•MPCHI envelope performances well in nonstationary part of a signal.•CSI envelope is more suitable in the smooth part of a signal.•A CIE LMD method based on MPCHI and CSI was proposed.•The CIE LMD ...performances better for the diagnosis of reciprocating compressor bearing fault.
Local mean decomposition (LMD) is a self-adaptive analysis method which can decompose a signal into a set of product function (PF) components, and the construction of envelope function plays an important role in the accuracy of its PF components. According to the local nonstationary characteristics of vibration signals, a compound interpolation envelope (CIE) LMD was proposed through a novel envelope construction method. By defining an nonstationary coefficient to evaluate the local nonstationary characteristics of vibration signals, an compound envelope construction method which use Monotonic Piecewise Cubic Hermite Interpolation (MPCHI) for nonstationary part and Cubic spline interpolation (CSI) for smooth part was proposed, and an CIE LMD algorithm was give based on the novel envelope construction method. A numerical example simulation was conducted to verify the performance of CIE LMD, results indicated that CIE LMD outperforms three other methods. The CIE LMD was employed to diagnose the oversized bearing clearance fault in reciprocating compressor, and the envelope frequency spectrum of PF component gives a more significant peak of fault frequency than that of original signal, which further indicates that this proposed method is competent for the diagnosis of reciprocating compressor oversized bearing clearance fault.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Polyamide reverse osmosis membranes incorporating carboxy-functionalized multi-walled carbon nanotubes (MWNTs) were prepared by interfacial polymerization of metaphenylene diamine and trimesoyl ...chloride. The pristine MWNTs were pre-treated with mixed acids before being modified with diisobutyryl peroxide to enhance their dispersity and chemical activity. The prepared nanocomposite membranes had a 100–300nm skin layer and the modified MWNTs were embedded within the skin layer, which was confirmed by scanning electron microscopy and transmission electron microscopy. The surface of the nanocomposite membrane was shown to be more negatively charged than bare polyamide membrane. It was shown that with an increase in the carbon nanotube loading in the membrane, the membrane morphology changed distinctly, leading to a significantly improved flux without sacrificing the solute rejection. Meanwhile, the nanocomposite membranes showed better antifouling and antioxidative properties than MWNT-free polyamide membranes, suggesting that the incorporation of modified MWNTs in membranes is effective for improving the membrane performance.
Modified multi-walled carbon nanotubes have been incorporated into polyamide reverse osmosis membrane to improve the separation performance. Display omitted
•Appropriate modification improves the compatibility between MWNTs and polyamide.•Flux of polyamide/MWNT membrane increased without largely sacrificing the rejection.•Antifouling properties of membranes were enhanced by incorporating MWNTs.•Antioxidative properties of membranes were also improved by incorporating MWNTs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this paper, isocyanate-treated graphene oxide (iGO), which can be well dispersed in organic solvent, was prepared in a simple manner and showed excellent compatibility with polysulfone (PSF). ...iGO-PSF ultrafiltration membranes were prepared by the classical phase inversion method. The separation performance and the antifouling property of the prepared membranes were investigated in detail. The antifouling property of the prepared membranes was found to be greatly enhanced by the addition of iGO, and we attributed the enhanced antifouling property to the improved hydrophilicity, the more negative zeta potential and the improved smoothness of the membrane surface.
Polyamide (PA) membrane-based reverse-osmosis (RO) serves as one of the most important techniques for water desalination and purification. Fundamental understanding of PA RO membranes at the ...atomistic level is critical to enhance their separation capabilities, leading to significant societal and commercial benefits. In this paper, a fully atomistic molecular dynamics simulation was performed to investigate PA membrane. Our simulated cross-linked membrane exhibits structural properties similar to those reported in experiments. Our results also reveal the presence of small local two-layer slip structures in PA membrane with 70% cross-linking, primarily due to short-range anisotropic interactions among aromatic benzene rings. Inside the inhomogeneous polymeric structure of the membrane, water molecules show heterogeneous diffusivities and converge adjacent to polar groups. Increased diffusion of water molecules is observed through the less cross-linked pathways. The existence of the fast pathways for water permeation has no effect on membrane’s salt rejections.
