Self-Learning Hot Data Prediction: Where Echo State Network Meets NAND Flash Memories

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Well understanding the access behavior of hot data is significant for NAND flash memory due to its crucial impact on the efficiency of garbage collection (GC) and wear leveling (WL), which respectively dominate the performance and life span of SSD. Generally, both GC and WL rely greatly on the recognition accuracy of hot data identification (HDI). However, in this paper, the first time we propose a novel concept of hot data prediction (HDP), where the conventional HDI becomes unnecessary. First, we develop a hybrid optimized echo state network (HOESN), where sufficiently unbiased and continuously shrunk output weights are learnt by a sparse regression based on L2 and L1/2 regularization. Second, quantum-behaved particle swarm optimization (QPSO) is employed to compute reservoir parameters (i.e., global scaling factor, reservoir size, scaling coefficient and sparsity degree) for further improving prediction accuracy and reliability. Third, in the test on a chaotic benchmark (Rossler), the HOESN performs better than those of six recent state-of-the-art methods. Finally, simulation results about six typical metrics tested on five real disk workloads and on-chip experiment outcomes verified from an actual SSD prototype indicate that our HOESN-based HDP can reliably promote the access performance and endurance of NAND flash memories.Peer reviewe

Surface Defect Classification for Hot-Rolled Steel Strips by Selectively Dominant Local Binary Patterns

Developments in defect descriptors and computer vision-based algorithms for automatic optical inspection (AOI) allows for further development in image-based measurements. Defect classification is a vital part of an optical-imaging-based surface quality measuring instrument. The high-speed production rhythm of hot continuous rolling requires an ultra-rapid response to every component as well as algorithms in AOI instrument. In this paper, a simple, fast, yet robust texture descriptor, namely selectively dominant local binary patterns (SDLBPs), is proposed for defect classification. First, an intelligent searching algorithm with a quantitative thresholding mechanism is built to excavate the dominant non-uniform patterns (DNUPs). Second, two convertible schemes of pattern code mapping are developed for binary encoding of all uniform patterns and DNUPs. Third, feature extraction is carried out under SDLBP framework. Finally, an adaptive region weighting method is built for further strengthening the original nearest neighbor classifier in the feature matching stage. The extensive experiments carried out on an open texture database (Outex) and an actual surface defect database (Dragon) indicates that our proposed SDLBP yields promising performance on both classification accuracy and time efficiencyPeer reviewe

Responses of Soil Microbial Biomass and Enzyme Activities to Natural Restoration of Reclaimed Temperate Marshes After Abandonment

Restoration of reclaimed marshes has great effects on soil biological processes. However, the responses of soil microbial properties (microbial biomass and enzyme activities) to natural restoration of reclaimed marshes is poorly studied, especially in a long restoration chronosequence. This study assessed the responses of soil microbial properties to natural restoration and investigated the relationships between soil microbial properties and soil physico-chemical and plant properties. We selected a restoration chronosequence (1, 4, 8, 13, 17, 27 years) after farmland abandonment, a soybean field, and a natural marsh in Sanjiang Plain, northeast China. For each site, we analyzed the soil microbial biomass carbon and nitrogen (MBC and MBN), four enzymes (β-glucosidase, invertase, catalase, urease) activities, soil physico-chemical properties at 0–50 cm depths, and plant properties (biomass, height, and coverage). The MBC and MBN contents increased with restoration time, but MBN content slowed down after 8 years of restoration. After 27 years of restoration, the soil MBC and MBN contents were 15.7 and 3.2 times of those in the soybean field, but the largest contents of MBC and MBN in the restored sites were 7.78%, 27.76% lower than those in natural marshes, respectively. Moreover, soil enzyme activities and the geometric mean of enzymatic activities (GME) also increased with restoration but slowed down after 13 years of restoration. After 27 years of restoration, the GME was 2.9 times than that in the soybean field, but the largest GME in the restored sites was 31.15% lower than that in the natural marsh. MBC and MBN contents, soil enzyme activities, and GME had significant relationships with soil C:N ratio, organic carbon, nutrients (total nitrogen, available nitrogen, total phosphorus), bulk density, moisture content, pH, plant properties, (i.e. biomass, height, and coverage) (p < 0.01). Redundancy analysis revealed that soil C:N ratio, pH, moisture content, total nitrogen and phosphorus were main factors affecting MBC and MBN contents and enzyme activities. In conclusion, soil microbial properties can respond positively to the natural restoration process of the reclaimed marshes and were significantly correlated with specific parameters of soil physico-chemical and plant properties

