Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.Comment: 17 pages, 12 figures; Open Access at http://www.mdpi.org/sensors/papers/s8074265.pd

Deep learning-based correlation analysis for probabilistic power flow considering renewable energy and energy storage

Developing photovoltaic (PV) and wind power is one of the most efficient approaches to reduce carbon emissions. Accumulating the PV and wind energy resources at different geographical locations can minimize total power output variance as injected into the power systems. To some extent, a low degree of the variance amplitude of the renewable resources can reduce the requirement of in-depth regulation and dispatch for the fossil fuel-based thermal power plants. Such an issue can alternatively reduce carbon emissions. Thus, the correlation problem by minimizing the variance of total PV and wind power plays a vital role in power system planning and operation. However, the synergistic effect of power output correlation is mainly considered on the generation side, and it is often neglected for the correlation relationship between the power grid components. To address this problem, this paper proposes a correlation coefficient analysis method for the power grid, which can quantify the relationship between energy storage and the probabilistic power flow (PPF) of the grid. Subsequently, to accelerate the mapping efficiency of power correlation coefficients, a novel deep neural network (DNN) optimized by multi-task learning and attention mechanism (MA-DNN) is developed to predict power flow fluctuations. Finally, the simulation results show that in IEEE 9-bus and IEEE14-bus systems, the strong correlation grouping percentage between the power correlation coefficients and power flow fluctuations reached 92% and 51%, respectively. The percentages of groups indicating weak correlation are 4% and 38%. In the modified IEEE 23-bus system, the computational accuracy of MA-DNN is improved by 37.35% compared to the PPF based on Latin hypercube sampling. Additionally, the MA-DNN regression prediction model exhibits a substantial improvement in assessing power flow fluctuations in the power grid, achieving a speed enhancement of 758.85 times compared to the conventional probability power flow algorithms. These findings provide the rapid selection of the grid access point with the minimum power flow fluctuations

Physiological and Metabolomic Alterations in Macrocystis pyrifera upon Exposure to Chromium(VI)

1593-1599In order to comprehensively characterize the effects of chromium (VI) on physiological and metabonomic performance of Macrocystis pyrifera, the sporophytes were exposed to 2 mg L-1 potassium dichromate for 3 days. M. pyrifera sporophytes showed decreased pigment content and Chla fuloresecnece parameters with the accumulation of Cr(VI). The carbon content was clearly increased, while the content of nitrogen, hydrogen and sulfur were little changed. Moreover, an untargeted metabolomic analysis was carried out in order to investigate the metabolic effects and to obtain a comprehensive profiling of induced metabolites during Cr stress. Absolute quantification of 14 different metabolites was obtained through GC-MS methods. The principal component analysis showed a clear separation between control and Cr treated samples. Some pathways including carbon fixation, sulfur metabolism, taurine and hypotaurine metabolism were affected by Cr (VI) stress. These findings provided valuable information to elucidate the mechanism of M. pyrifera upon Cr (VI) stress

Visual field mean deviation and relevant factors in 928 Chinese retinitis pigmentosa patients

AIM: To investigate the associations between demographic and clinical factors with the rate of visual field mean derivation (MD) decline in retinitis pigmentosa (RP) patients. METHODS: Correlations of MDs with the visual acuity and retinal pigmentation were analyzed in 928 RP patients. MD decreasing rate in 10y and potential influences of gender, age, family history and retinal pigmentation on the rate were explored in 201 RP patients. RESULTS: In the 928 patients, average MD and visual acuity were -14.44±8.61 dB and 0.79±0.35 respectively and when MD was lower than -9.18 dB the visual acuity would be below 1.0 (20/20). The average MD medium between eyes with or without retinal pigmentation was -14.82 dB. In 123 non-pigmented eyes, the average MD were lower than the medium but in 153 pigmented eyes it was higher than that. In the 201 patients, the average decreasing value of MD in 10 years’ period was -8.01±3.66 dB and the value were correlated to retinal pigmentation but not to gender, age or RP family history. CONCLUSION: The rate of MD decline in RP eyes is significantly related to retinal pigmentation. Our study demonstrates the quantitative rate of MD decline in RP patients and the value of MD could well reflect the severity of RP

Fractional matching preclusion for butterfly derived networks

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. As a generalization, Liu and Liu [18] recently introduced the concept of fractional matching preclusion number. The fractional matching preclusion number (FMP number) of G, denoted by fmp(G), is the minimum number of edges whose deletion leaves the resulting graph without a fractional perfect matching. The fractional strong matching preclusion number (FSMP number) of G, denoted by fsmp(G), is the minimum number of vertices and edges whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we study the fractional matching preclusion number and the fractional strong matching preclusion number for butterfly network, augmented butterfly network and enhanced butterfly network

