Integration of Signal and Artificial Noise in MIMO Wiretap Channel

In this paper, the integrated signal-to-artificial noise (ISAN) design is applied in MIMO wiretap channel to ensure wireless communication security. When the information of eavesdropper is unknown, the total power is divided into two parts: signal and artificial noise. The signal can secure certain quality at the legitimate receiver. The artificial noise which is in the null space of the receiver channel matrix can deteriorate eavesdropper channel by the method of beam forming. The artificial noise power is distributed evenly in other space, so that the eavesdropper channel is deteriorated in all directions. The signal to interface and noise ratio (SINR) is regarded as the efficient parameter on measuring reliability and security of information at the legitimate receiver. The simulations reveal that ISAN can deteriorate the eavesdropper channel and safeguard the information transmission on the premise of the given SINR of the legitimate receiver

High Viral Load of Human Bocavirus Correlates with Duration of Wheezing in Children with Severe Lower Respiratory Tract Infection

Background: Human bocavirus (HBoV) is a newly discovered parvovirus and increasing evidences are available to support its role as an etiologic agent in lower respiratory tract infection (LRTI). The objective of this study is to assess the impact of HBoV viral load on clinical characteristics in children who were HBoV positive and suffered severe LRTI. Methods: Lower respiratory tract aspirates from 186 hospitalized children with severe LRTI were obtained by bronchoscopy. HBoVs were detected by real-time PCR and other 10 infectious agents were examined using PCR and/or direct fluorescent assay. Results: Thirty-one patients (24.6%) were tested positive for HBoV in the respiratory tract aspirates. Fifteen samples had a high viral load (.10 4 copies/mL) and the other sixteen samples had a low viral load (,10 4 copies/mL). The duration of presented wheezing and hospitalization was longer in children with high viral load of HBoV than that in children with low viral load. The days of wheezing showed a correlation with viral load of HBoV. Conclusion: We confirmed that HBoV was frequently detected in patients with severe LRTI. Wheezing was one of the most common symptoms presented by patients with positive HBoV. A high HBoV viral load could be an etiologic agent for LRTI

Uric acid predicts recovery of left ventricular function and adverse events in heart failure with reduced ejection fraction: Potential mechanistic insight from network analyses

Background and Aims: Heart failure with reduced ejection fraction (HFrEF) still carries a high risk for a sustained decrease in left ventricular ejection fraction (LVEF) even with the optimal medical therapy. Currently, there is no effective tool to stratify these patients according to their recovery potential. We tested the hypothesis that uric acid (UA) could predict recovery of LVEF and prognosis of HFrEF patients and attempted to explore mechanistic relationship between hyperuricemia and HFrEF. Methods: HFrEF patients with hyperuricemia were selected from the National Inpatient Sample (NIS) 2016-2018 database and our Xianyang prospective cohort study. Demographics, cardiac risk factors, and cardiovascular events were identified. Network-based analysis was utilized to examine the relationship between recovery of LVEF and hyperuricemia, and we further elucidated the underlying mechanisms for the impact of hyperuricemia on HFrEF. Results: After adjusting confounding factors by propensity score matching, hyperuricemia was a determinant of HFrEF [OR 1.247 (1.172-1.328); Conclusion: Lower baseline UA value predicted the LVEF recovery and less long-term adverse events in HFrEF patients. Our results provide new insights into underlying mechanistic relationship between hyperuricemia and HFrEF

Deregulation of manganese superoxide dismutase (SOD2) expression and lymph node metastasis in tongue squamous cell carcinoma

<p>Abstract</p> <p>Background</p> <p>Lymph node metastasis is a critical event in the progression of tongue squamous cell carcinoma (TSCC). The identification of biomarkers associated with the metastatic process would provide critical prognostic information to facilitate clinical decision making. Previous studies showed that deregulation of manganese superoxide dismutase (SOD2) expression is a frequent event in TSCC and may be associated with enhanced cell invasion. The purpose of this study is to further evaluate whether the expression level of SOD2 is correlated with the metastatic status in TSCC patients.</p> <p>Methods</p> <p>We first examined the SOD2 expression at mRNA level on 53 TSCC and 22 normal control samples based on pooled-analysis of existing microarray datasets. To confirm our observations, we examined the expression of SOD2 at protein level on an additional TSCC patient cohort (n = 100), as well as 31 premalignant dysplasias, 15 normal tongue mucosa, and 32 lymph node metastatic diseases by immunohistochemistry (IHC).</p> <p>Results</p> <p>The SOD2 mRNA level in primary TSCC tissue is reversely correlated with lymph node metastasis in the first TSCC patient cohort. The SOD2 protein level in primary TSCC tissue is also reversely correlated with lymph node metastasis in the second TSCC patient cohort. Deregulation of SOD2 expression is a common event in TSCC and appears to be associated with disease progression. Statistical analysis revealed that the reduced SOD2 expression in primary tumor tissue is associated with lymph node metastasis in both TSCC patient cohorts examined.</p> <p>Conclusions</p> <p>Our study suggested that the deregulation of SOD2 in TSCC has potential predictive values for lymph node metastasis, and may serve as a therapeutic target for patients at risk of metastasis.</p

Quantifying the Impact of Different Ways to Delimit Study Areas on the Assessment of Species Diversity of an Urban Forest