Stoichiometry and stable isotopes of plants and their response to environmental factors in boreal peatland, Northeast China

The alterations of plant composition and diversity pose a threat to the stability of the carbon pool in boreal peatland under climate change. We collected the samples of three plant functional types (deciduous shrubs, evergreen shrubs, and sedge) in seven permafrost peatlands of the Great Hing’an Mountains, China, and measured the properties of total carbon (TC), nitrogen (TN), and phosphorus (TP), their stoichiometric ratios (C:N, C:P, and N:P), and the stable isotope values (δ13C and δ15N) of six tissues (ranging from leaves to roots). For TC, TN, and TP, the contents had an average of 470.69 ± 1.56, 8.03 ± 0.23, and 1.71 ± 0.61 mg·g−1, respectively. TC contents of sedge were lower than those of shrubs for the whole plant. The allocations of N and P to shrub leaves were higher than to stems and roots. There was a similar trend of TN and TP contents, and stoichiometric ratios from leaves to roots between deciduous shrubs and evergreen shrubs. Shrubs and sedge have similar C: N in leaves and fine roots, while leaves of sedge C:P and N:P ratios were higher than shrubs, mainly showed that sedge is N and P co-limitation and shrubs are N limitation. The values of δ13C and δ15N were significantly higher in leaves and roots of sedge than those of shrubs, which means shrubs have higher nutrient acquisition strategies. These results support the shrubs are expanding in the boreal peatland under climate warming through nutrient competition. TC contents of all deciduous shrubs and sedge tissues were positively linear correlated to MAT and the values of δ13C and δ15N in sedge had significant relationships with MAT and MAP. Our results imply warming can increase plant photosynthesis in boreal peatland, and sedge was more sensitive to climate change. These findings would be helpful to understanding the responses of different plant tissues to climate changes in permafrost peatland

Parameter design oriented analysis of the current control stability of the weak-grid-tied VSC

This paper studies the dynamic behaviors of weak-grid-tied VSCs with simplified transfer functions, which provides an accurate stability analysis and useful indications for tuning system parameters. A reduced-order multi-input multi-output (MIMO) transfer function that contains four single-input single-output (SISO) transfer functions for the weak-grid-tied VSC is first presented. It is found that the four SISO transfer functions share the same equivalent open-loop transfer function, i.e., the same stability conclusion. The Bode plots of the equivalent open-loop transfer function show that the inner current loop behaves as a band-pass filter whose maximum gain is approximately at the frequency of the PLL's bandwidth. By stability criterion, the harmonic amplification and instability occur when its maximum gain exceeds 0dB caused by high PLL's bandwidth, large grid impedance or high active power. It is also found that the target system is less stable when it works as an inverter than as a rectifier, due to the risk of the local positive feedback in the inverter mode. An effective criterion is further proposed to guide the selection of a proper PLL's bandwidth to ensure the stability of the VSC system. Simulation results validate the correctness of the analysis and the efficacy of the criterion

Antitumor effects of paeonol on mice bearing EMT6 breast Infiltrating ductal carcinoma

Paeonol is a micromolecular phenolic compound and it is the main component of Chinese herbal medicine that has been isolated from the root bark of Paeonia moutan. Paeonol is identified to have various physiological activities. In this study the antitumor activity and the possible mechanisms of paeonol were investigated in mice bearing EMT6 breast cancer model. The results showed that paeonol (150 mg/kg and 300 mg/kg) effectively reduced the weight of EMT6 breast tumor. Compared with the control group, paeonol significantly increased the number of tumor cells in G0/G1 phase, increased the number of cells in apoptosis and decreased the number of cells in S phase and G2/M, inhibited the expression of mutant p53, Bcl-2 and C-erbB-2 protein. The mechanisms of paeonol of antitumor effects might be associated with inhibition of tumor cells in G0/G1 phase, inducing cell apoptosis and inhibiting the expression of mutant p53, Bcl-2 and C-erbB-2 protein.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Mitigation of oscillations in three phase LCL-filtered grid converters based on proportional resonance and improved model predictive control

