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The turbulent energy dissipation rate is an important parameter that determines the transfer rates of mass, heat and momentum in chemical engineering industry. Especially in a multiphase reactor, the local instantaneous turbulent dissipation rate affects the breakage and coalescence of bubbles or droplets. To directly determine the local turbulent dissipation rate, fluctuating velocity gradients have to be measured down to the Kolmogorov length scale. This paper compares the advantages and disadvantages of three different methods, namely, correlation method, optical flow method and hybrid method, in the evaluation of velocity fields, which are subsequently used to calculate the turbulent dissipation rate. An instantaneous flow field of homogeneous isotropic turbulence from DNS results is used as a benchmark. The velocity field and turbulent dissipation rate field obtained by these three methods are compared to the DNS results. It is shown that the hybrid method performs better in both velocity field evaluation and local turbulent dissipation rate estimation compared to the other two methods. This is because the hybrid method combines the advantages of the correlation method in achieving a stable averaged velocity field and the optical flow method in achieving pixel-level resolution measurement of the flow field.

Characteristic amplitude modulated radiated noise signals are generated as the propeller operates underwater. Generally, passive underwater acoustic detection is accomplished by processing the radiated noise of a marine’s propeller. This study proposes a robust passive underwater acoustic detection method of a propeller by combining cyclostationary mechanism and principal component analysis (PCA). The proposed method can extract the characteristic frequency information of a propeller accurately. The effectiveness of the proposed method is verified according to simulated signals and real application cases. Both monocomponent and multicomponent modulated simulated signals are used to test the performance of the proposed method. The proposed method is then applied to the acoustic signals of propeller experiments and merchant ship propeller. Finally, the superiority of the proposed method is demonstrated by comparing the application results with the kurtogram and cyclostationary analysis method, during the extraction of the characteristic frequency of the propeller under low signal-to-noise ratio (SNR). The innovation of the proposed method not only realizes marine propeller detection from propeller acoustic signals but also has remarkable performance under low SNR.

Demodulation is a highly effective method for feature extraction of rotating machinery. Vibration/acoustic signal of rotating machinery carries substantial information that represents the mechanical equipment conditions. Therefore, the demodulation of vibration/acoustic signals is a key issue in fault diagnosis and target recognition. However, background noise enhances the difficulty of signal demodulation. This study proposes a novel demodulation method based on time-frequency analysis and principal component analysis (DPCA) to enhance demodulation performance under low signal-to-noise ratio (SNR). The periodic modulation wave signal is extracted by combining time–frequency analysis and principal component analysis (PCA). The effectiveness of the proposed method is verified by mean of simulation analysis and two real application cases. Firstly, monocomponent and multicomponent modulated simulation signals are used to test the performance of the proposed method. Secondly, the proposed method is applied to the vibration signals of the pump and acoustic signals of the propeller. Finally, the superiority of the proposed demodulation method is demonstrated by comparing the demodulation results with the kurtogram and cyclostationary analysis method under low SNR condition.

In this paper, the volume of fluid (VOF) model in conjunction with continuum surface force (CSF) model is applied to numerically investigate the single bubble formation process in the bubble columns. Meanwhile, the hybrid method (large-eddy simulation (LES) and acoustic analogy method) is used for bubble acoustic prediction. Experimental results provide a reliable validation of the numerical results. Adaptive filtering technique and time–frequency analyses are adapted for the numerical acoustic data at the gas velocity of 0.1 m/s. The spectrum and spectrogram approaches indicate that the numerical acoustic data covers two principal frequency components, in which, one is the bubble generation rate and the other is the natural frequency of volumetric bubble oscillation. By combining the studies of flow field and acoustic signals, volumetric bubble oscillation is found to be excited by an axial water jet up into the bubble, immediately following the bubble detachment. The results of this study lead to the proposition that numerical simulation method could be applied to well understanding of the physics behind the passive acoustic emission.