Daidzein: A review of pharmacological effects

Background: Daidzein is an isoflavone with extensive nutritious value and is mainly extracted from soy plants. It is also called phytoestrogen due to its structural similarity to the human hormone estrogen. However, daidzein is distinct from estrogen due to the specificity of the estrogen receptor (ER) complex. In recent years, the pharmacological properties of daidzein have been extensively investigated and considerable progress has been made. The present review aims to evaluate the pharmacological effects and mechanisms of daidzein as reported in scientific literature.Materials and Methods: Studies were identified as reported in PubMed, Elsevier, Scholar, and Springer over the last ten years and this resulted in the identification of 112 papers.Results: Daidzein is reported to play a significant role in the prevention and treatment of a variety of diseases such as cancer, cardiovascular disease, diabetes, osteoporosis, skin disease, and neurodegenerative disease. This pharmacological activity is attributed to various metabolites including equol and trihydroxy isoflavone.Conclusion: Daidzein appears to play a significant role in the prevention of a variety of diseases and has the potential of being used in a clinical setting. However, further research is needed to understand its molecular mechanisms and safety for use in humans.Keywords: Plant, natural product, phytoestrogen, pharmacolog

DAIDZEIN: A REVIEW OF PHARMACOLOGICAL EFFECTS

Background: Daidzein is an isoflavone with extensive nutritious value and is mainly extracted from soy plants. It is also called phytoestrogen due to its structural similarity to the human hormone estrogen. However, daidzein is distinct from estrogen due to the specificity of the estrogen receptor (ER) complex. In recent years, the pharmacological properties of daidzein have been extensively investigated and considerable progress has been made. The present review aims to evaluate the pharmacological effects and mechanisms of daidzein as reported in scientific literature. Materials and Methods: Studies were identified as reported in PubMed, Elsevier, Scholar, and Springer over the last ten years and this resulted in the identification of 112 papers. Results: Daidzein is reported to play a significant role in the prevention and treatment of a variety of diseases such as cancer, cardiovascular disease, diabetes, osteoporosis, skin disease, and neurodegenerative disease. This pharmacological activity is attributed to various metabolites including equol and trihydroxy isoflavone. Conclusion: Daidzein appears to play a significant role in the prevention of a variety of diseases and has the potential of being used in a clinical setting. However, further research is needed to understand its molecular mechanisms and safety for use in humans. Keywords: Plant, natural product, phytoestrogen, pharmacolog

Are We Building on the Rock? On the Importance of Data Preprocessing for Code Summarization

Code summarization, the task of generating useful comments given the code, has long been of interest. Most of the existing code summarization models are trained and validated on widely-used code comment benchmark datasets. However, little is known about the quality of the benchmark datasets built from real-world projects. Are the benchmark datasets as good as expected? To bridge the gap, we conduct a systematic research to assess and improve the quality of four benchmark datasets widely used for code summarization tasks. First, we propose an automated code-comment cleaning tool that can accurately detect noisy data caused by inappropriate data preprocessing operations from existing benchmark datasets. Then, we apply the tool to further assess the data quality of the four benchmark datasets, based on the detected noises. Finally, we conduct comparative experiments to investigate the impact of noisy data on the performance of code summarization models. The results show that these data preprocessing noises widely exist in all four benchmark datasets, and removing these noisy data leads to a significant improvement on the performance of code summarization. We believe that the findings and insights will enable a better understanding of data quality in code summarization tasks, and pave the way for relevant research and practice

Smad7 enables STAT3 activation and promotes pluripotency independent of TGF-β signaling

TGF-β and related growth factors critically regulate cell potency and functions. Smad7 is induced by TGF-βs and inhibits the physiological functions of TGF-β signaling. This study describes an unexpected finding that Smad7 promotes self-renewal of embryonic stem cells (ESCs) in a manner independent of its inhibition on TGF-β signaling. Instead, Smad7 acts to induce activation of transcription factor signal transducers and activators of transcription 3 (STAT3) in ESCs. Smad7 activates STAT3 through its direct binding to the cytokine receptor upstream of STAT3 activation. In agreement with the role of STAT3 in maintaining ESC pluripotency, Smad7 promotes ESC self-renewal and induced pluripotent stem cell reprogramming. This finding illustrates a regulatory mechanism for Smad7 in maintaining pluripotency, and likely in cancer and inflammation