For three phase LCL -filtered gird converters, this paper designs a robust control strategy to reduce high frequency and subsynchronous or supersynchronous oscillations. Two components, namely the grid side inductor component and the LC filter component, constitute a three phase LCL -filtered grid converter. Model predictive control (MPC) with a disturbance observer is used to control the interconnection voltage of the LC filter. Proportional resonance (PR) control regulates the grid side current. It is possible to combine MPC with PR's advantages. The dynamic performance is enhanced by MPC's intrinsic ability to achieve active damping without extra control and reduce modulation latency. In addition to achieving zero steady state error, PR control greatly simplifies the control process when compared to the overall MPC of the entire grid converter. By analyzing the frequency response of the transfer function and output impedance, it is possible to determine that the proposed control has a sufficient phase margin and that, even when the system and control parameters change, the grid converters' output impedance is always resistive or inductive at the entire frequency, suppressing subsynchronous and high frequency oscillations. To further reduce the oscillations and harmonics, an improved MPC control framework and a feedback compensation mechanism are proposed. The effectiveness and reliability of the proposed control in current tracking, harmonic suppression, and response to grid impedance variations are verified by comparative analysis of simulation results

Multiple cardiac myxofibrosarcomas with complete right pulmonary artery occlusion: a case report

Primary cardiac myxofibrosarcoma is a rare form of cardiac malignant tumors. MFS usually involves the left atrium and presents as a unicentric or multicentric tumor mass. We reported on a 37-year-old female who presented with chest tightness and dyspnea for a month, dry cough, and occasionally having blood streak sputum for half a month. Echocardiography, cardiac computed tomography and cardiac positron emission tomography revealed multiple tumors in the heart. The right ventricle and right pulmonary artery were involved, with occlusion of the right pulmonary artery. Cardiac tumors were surgically resected and were consistent with low-grade MFS. No recurrence or metastasis occurred at 20 months of follow-up

Causal relationship between gut microbiota and differentiated thyroid cancer: a two-sample Mendelian randomization study

BackgroundThe gut microbiota has been significantly associated with differentiated thyroid cancer (DTC). However, the causal relationship between the gut microbiota and DTC remains unexplored.MethodsGenome-wide association study (GWAS) summary databases were utilized to select exposures and outcomes. The Mendelian randomization (MR) method was employed to investigate the causal relationship between the gut microbiota and DTC. A sensitivity analysis was performed to assess the reliability of the findings.ResultsFour bacterial traits were associated with the risk of DTC: Class Mollicutes [odds ratio (OR) = 10.953, 95% confidence interval (95% CI): 2.333–51.428, p = 0.002], Phylum Tenericutes (OR = 10.953, 95% CI: 2.333–51.428, p = 0.002), Genus Eggerthella (OR = 3.219, 95% CI: 1.033–10.024, p = 0.044), and Order Rhodospirillales (OR = 2.829, 95% CI: 1.096–7.299, p = 0.032). The large 95% CI range for the Class Mollicutes and the Phylum Tenericutes may be attributed to the small sample size. Additionally, four other bacterial traits were negatively associated with DTC: Genus Eubacterium fissicatena group (OR = 0.381, 95% CI: 0.148–0.979, p = 0.045), Genus Lachnospiraceae UCG008 (OR = 0.317, 95% CI: 0.125–0.801, p = 0.015), Genus Christensenellaceae R-7 group (OR = 0.134, 95% CI: 0.020–0.886, p = 0.037), and Genus Escherichia Shigella (OR = 0.170, 95% CI: 0.037–0.769, p = 0.021).ConclusionThese findings contribute to our understanding of the pathological mechanisms underlying DTC and provide novel insights for the clinical treatment of DTC