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The kurtogram developed from spectral kurtosis has been proven as an efficient tool for extracting the fault impulses in the diagnosis of rolling element bearings and gearboxes. Although the optimal narrowband chosen for demodulat...
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The kurtogram developed from spectral kurtosis has been proven as an efficient tool for extracting the fault impulses in the diagnosis of rolling element bearings and gearboxes. Although the optimal narrowband chosen for demodulation by kurtogram is accurate and effective in experimental environment, this approach is very sensitive to large random impulses that are frequently encountered in industrial applications. The narrowband with maximum kurtosis is always associated with large interferential impulses, rather than the bearing fault. To overcome this limitation, the periodic component to aperiodic component ratio (PAR) is utilized in this article to differentiate the two types of impulses. The novel method named the PAR-based kurtogram focuses on finding the significant frequency band with periodic impulses. The effectiveness of the proposed method is verified by simulations, a test rig of locomotive rolling element bearings, and bearing data from the Case Western Reserve University. The results show that the PAR-based kurtogram improves the robustness to interference from aperiodic impulses significantly, which is very useful for bearing faults diagnosis.
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Propionate is a short-chain fatty acid that is generated upon microbiome-mediated fiber fermentation in the intestine. By modulating immune and metabolic pathways, propionate exerts many health benefits. Key bacterial species, suc...
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Propionate is a short-chain fatty acid that is generated upon microbiome-mediated fiber fermentation in the intestine. By modulating immune and metabolic pathways, propionate exerts many health benefits. Key bacterial species, such as Bacteroides thetaiotaomicron, generate propionate, but the biochemical pathways and specific functions remain undetermined. We identified a gene operon-encoding methylmalonyl-CoA mutase (MCM) that contributes to propionate biosynthesis in B. thetaiotaomicron. Colonization of germ-free mice with wild-type or MCM-deficient strains as well as in vitro examination demonstrated that MCM-mediated propionate production promotes goblet cell differentiation and mucus-related gene expression. Intestinal organoids lacking the propionate receptor, GPR41, showed reduced goblet cell differentiation upon MCM-mediated propionate production. Furthermore, although wild-type B. thetaiotaomicron alleviated DSS-induced intestinal inflammation, this effect was abolished in mice receiving the MCM-deficient strain but restored upon propionate supplementation. These data emphasize the critical role of MCM-mediated propionate biosynthesis in goblet cell differentiation, offering potential pathways to ameliorate colitis.
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Molybdenum complexes are versatile and efficient for liquid phase olefin epoxidation reactions. Rational design of catalysts is critical to achieve high atom efficiency during epoxidation processes. Although liquid phase epoxidati...
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Molybdenum complexes are versatile and efficient for liquid phase olefin epoxidation reactions. Rational design of catalysts is critical to achieve high atom efficiency during epoxidation processes. Although liquid phase epoxidation has been a popular topic for decades, three key issues, (a) rational control of morphology of molybdenum nanoparticles, (b) manipulating metal-support interaction and (c) altering electronic configuration at molybdenum center remains unsolved in this area. Therefore, in this paper, we have critically revised recent research progress on heterogeneous molybdenum catalysts for facile liquid phase olefin epoxidation in terms of catalyst synthesis, surface characterization, catalytic performance and structure-function relationship. Furthermore, plausible reaction mechanisms will be systematically discussed with the aim to provide insights into fundamental understanding on novel epoxidation chemistry.
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Previous studies have shown independently that the skin and gut microbiota are closely associated with atopic dermatitis (AD); however, the microbiota across different habitats of AD patients as an integrated community has not bee...
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Previous studies have shown independently that the skin and gut microbiota are closely associated with atopic dermatitis (AD); however, the microbiota across different habitats of AD patients as an integrated community has not been characterized. In the present study, we comparatively analyzed the structure and function of the microbial communities in the skin, oral cavity, and gut of 172 AD patients and 120 healthy controls through 16S ribosomal RNA gene amplicon sequencing. The skin and oral cavity, but not the gut, of AD patients demonstrated differential reduction in the microbial diversity, and these were distinctly correlated with disease severity. Different degrees of shifts in the community structure were found among different habitats, and the lineage distance between the skin and oral microbiota of AD patients was closer than that observed in the controls. The different habitats of AD patients exhibited site-specific alterations at the genus level, and many oral-specific microbes of AD showed opposing directions of enrichment in the skin and oral cavity. Most interestingly, an inverse association in the functional pathways was found between the skin and oral microbiota of AD patients. Additionally, the alterations of the microbiota in different body sites of AD patients were differentially affected by age.
