Improved Soft-Aided Decoding of Product Codes With Dynamic Reliability Scores

Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss compared to a soft-decision decoder. Recently, several hybrid algorithms have been proposed aimed to improve the performance of iBDD decoders via the aid of a certain amount of soft information while keeping the decoding complexity similarly low as in iBDD. We propose a novel hybrid low-complexity decoder for PCs based on error-and-erasure (EaE) decoding and dynamic reliability scores (DRSs). This decoder is based on a novel EaE component code decoder, which is able to decode beyond the designed distance of the component code but suffers from an increased miscorrection probability. The DRSs, reflecting the reliability of a codeword bit, are used to detect and avoid miscorrections. Simulation results show that this policy can reduce the miscorrection rate significantly and improves the decoding performance. The decoder requires only ternary message passing and a slight increase of computational complexity compared to iBDD, which makes it suitable for high-speed communication systems. Coding gains of up to 1.2 dB compared to the conventional iBDD decoder are observed

Improved Soft-aided Decoding of Product Codes with Dynamic Reliability Scores

Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss compared to a soft-decision decoder. Recently, several hybrid algorithms have been proposed aimed to improve the performance of iBDD decoders via the aid of a certain amount of soft information while keeping the decoding complexity similarly low as in iBDD. We propose a novel hybrid low-complexity decoder for PCs based on error-and-erasure (EaE) decoding and dynamic reliability scores (DRSs). This decoder is based on a novel EaE component code decoder, which is able to decode beyond the designed distance of the component code but suffers from an increased miscorrection probability. The DRSs, reflecting the reliability of a codeword bit, are used to detect and avoid miscorrections. Simulation results show that this policy can reduce the miscorrection rate significantly and improves the decoding performance. The decoder requires only ternary message passing and a slight increase of computational complexity compared to iBDD, which makes it suitable for high-speed communication systems. Coding gains of up to 1.2 dB compared to the conventional iBDD decoder are observed.Comment: Submitted to IEE

Quaternary Neural Belief Propagation Decoding of Quantum LDPC Codes with Overcomplete Check Matrices

Quantum low-density parity-check (QLDPC) codes are promising candidates for error correction in quantum computers. One of the major challenges in implementing QLDPC codes in quantum computers is the lack of a universal decoder. In this work, we first propose to decode QLDPC codes with a belief propagation (BP) decoder operating on overcomplete check matrices. Then, we extend the neural BP (NBP) decoder, which was originally studied for suboptimal binary BP decoding of QLPDC codes, to quaternary BP decoders. Numerical simulation results demonstrate that both approaches as well as their combination yield a low-latency, high-performance decoder for several short to moderate length QLDPC codes.Comment: arXiv admin note: text overlap with arXiv:2212.1024

The recent ecological efficiency development in China: interactive systems of economy, society and environment

Ecological efficiency (EE) provides much reference for formulating appropriate regional economic, social and environmental policies to promote sustainable development. Interactive subsystems of economy, society and environment within EE system have been considered in this paper. By innovatively integrating the merits of two advanced economic research methods (global super efficiency network data envelopment analysis (GSE-NDEA) and panel vector autoregression (PVAR) and updating the EE evaluation indicator system by following the new features of sustainable development in the recent China, this paper comprehensively evaluates EE by drawing evidence from 3 regions in China during the period of 2011–2020, and further reveals how the three subsystems within EE system interact to achieve EE enhancement. The findings show EE and its three subsystems’ trend, the major constrains of EE development, the regional discrepancies in EE progress, and the interactions among the subsystems of economy-society-environment within the EE system in different regions of China. The policy implications are proposed accordingly

Analysis of Vibration Response Law of Multistory Building under Tunnel Blasting Loads

This paper takes the Dizong tunnel engineering as its background. Combined with the on-site monitoring data, the wavelet packet program based on MATLAB was compiled to study the vibration response of the four-story masonry building in a typical southwestern mountainous area of China under the blasting load. The results showed that the maximum particle velocity increased to the 3rd floor and attenuation occurred on the 4th floor. The particle velocity in the z-direction was the largest and should be paid attention. The dominant frequency of the building showed a trend from high frequency to low frequency, the duration became short, and the acceleration decreased to the 4th floor. With the increase of the building floor, the main frequency domain of the building decreased and then gradually tended to the low-frequency domain. The high-frequency particle velocity gradually decreased, gathered to the low frequency, and developed from the dispersed multiband to the concentrated low-frequency band. The total energy value of vibration increased to the 3rd floor and then decreased to the 4th floor. The energy of the building was between 0 and 171.6 Hz. The higher the floor was, the more concentrated the energy was in the low-frequency domain

Effects of Grazing Intensity on the Carbon, Nitrogen and Phosphorus Content, Stoichiometry and Storage of Plant Functional Groups in a Meadow Steppe