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IJS, KILJ, NUK, PNG, UL, UM
•The effects of flash drought on productivity and the relationship among influencing factors are revealed.•The sensitivity and anomaly of grassland productivity response to flash drought are ...discussed.•The time stage and type of flash drought had the greatest impact on grassland productivity.•The drought tolerance of grassland and the grassland type with the greatest risk of flash drought are determined.
Flash droughts have attracted worldwide attention because of their rapid outbreak and extensive influence. However, studies regarding the characteristics and effects of flash droughts in grassland ecosystems are insufficient. In this study, the frequency and intensity characteristics of flash droughts in the Xilinguole Grassland in China were studied. The response characteristics of the productivity of different types of grassland to flash droughts and the relationship between these characteristics and the drought tolerance of grassland were revealed. The results show that (1) flash droughts had the greatest impact on grassland net primary productivity (NPP) and rain use efficiency (RUE) in summer and spring, respectively, with a level of intensity above that of moderate drought. Strong evapotranspiration flash droughts (SEFD) require more attention from decision-makers than heat wave flash droughts (HWFD). A higher frequency and intensity of flash droughts had a greater impact on vegetation. (2) Flash droughts caused moderate negative anomalies in the NPP and RUE indices in more than 90 % of the grasslands. The longest lag time of the NPP response to flash droughts was 2 months, and NPP anomalies were affected by flash droughts for nearly 2 months. RUE was more sensitive to flash droughts than NPP. RUE responded to flash droughts within 10 days, with a decrease of more than 80 % in magnitude, which was 30 % higher than that of the NPP, and the duration of the anomaly was half that of the NPP. (3) Grasslands with a high sensitivity to flash droughts had shorter response durations, fewer abnormalities, better recovery abilities and better drought tolerance. The drought tolerance of grasslands did not increase in association with large NPP and RUE values. Desert grasslands were the most drought tolerant, while meadow grasslands were the least drought tolerant, with the highest risk of flash droughts. This study provides theoretical support for improving the ability of an ecosystem to cope with flash drought risk and scientific grassland management.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To achieve real‐time and effective prediction of industrial site risks, this paper proposes an industrial risk prediction framework for multimodal data based on edge computing. First, the authors ...gather and annotate industrial risk multimodal data that consist of text descriptions, images, and videos. Then, the authors transfer the data to the edge server, and apply deep learning models such as Bidirectional Encoder Representations from Transformers (BERT), ResNet etc., to extract features and learn representations for text, image, and video data respectively. The authors input the fused feature data into an enhanced long short term memory (LSTM) model and train it on the dataset. Finally, the authors perform the risk prediction based on the collected multimodal data. The experimental results demonstrate that the method proposed in this paper exhibits superior performance, achieving a 1.4% enhancement in predictive accuracy.
To tackle industrial risks arising from system complexity, this paper develops a deep learning framework that fuses multimodal factory data for predictive analytics. Extensive evaluations demonstrate superior risk prediction performance over traditional models, proving the efficacy of data‐driven intelligence for safety enhancement in future smart factories.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Signal transducer and activator of transcription 3 (STAT3) is an oncogene, which upregulates in approximately 70% of human cancers. Autophagy is an evolutionarily conserved process which maintains ...cellular homeostasis and eliminates damaged cellular components. Moreover, the STAT3 signaling pathway, which may be triggered by cancer cells, has been implicated in the autophagic process.
In this study, we found that the anthelmintic flubendazole exerts potent antitumor activity in three human colorectal cancer (CRC) cell lines and in the nude mouse model. The inhibition of cell proliferation in vitro by flubendazole was evaluated using a clonogenic assay and the MTT assay. Western blot analysis, flow cytometry analysis, siRNA growth experiment and cytoplasmic and nuclear protein extraction were used to investigate the mechanisms of inhibiting STAT3 signaling and activation of autophagy induced by flubendazole. Additionally, the expression of STAT3 and mTOR was analyzed in paired colorectal cancer and normal tissues collected from clinical patients.
Flubendazole blocked the IL6-induced nuclear translocation of STAT3, which led to inhibition of the transcription of STAT3 target genes, such as MCL1, VEGF and BIRC5. In addition, flubendazole also reduced the expression of P-mTOR, P62, BCL2, and upregulated Beclin1 and LC3-I/II, which are major autophagy-related genes. These processes induced potent cell apoptosis in CRC cells. In addition, flubendazole displayed a synergistic effect with the chemotherapeutic agent 5-fluorouracil in the treatment of CRC.