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Microbiota-induced tumorigenesis is well established in solid tumors of the gastrointestinal tract but rarely explored in hematologic malignancies. To determine the role of gut microbiota in lymphoma progression, we performed meta...
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Microbiota-induced tumorigenesis is well established in solid tumors of the gastrointestinal tract but rarely explored in hematologic malignancies. To determine the role of gut microbiota in lymphoma progression, we performed metagenomic sequencing on human primary gastrointestinal B cell lymphomas. We identified a distinct microbiota profile of intestinal lymphoma, with significantly decreased symbiotic microbes, particularly the genus Eubacterium and notably butyrate-producing Eubacterium rectale. Transfer of E. rectale-deficit microbiota of intestinal lymphoma patients to mice caused inflammation and tumor necrosis factor (TNF) production. Conversely, E. rectale treatment reduced TNF levels and the incidence of lymphoma in sensitized E mu-Myc mice. Moreover, lipopolysaccharide from the resident microbiota of lymphoma patients and mice synergizes with TNF signaling and reinforces the NF-kappa B pathway via the MyD88-dependent TLR4 signaling, amalgamating in enhanced intestinal B cell survival and proliferation. These findings reveal a mechanism of inflammationassociated lymphomagenesis and a potential clinical rationale for therapeutic targeting of gut microbiota.
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The detection and recovery of impulsive signature play a vital role in the diagnosis and prognosis of rolling element bearings. Though different approaches have been proposed to deal with this problem so far, challenges still exis...
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The detection and recovery of impulsive signature play a vital role in the diagnosis and prognosis of rolling element bearings. Though different approaches have been proposed to deal with this problem so far, challenges still exist when they are applied to the bearings operating under harsh working conditions. The difficulties mainly come from the multi-resonance and multi-modulation characteristics of bearing vibration signals. To overcome this limitation, a new methodology for the detection and recovery of fault impulses is presented in this paper. First, an improved harmonic product spectrum (IHPS) is proposed to detect and identify the multiple modulation sources buried in a vibration signal. With this method, the fault-related impulsive features could be recognized, while the influence caused by non-fault modulation is eliminated. On this basis, a harmonic significance index is further established to quantify the diagnostic information contained in a narrow band signal. By utilizing this index, the optimal resonance band where the fault impulses are most significant could be accurately determined. Finally, IHPS and sideband product spectrum are integrated to reduce the in-band noise and further recover the fault impulses. The performance of this method is evaluated by both simulated data and real vibration data measured from a train wheel bearing with a naturally developed defect. Compared with Kurtogram and Protrugram, the proposed method can detect the resonance band more precisely even in the presence of heavy noise and other impulsive vibration sources. Moreover, with the impulses recovery scheme, the double impact phenomenon caused by a distributed defect is extracted successfully. Benefiting from this, the defect size of a bearing can be estimated from its vibration signal without dismantling, which makes it a promising tool for the bearing diagnosis and prognosis in industrial applications. (C) 2016 Elsevier Ltd. All rights reserved.
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De-noising and enhancement of the weak fault signature from the noisy signal are crucial for fault diagnosis, as features are often very weak and masked by the background noise. Deconvolution methods have a significant advantage i...
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De-noising and enhancement of the weak fault signature from the noisy signal are crucial for fault diagnosis, as features are often very weak and masked by the background noise. Deconvolution methods have a significant advantage in counteracting the influence of the transmission path and enhancing the fault impulses. However, the performance of traditional deconvolution methods is greatly affected by some limitations, which restrict the application range. Therefore, this paper proposes a new deconvolution method, named sparse maximum harmonics-noise-ratio deconvolution ( SMHD), that employs a novel index, the harmonics-to-noise ratio ( HNR), to be the objective function for iteratively choosing the optimum filter coefficients to maximize HNR. SMHD is designed to enhance latent periodic impulse faults from heavy noise signals by calculating the HNR to estimate the period. A sparse factor is utilized to further suppress the noise and improve the signal-to-noise ratio of the filtered signal in every iteration step. In addition, the updating process of the sparse threshold value and the period guarantees the robustness of SMHD. On this basis, the new method not only overcomes the limitations associated with traditional deconvolution methods, minimum entropy deconvolution ( MED) and maximum correlated kurtosis deconvolution ( MCKD), but visual inspection is also better, even if the fault period is not provided in advance. Moreover, the efficiency of the proposed method is verified by simulations and bearing data from different test rigs. The results show that the proposed method is effective in the detection of various bearing faults compared with the original MED and MCKD.
