (R-2 = 0.69, RMSECV = 30.2 g m(-2) for calibration; RMSE = 33.1 g m(-2), rRMSE = 27.6% for validation) was slight lower than that of BD698nm, the performance was far better than that of BDR, NBDI, and BNA. Our results suggest that BD698nm has good potential to estimate aboveground green biomass in grassland with low canopy cover. The performance of BD698nm needs to be further tested using space-borne hyperspectral images. (C) 2014 IAgrE. Published by Elsevier Ltd. All rights reserved

Determination of green aboveground biomass in desert steppe using litter-soil-adjusted vegetation index

Accurate estimation of green aboveground biomass in arid and semiarid grassland is essential for a variety of studies, such as sustainable grassland management, fire risk assessment, climate change, and environmental degradation. A great need exists for the establishment of robust method for estimating green aboveground biomass in arid and semiarid grassland due to the influences of soil background and litter. In the study, a new index (litter-soil-adjusted vegetation index, L-SAVI) was proposed to estimate green aboveground biomass in arid and semiarid grassland. The L-SAVI was also evaluated based on biomass and spectra in situ measurements in the desert steppe of Inner Mongolia. Results showed that, the performance of the new index was better than that of NDVI (normalized difference vegetation index), SAVI (soil-adjusted vegetation index), MSAVI (modified soil-adjusted vegetation index), OSAVI (optimised soil-adjusted vegetation index), TSAVI (transformed soil-adjusted vegetation index), ATSAVI (adjusted transformed soil-adjusted vegetation index), PVI (perpendicular vegetation index), GSAVI (green-adjusted vegetation index), and L-ATSAVI (litter-corrected ATSAVI) in our study site. The logic behind the L-SAVI was to enable the SAVI to be less sensitive to litter by incorporating the CAI (cellulose absorption index) in the SAVI. In conclusion, the L-SAVI is a suitable predictor for complementing existing vegetation indices on green aboveground biomass estimation in arid and semiarid grassland