Studies on the impacts of grazing on carbon, nitrogen, and phosphorus stoichiometry and storage are crucial for better understanding the nutrient cycles of grasslands ecosystems. Using a controlled grazing experimental platform in a meadow steppe ecosystem, the effects of different stocking rates (0.00, 0.23, 0.34, 0.46, 0.69, and 0.92 AU ha−1) on the carbon, nitrogen, and phosphorus contents of plant functional groups were explored. The major results were: (1) The carbon content of Gramineae Barnhart was significantly reduced by grazing intensity (p Cyperaceae Rotundus was significantly higher than that of the other groups; the total nitrogen content of Cyperaceae and other groups and total phosphorus contents of Gramineae, Leguminosae Sp., Cyperaceae, and other groups all increased significantly with increasing grazing intensity (p Gramineae, Leguminosae, and Ranunculaceae L. decreased significantly with increasing grazing intensity. Heavy grazing reduced the carbon, nitrogen, and phosphorus storage amounts of Cyperaceae and other groups, while the carbon, nitrogen, and phosphorus storage amounts of Compositae were the largest under moderate grazing. (3) The nitrogen content of each functional group was highly significantly negatively correlated with the C/N ratio, and the phosphorus content was highly significantly negatively correlated with the C/P ratio. Grazing and foraging affected the growth of the different functional groups, which in turn affected their carbon, nitrogen, and phosphorus content, stoichiometry, and storage. Moderate grazing improved the nutrient utilization efficiency of grassland and is beneficial for promoting sustainable grassland development

Impacts of Grazing Disturbance on Soil Nitrogen Component Contents and Storages in a <i>Leymus chinensis</i> Meadow Steppe

Long-term grazing leads to soil degradation in Inner Mongolia grassland. Based on the Hulunbeier meadow steppe, the variation characteristics of soil nitrogen content and storage in soil layers between 0–40 cm, under six different grazing intensities, and the response of vegetation and other physical and chemical properties of soil to grazing were studied. The main results were as follows: (1) Moderate grazing increased soil total nitrogen (TN), soluble total nitrogen (STN) and microbial biomass nitrogen (MBN) contents, while heavy grazing decreased MBN content. In the year with more rain, heavy grazing increased nitrate nitrogen (NO3−-N) content and storage, while less rain increased ammonium nitrogen (NH4+-N) content. (2) The proportion of 0–40 cm nitrogen components showed an upward trend in the year with more rain, and the opposite in the years with less rainfall with the increase of grazing intensity. Soil soluble organic nitrogen (SON) and NO3−-N storages decreased and MBN storage increased in rainy years. (3) Soil nitrogen component contents and storages were correlated with plant growth status, soil moisture (SM) and soil bulk density (SBD), and were significantly negatively correlated with soil temperature (ST) and pH (p < 0.05). The content and storage of soil nitrogen were affected by grazing, soil, vegetation, meteorological and other environmental factors. Moderate grazing was more conducive to the improvement of soil nitrogen storage capacity and the healthy development of grassland

Response of Temperate <i>Leymus chinensis</i> Meadow Steppe Plant Community Composition, Biomass Allocation, and Species Diversity to Nitrogen and Phosphorus Addition

Studies on the impacts of fertilization on plant production and species diversity are crucial for better maintaining the stability of grassland ecosystems and restoring degraded grasslands. Using a controlled fertilization experimental platform in a temperate Leymus chinensis meadow steppe ecosystem, the effects of different levels of nitrogen (N) and phosphorus (P) addition on plant community structure, biomass allocation, diversity, and the correlation relationship were explored. The major results were as follows: (1) The structural composition of the plant community changed after different levels of N and P addition; the dominance ratio and biomass of Poaceae plants increased gradually with increasing N and P addition levels. (2) The addition of N and P increased the height, density and coverage of the plant community, the biomass of the dominant L. chinensis and plant community and the total productivity of grassland, and reduced the root–shoot ratio of grassland biomass. For example, plant community biomass, gramineous plant biomass and grassland total productivity increased by 84.46–204.08%, 162.64–424.20%, and 38.12–46.44%, respectively, after N and P addition. (3) The community richness, diversity, and evenness indices decreased overall and showed binomial regression after N and P addition; the functional group of Poaceae plants was highly significantly negatively correlated with species diversity indices and was highly significantly positively correlated with the aboveground biomass of L. chinensis and community; Leguminosae plants and Ranunculaceae plants were highly significantly positively correlated with Margalef and Patrick richness indices; Ranunculaceae plants were highly significantly and negatively correlated with L. chinensis biomass, community biomass, and Poaceae plants. Moderate fertilization not only improved the plant community structure and productivity but was also beneficial for maintaining the grassland species diversity and stability

Serum Cytokine Profile in Relation to the Severity of Coronary Artery Disease

Objectives. To investigate the potential association of a set of serum cytokines with the severity of coronary artery disease (CAD). Methods. A total of 201 patients who underwent coronary angiography for chest discomfort were enrolled. The concentrations of serum IFN-γ, TNF-α, IL-2, IL-4, IL-6, IL-10, IL-9, and IL-17 were determined by xMAP multiplex technology. The CAD severity was assessed by Gensini score (GS). Results. The serum levels of TNF-α, IL-6, IL-9, IL-10, and IL-17 were significantly higher in high GS group (GS ≥ 38.5) than those in low GS group (GS < 38.5). Positive correlations were also found between these cytokines and the severity of CAD. After adjustment for other associated factors, three serum cytokines (IL-6, IL-9, and IL-17) and two clinical risk factors (creatinine and LDL-C) were identified as the independent predictors of increased severity of CAD. ROC curve analysis revealed that the logistic regression risk prediction model had a good performance on predicting CAD severity. Conclusions. Combinatorial analysis of serum cytokines (IL-6, IL-9, and IL-17) with clinical risk factors (creatinine and LDL-C) may contribute to the evaluation of the severity of CAD and may help guide the risk stratification of angina patients, especially in primary health facilities and in the catheter lab resource-limited settings