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The size of the bearing spall fault can be estimated by the time interval between the roller's entry and exit points in the bearing vibration signal. However, the entry vibration response is typically low amplitude and masked in e...
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The size of the bearing spall fault can be estimated by the time interval between the roller's entry and exit points in the bearing vibration signal. However, the entry vibration response is typically low amplitude and masked in environmental noise. The time-domain average (TDA) method is effective for periodic impulse enhancement. However, bearing skidding is unavoidable during its running, and the cage's speed fluctuations caused by skidding will lead to non-periodicity of the impulses. The performance of TDA seriously deteriorated with such skidding because of the timevarying period. This paper presents the adaptive time-domain sliding average (ATDSA) method to address the bearing skidding problem. The similarity feature between each impulse segment is utilized, and a time delay matrix is constructed to estimate the skidding rate and mitigate the skidding effect. The frequency spectrum of the reconstructed signal shows clear sidebands with BCF interval. And the obtained averaged waveform has high resolution in both the low-frequency entry and high-frequency exit events. Simulation and experiment results show that it can effectively suppress the skidding effect and estimate the spall size correctly under different speeds.
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Unmanned surface vessel (USV) operations will change the future form of maritime wars profoundly, and one of the critical factors for victory is the cluster intelligence of USVs. Training USVs for combat using reinforcement learni...
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Unmanned surface vessel (USV) operations will change the future form of maritime wars profoundly, and one of the critical factors for victory is the cluster intelligence of USVs. Training USVs for combat using reinforcement learning (RL) is an important research direction. Sparse reward as one of the complex problems in reinforcement learning causes sluggish and inefficient USV training. Therefore, a modified random network distillation (MRND) algorithm is proposed for the sparse reward problem. This algorithm measures the weight of internal rewards by calculating the variance of the number of training steps in each training episode to adjust internal and external rewards dynamically. Through the self-play iterative training method, our algorithm, in conjunction with the classical proximal policy optimization (PPO) algorithm, can improve USV cluster intelligence rapidly. Based on USV cluster combat training environments constructed on Unity3D and ML-Agent Toolkits platform, three types of USV cluster combat simulations are conducted to validate the algorithm, including a target pursuit combat simulation, a USV cluster maritime combat simulation, and a USV cluster base offense and defense combat simulation. Simulation experiments have shown that USV clusters trained with the MRND algorithm converge quicker, acquire more rewards in fewer steps, and exhibit a higher level of intelligence than the USV cluster trained by the comparison algorithms.
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Textile dyeing wastewater is characterized by low biodegradability and high nitrogen strength, which is difficult to meet the increasingly stringent discharge requirements. Therefore, the tertiary nutrient and refractory organics ...
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Textile dyeing wastewater is characterized by low biodegradability and high nitrogen strength, which is difficult to meet the increasingly stringent discharge requirements. Therefore, the tertiary nutrient and refractory organics removal is considered and aerated biofilter is often adopted. However, the aerobic condition and carbon source shortage restrict tertiary biological nitrogen removal. In this study, iron scrap was introduced as the filter medium to enhance the pollutant removal capacity, and three aerobic biofilters were constructed. Biofilter Fe-CE was filled with iron scrap and ceramisite; biofilter Fe-AC was added with iron scrap and granular activated carbon, and biofilter CE only had ceramisite to pad as control system. After the biofilters were acclimatized by synthetic wastewater and actual dyeing wastewater, the optimal operation parameters based on nitrogen removal were determined as pH 7, gas water ratio 5:1, hydraulic retention time 8 h and C/N ratio 8.5:1. The iron scraps improved total nitrogen (TN) removal significantly, with TN removal efficiency of 68.7% and 57.3% in biofilter Fe-AC and biofilter Fe-CE, comparing with biofilter CE of 29.9%. Additionally, phosphorus and COD had better removal performance as well when iron scrap existed. Further investigation interpreted the reason for iron's facilitating effect on tertiary nutrient and refractory organics removal. The introduction of iron scrap made the habitat conditions such as pH values, DO concentrations and biomass contents inside the biofilters change towards the direction beneficial for pollutant elimination especially for nitrogen removal. In iron containing biofilters, the majority of nitrogen, phosphorus and organic pollutants were removed in the iron scrap layers, and more pollutants types appeared, implying that iron triggered pollutants to go through more diverse degradation or transformation pathways. Moreover, the phylum Proteoabcteria dominated in samples of ceramisite-containing biofilters, with abundances more than 40%. The iron scrap existence increased the abundances of phyla Bacteroidetes and Firmicutes, and triggered higher abundance of denitrification bacteria. (C) 2018 Elsevier Ltd. All rights reserved.
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