Taken together, these results indicate that flubendazole exerts antitumor activities by blocking STAT3 signaling and inevitably affects the autophagy pathway. Flubendazole maybe a novel anticancer drug and offers a distinctive therapeutic strategy in neoadjuvant chemotherapy of CRC.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Underdetermined blind source separation (UBSS) has garnered significant attention in recent years due to its ability to separate source signals without prior knowledge, even when sensors are limited. ...To accurately estimate the mixed matrix, various clustering algorithms are typically employed to enhance the sparsity of the mixed matrix. Traditional clustering methods require prior knowledge of the number of direct signal sources, while modern artificial intelligence optimization algorithms are sensitive to outliers, which can affect accuracy. To address these challenges, we propose a novel approach called the Genetic Simulated Annealing Optimization (GASA) method with Adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering as initialization, named the CYYM method. This approach incorporates two key components: an Adaptive DBSCAN to discard noise points and identify the number of source signals and GASA optimization for automatic cluster center determination. GASA combines the global spatial search capabilities of a genetic algorithm (GA) with the local search abilities of a simulated annealing algorithm (SA). Signal simulations and experimental analysis of compressor fault signals demonstrate that the CYYM method can accurately calculate the mixing matrix, facilitating successful source signal recovery. Subsequently, we analyze the recovered signals using the Refined Composite Multiscale Fuzzy Entropy (RCMFE), which, in turn, enables effective compressor connecting rod fault diagnosis. This research provides a promising approach for underdetermined source separation and offers practical applications in fault diagnosis and other fields.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Ovarian age assessment is an important indicator to evaluate the ovarian reserve function and reproductive potential of women. At present, the application of ovarian age prediction model in China ...needs further improvement and optimization to make it more suitable for the actual situation of women in China. In this study, we collected subjects and their data in three ways: firstly, we collected clinical data from a number of women go to local hospital, including healthy women and women with DOR or PCOS; secondly, we obtained data by recruited healthy women through CRO companies for a fee; thirdly, we collected data from a number of healthy women using WeChat applet. Using the data collected by CRO company and WeChat applet, we applied the generalized linear model to optimize the ovarian age prediction model. The optimized formula is: OvAge = exp (3.5254-0.0001*PRL-0.0231*AMH), where P = 0.8195 for PRL and P = 0.0003 for AMH. Applying the formula to the hospital population data set for testing, it showed that the predicted ovarian age in the healthy women was comparable to their actual age, with a root mean squared error (RMSE) = 5.6324. The prediction accuracy was high. These data suggest that our modification of the ovarian age prediction model is feasible and that the formula is currently a more appropriate model for ovarian age assessment in healthy Chinese women. This study explored a new way to collect clinical data, namely, an online ovarian age calculator developed based on a WeChat applet, which can collect data from a large number of subjects in a short period of time and is more economical, efficient, and convenient. In addition, this study introduced real data to optimize the model, which could provide insights for model localization and improvement.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A demodulation technique based on improved local mean decomposition (LMD) is investigated in this paper. LMD heavily depends on the local mean and envelope estimate functions in the sifting process. ...It is well known that the moving average (MA) approach exists in many problems (such as step size selection, inaccurate results and time-consuming). Aiming at the drawbacks of MA in the smoothing process, this paper proposes a new self-adaptive analysis algorithm called optimized LMD (OLMD). In OLMD method, an alternative approach called rational Hermite interpolation is proposed to calculate local mean and envelope estimate functions using the upper and lower envelopes of a signal. Meanwhile, a reasonable bandwidth criterion is introduced to select the optimum product function (OPF) from pre-OPFs derived from rational Hermite interpolation with different shape controlling parameters in each rank. Subsequently, the orthogonality criterion (OC) is taken as the product function (PF) iterative stopping condition. The effectiveness of OLMD method is validated by the numerical simulations and applications to gearbox and roller bearing fault diagnosis. Results demonstrate that OLMD method has better fault identification capacity, which is effective in rotating machinery fault diagnosis.
•A novel time–frequency analysis method called OLMD is presented in this paper.•OLMD can weaken the mode mixing problem in traditional LMD.•The simulation and experimental results validate the reliability and feasibility of the proposed methodology.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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