Assessing the species diversity of an urban forest is important for understanding its structure and functions, but the result can be affected by sampling methods, times, and delimitations of the study area. In this study, we examined the influence of different ways to delimit boundaries of urban areas on the assessment of species diversity of urban forests through a case study conducted in Haikou, China. We surveyed the species diversity of the urban forest in Haikou twice using the same sampling protocol but two commonly used delimitations of the urban area. The two surveys produced significantly different estimates of species richness of the urban forest. Recorded species richness was 228 (144 woody and 84 herbaceous species) and 303 (164 woody and 139 herbaceous species) for the first and the second survey, respectively. The rarefaction analysis indicated that species richness of woody plants recorded in the two surveys could converge by doubling the sample size, but species richness of herbaceous plants was significantly different between the two surveys at the 95% confidence interval even at three times the original sample size. The value of the Simpson dissimilarity index between the two surveys was 0.417 and 0.357 for woody and herbaceous plants respectively, which implied noticeable dissimilarity of species compositions of plant assemblages in the two areas. We concluded that the assessment of biodiversity of an urban forest can be affected significantly by how the boundary of an urban area is defined. Caution should be taken when comparing species diversities of urban forests reported in different studies, especially when richness measures are used

Non-intrusive load decomposition algorithm based on temporal convolutional network and long short-term memory model combined with strongly correlated power sequences

The deep learning neural network method is used to complete the non-intrusive load decomposition task, which often has the problems of poor model performance and low decomposition accuracy. In order to solve the problem that the decomposition accuracy is reduced because the model cannot fully learn all the power characteristics of a specific load in deep learning, a non-intrusive method based on the combination of TCN-LSTM two-layer neural network and strongly correlated power sequence is proposed. Firstly, the load decomposition algorithm learns the time-attribute power information mapping relationship through TCN, obtains the load state pre-identification result and coupling it with the prior data, obtains the independent strongly correlated power sequence of each electrical device to replace the original aggregate power sequence to improve the proportion of the target signal in the mixed signal, and inputs it into the LSTM to capture advanced time-domain information. The measured power sequence is used as a label to implement the neural network model. After training, the decomposed power sequences of five experimental loads were obtained and compared with the actual power sequences. In the part of case analysis, the UK-DALE public data set is used to verify the algorithm in the paper, and by comparing the algorithm in the paper with two typical algorithms, the effectiveness of the model in the paper is verified, and the high-precision load decomposition task is completed

Effects of Permafrost Degradation on the Hydrological Regime in the Source Regions of the Yangtze and Yellow Rivers, China

Climate warming has intensified permafrost degradation, which could have a variety of implications on the hydrological regime in permafrost regions. In this study, we analyzed the effects of permafrost degradation on the hydrological regime via four hydrological variables for 10 unregulated catchments in the source regions of the Yangtze and Yellow rivers. The results demonstrate that catchments with high permafrost coverage are expected to have an increased winter discharge ratio (proportion of winter discharge contribution to total annual flow), a decreased recession coefficient and a decreased ratio of Qmax/Qmin due to permafrost degradation. However, the great storage effects of lakes and wetlands, which could contribute to more groundwater instead of direct surface discharge, may affect the hydrological effects of permafrost degradation and result in the abnormal performance at catchment scale. The correlation analysis between summer precipitation (July–September) and the following winter discharge (December–February) indicates that permafrost degradation may affect the redistribution of summer precipitation towards the following winter discharge via increasing the soil storage capacity and delaying the release of water into streams in permafrost regions. However, unlike the Arctic and sub-Arctic regions, no significant changes for the hydrological regime (four hydrological variables) are detected over the individual periods of records for each catchment. Decreased precipitation in summer seems to reduce the water infiltration to supply the groundwater, which weakens the effects of permafrost degradation on the hydrological regime. This study implies that the storage effects of lakes and wetlands and the changes of summer precipitation patterns should be considered in future permafrost hydrological simulations, which have suggested that a large increase in groundwater discharge to streams will likely occur in response to permafrost degradation due to the warming climate in the ideal scenario

Survey of Security Technologies on Wireless Sensor Networks

Because of their low cost and adaptability, wireless sensor networks are widely used in civil, military, and commercial fields and other fields. However, since the sensor node in the calculation of the capacity, battery capacity, and storage capacity are restricted by the limitations and inherent characteristics of the sensor networks, compared to traditional networks, which makes wireless sensor networks face more security threats. This paper summarized research progress of sensor network security issues as three aspects, key management, authentication, and secure routing, analyzed and commented on these results advantages and disadvantages and pointed out the future direction of the hot research field

Precision cylindricity error measurement system design and error analysis

A precise cylindricity error measurement system is designed for cylindricity error measurement. Firstly, three-point cylindricity error separation algorithm and cylindricity evaluation method are introduced. By eliminating rotation error and random error, accurate roundness error, radius error of different sections and least square center coordinate of measured sections are calculated, which eliminates the influence of installation eccentricity on measurement results. Then, according to the three-point error measurement principle, a set of precise circle is designed. Cylindricity error measurement system, and the use of OpenGL graphics technology to reconstruct the shape of the cylinder and three-dimensional display. Finally, a number of groups of experiments were carried out on the cylinder standard parts, and the experimental results were analyzed. The results show that the system can realize cylindricity error measurement based on three-point method, which is consistent with the nominal accuracy of standard parts, and has certain application value