•Propose a novel deep convolutional neural network-based method for remaining useful life predictions.•No prior expertise on prognostics and signal processing is required, that facilitates the ...application of the proposed method.•Effects of the key factors on the prognostic performance are widely investigated and the model parameters are optimized.•Experiments on a popular aero-engine degradation dataset (C-MAPSS) and comparisons with the related state-of-the-art results validate the effectiveness and superiority of the proposed method.
Traditionally, system prognostics and health management (PHM) depends on sufficient prior knowledge of critical components degradation process in order to predict the remaining useful life (RUL). However, the accurate physical or expert models are not available in most cases. This paper proposes a new data-driven approach for prognostics using deep convolution neural networks (DCNN). Time window approach is employed for sample preparation in order for better feature extraction by DCNN. Raw collected data with normalization are directly used as inputs to the proposed network, and no prior expertise on prognostics and signal processing is required, that facilitates the application of the proposed method. In order to show the effectiveness of the proposed approach, experiments on the popular C-MAPSS dataset for aero-engine unit prognostics are carried out. High prognostic accuracy on the RUL estimation is achieved. The superiority of the proposed method is demonstrated by comparisons with other popular approaches and the state-of-the-art results on the same dataset. The results of this study suggest that the proposed data-driven prognostic method offers a new and promising approach.
Various studies have shown that soils surrounding mining areas are seriously polluted with heavy metals. Determining the effects of natural factors on spatial distribution of heavy metals is ...important for determining the distribution characteristics of heavy metals in soils. In this study, an 8km buffer zone surrounding a typical non-ferrous metal mine in Suxian District of Hunan Province, China, was selected as the study area, and statistical, spatial autocorrelation and spatial interpolation analyses were used to obtain descriptive statistics and spatial autocorrelation characteristics of As, Pb, Cu, and Zn in soil. Additionally, the distributions of soil heavy metals under the influences of natural factors, including terrain (elevation and slope), wind direction and distance from a river, were determined. Layout of sampling sites, spatial changes of heavy metal contents at high elevations and concentration differences between upwind and downwind directions were then evaluated. The following results were obtained: (1) At low elevations, heavy metal concentrations decreased slightly, then increased considerably with increasing elevation. At high elevations, heavy metal concentrations first decreased, then increased, then decreased with increasing elevation. As the slope increased, heavy metal contents increased then decreased. (2) Heavy metal contents changed consistently in the upwind and downwind directions. Heavy metal contents were highest in 1km buffer zone and decreased with increasing distance from the mining area. The largest decrease in heavy metal concentrations was in 2km buffer zone. Perennial wind promotes the transport of heavy metals in downwind direction. (3) The spatial extent of the influence of the river on Pb, Zn and Cu in the soil was 800m. (4) The influence of the terrain on the heavy metal concentrations was greater than that of the wind. These results provide a scientific basis for preventing and mitigating heavy metal soil pollution in areas surrounding mines.
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•Distributions of As, Pb, Cu, Zn under influences of natural factors are explored.•Distributions of heavy metals with slopes are different from that of elevations.•Perennial wind promotes the spread of heavy metal to downwind direction.•Influence ranges of river on Pb, Zn and Cu in surrounding soil are within 800m.•Influence of terrain on distributions of heavy metals is greater than wind.
Prostate cancer (PC) is a very important kind of male malignancies. When PC evolves into a stage of hormone resistance or metastasis, the fatality rate is very high. Currently, discoveries and ...advances in miRNAs as biomarkers have opened the potential for the diagnosis of PC, especially early diagnosis. miRNAs not only can noninvasively or minimally invasively identify PC, but also can provide the data for optimization and personalization of therapy. Moreover, miRNAs have been shown to play an important role to predict prognosis of PC. The purpose of this meta‐analysis is to integrate the currently published expression profile data of miRNAs in PC, and evaluate the value of miRNAs as biomarkers for PC. All of relevant records were selected via electronic databases: Pubmed, Embase, Cochrane, and CNKI based on the assessment of title, , and full text. we extracted mean ± SD or fold change of miRNAs expression levels in PC versus BPH or normal controls. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS) and recurrence‐free survival (RFS), were also calculated to detect the relationship between high miRNAs expression and PC prognosis. Selected 104 articles were published in 2007‐2017. According to the inclusion criteria, 104 records were included for this meta‐analysis. The pooled or stratified analyze showed 10 up‐regulated miRNAs (miR‐18a, miR‐34a, miR‐106b, miR‐141, miR‐182, miR‐183, miR‐200a/b, miR‐301a, and miR‐375) and 14 down‐regulated miRNAs (miR‐1, miR‐23b/27b, miR‐30c, miR‐99b, miR‐139‐5p, miR‐152, miR‐187, miR‐204, miR‐205, miR‐224, miR‐452, miR‐505, and let‐7c) had relatively good diagnostic and predictive potential to discriminate PC from BPH/normal controls. Furthermore, high expression of miR‐32 and low expression of let‐7c could be used to differentiate metastatic PC from local/primary PC. Additional interesting findings were that the expression profiles of five miRNAs (miR‐21, miR‐30c, miR‐129, miR‐145, and let‐7c) could predict poor RFS of PC, while the evaluation of miR‐375 was associated with worse OS. miRNAs are important regulators in PC progression. Our results indicate that miRNAs are suitable for predicting the different stages of PC. The detection of miRNAs is an effective way to control patient's prognosis and evaluate therapeutic efficacy. However, large‐scale detections based on common clinical guidelines are still necessary to further validate our conclusions, due to the bias induced by molecular heterogeneity and differences in study design and detection methods.
miRNAs have been shown to play an important role to predict prognosis of PC. The purpose of this meta‐analysis is to integrate the currently published expression profile data of miRNAs in PC, and evaluate the value of miRNAs as biomarkers for PC.
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•Electro-stimulation of microbial chain elongation for ethanol and CO2 conversion.•Caproate was produced at 2.41 ± 0.69 g L−1 d−1, and reached to 7.66 ± 1.38 g L−1.•Maximum ...SelectivityS was 91.47 ± 0.58% and SelectivityS+E was 80.28 ± 0.52%.•Carbon of 23.43 ± 0.69% in final products was from CO2.•Microbial electrochemical caproate was produced without base addition.
The production of value added chemicals from CO2 is of critical importance for the practical application of microbial electrosynthesis (MES). Here, a binary electron donor (ED) design (using electrode and ethanol) was introduced to provide an efficient caproate production with the bioconversion of both CO2 and ethanol. A maximum caproate production rate of 2.41 ± 0.69 g L−1 d−1, and a final concentration of 7.66 ± 1.38 g L−1 was achieved. Caproate production selectivity based on the substrate increased to 91.47 ± 0.58% (Binary EDs) from 32.22 ± 32.58% (open circuit Electrode ED). An observed amount of 23.43 ± 0.69% of carbon within the final binary ED products originated from the CO2. This work proves for the first time the potential of caproate production from CO2 utilization and ethanol upgrading using solid electrodes to regulate the chain elongation process.
Confronted with serious environmental problems caused by the growing mountains of plastic packaging waste, the prevention and control of plastic waste has become a major concern for most countries. ...In addition to the recycling of plastic wastes, design for recycling can effectively prevent plastic packaging from turning into solid waste at the source. The reasons are that the design for recycling can extend the life cycle of plastic packaging and increase the recycling values of plastic waste; moreover, recycling technologies are helpful for improving the properties of recycled plastics and expanding the application market for recycled materials. This review systematically discussed the present theory, practice, strategies, and methods of design for recycling plastic packaging and extracted valuable advanced design ideas and successful cases. Furthermore, the development status of automatic sorting methods, mechanical recycling of individual and mixed plastic waste, as well as chemical recycling of thermoplastic and thermosetting plastic waste, were comprehensively summarized. The combination of the front-end design for recycling and the back-end recycling technologies can accelerate the transformation of the plastic packaging industry from an unsustainable model to an economic cycle model and then achieve the unity of economic, ecological, and social benefits.
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•Converting xylose to caproate (C6) by mixed culture fermentation was verified.•The maximum concentration of caproate was 2.06 g/L in a batch reactor.•Caproate concentration were ...between 0.45 and 1.07 g/L at pH 5.0 in a CSTR reactor.•Genus Caproiciproducens was unexpectedly identified as the main caproate producer.•Fatty acid biosynthesis, not reverse β-oxidation, may be the pathway to produce C6.
Caproate production by mixed culture fermentation (MCF) is economically attractive. Xylose is known as the second most abundant sugar in nature, however, producing caproate from xylose is never reported. In this study, caproate production from xylose by mesophilic MCF was firstly investigated. The results showed that as pH decreasing to 5.0, the caproate concentration was 2.06 g/L in a batch reactor and was between 0.45 and 1.07 g/L in a continuously stirred reactor. Microbial analysis illustrated that Caproiciproducens and Clostridium_sensu_stricto_12, as two main identified caproate producers, occupied over 50% and around 10% of mixed culture, respectively. Thus, caproate production from xylose was proposed via the fatty acid biosynthesis pathway, not the well-known reverse β-oxidation pathway. These unexpected differences from literatures gains more understanding about caproate production from organic substrates via MCF.
Background/Aims
Tooth avulsion is the most severe traumatic tooth injury. Immediate replantation after avulsion provides the highest success rate, whereas delayed replantation with dehydration for ...>1 h always results in ankylosis, replacement resorption, and eventual tooth loss. The aim of this study was to investigate the geomorphologic change of ultrastructure on tooth root surfaces due to dehydration.
Material and Methods
Twenty‐four sound human premolars and fully developed third molars without periodontitis were selected for the experiment. Roots were separated into 6–7 pieces with an intact root surface area (3 × 3 mm2) and then divided into the following groups: fresh group, prolonged dehydration groups (air drying for 1, 2, 4, 12, or 24 h), and dehydrated teeth (air drying for 2 h) treated with acid (Tris‐HCl buffer or citric acid buffer). More than six pieces of root from each group were subjected to scanning electron microscopy (SEM) observation. Captured images were exported to ImageJ software to quantitatively analyze the areas covered with fibers. Statistical significance was determined by comparing the means of the different groups using t‐testing or one‐way analysis of variance followed by post hoc testing.
Results
Fibrous “vegetation” covering the cementum was observed on the fresh root surface by SEM. This was destroyed by dehydration (>1 h), resulting in a root surface resembling the “Gobi Desert.” The difference was statistically significant (p < .001). Root surface deteriorated by dehydration could be recovered by the re‐use of the fibers embedded in the cementum as acid demineralization of the outer layer of cementum exposed the embedded fibers to simulate the geomorphology of fresh root surface.
Conclusions
Dehydrated teeth had deteriorated geomorphology of the root surface, which could be reversed by the re‐use of the fibers embedded in the cementum using citric acid. Direct evidence from SEM gives new insights into the replantation of dehydrated avulsed teeth.
Controlled polymerization of cumulenic monomers represents a promising yet underdeveloped strategy toward well-defined alkyne polymers. Here we report a stereoelectronic effect-inspired approach ...using simple vinylidenecyclopropanes (VDCPs) as butatriene homologues in controlled radical ring-opening polymerizations. While being thermally stable, VDCPs mimic butatrienes via conjugation of the cyclopropane ring. This leads to exclusive terminal-selective propagation that affords a highly structurally regular alkyne-based backbone, featuring complete ring-opening and no backbiting regardless of polymerization conditions.
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