Idiopathic pulmonary fibrosis (IPF) induces significant morbidity and mortality, for which there are limited therapeutic options available. Here, we found that tetraethylthiuram disulphide (disulfiram, DSF), a derivative of thiuram, used in the treatment of alcohol abuse, has an inhibitory effect on bleomycin (BLM)-induced pulmonary fibrosis via the attenuation of the fibroblast-to-myofibroblast transition, migration, and proliferation of fibroblasts. Furthermore, DSF inhibited the activation of primary pulmonary fibroblasts and fibroblast cell line under transforming growth factor-β 1 (TGF-β1) challenge. Mechanistically, the anti-fibrotic effect of DSF on fibroblasts depends on the inhibition of TGF-β signalling. We further determined that DSF interrupts the interaction between SMAD3 and TGF-β receptor Ι (TBR Ι), and identified that DSF directly binds with SMAD3, in which Trp326, Thr330, and Cys332 of SMAD3 are critical binding sites for DSF. Collectively, our results reveal a powerful anti-fibrotic function of DSF in pulmonary fibrosis through the inhibition of TGF-β/SMAD signalling in pulmonary fibroblasts, indicating that DSF is a promising therapeutic candidate for IPF.

The detachment of bubbles from an underwater nozzle inevitably generates distinct acoustic signals. This work proposes numerical simulation models to investigate the effect of different nozzle wall configurations on bubble formation and acoustic characteristics. A combination of large eddy simulation (LES) model and Ffowcs Williams–Hawkings (FW-H) equation is successfully applied to predict bubble acoustic pressures. The adaptive filtering techniques of signal processing are utilized in bubble acoustic analyses. In particular, transient spectrum based on time–frequency analyses can not only precisely count the bubbling period but also effectively measure the bubble sizes. The numerical results for bubble size are in good agreement with the theoretical data (less than 10% deviation). The main results of this research show that the structure of the nozzle wall plays a guiding role in vortex motion around bubbles. The bubble size also increases with the increase in exit-lip thickness, whereas the bubbling rate decreases.

To clarify the effects of free stream turbulence and surfactant concentration, a systematic study was carried out using an advanced PIV/Shadowgraphy system. The experiments were carried out for the case of single bubbles as well as bubbles rising in chains in grid generated turbulence. The data on rise characteristics of the bubbles along with liquid flow pattern are reported for the first time for the bubbles rising in surfactant solution in presence of controlled turbulence. An oscillating grid apparatus was used to generate nearly isotropic flow with nearly zero mean flow. The in-house image processing routines were used to deduce the trajectory of the bubbles along with the parameters describing bubble shape characteristics like the eccentricity and interface wobbling. The results indicated that the modification of rising velocity was a function of the turbulent characteristics, the bubble frequency and the surfactant concentration. The maximum interactions between the continuous and dispersed phases occurred at higher bubble frequency and higher surfactant concentration. The increase in turbulence intensity was observed to increase the bubble rise velocity at higher surfactant concentration.

Travel package recommendation is a critical task in the tourism e-commerce recommender systems. Recently, an increasing number of studies proposed various travel package recommendation algorithms to improve Online Travel Agencies (OTAs) service, such as collaborative filtering-based, matrix factorization-based and neural network-based methods. Despite their value, however, the main challenges that incorporating complex descriptive information of the travel packages and capturing complicated users’ long-term preferences for fine-grained travel package recommendation are still not fully resolved. In terms of these issues, this paper propose a novel model named Neural Attentive Travel package Recommendation (NATR) for tourism e-commerce by combining users’ long-term preferences with short-term preferences. Specifically, NATR mainly contains two core modules, namely, travel package encoder and user encoder. The travel package encoder module is developed to learn a unified travel package representation by an attentive multi-view learning approach including word-level and view-level attention mechanisms. The user encoder module is designed to study long-term and short-term preference of the user by Bidirectional Long Short-Term Memory (Bi-LSTM) neural networks with package-level attention mechanism. In addition, we further adopt a gated fusion approach to coalesce these two kinds of preferences for learning high-quality the user’s representation. Extensive experiments are conducted on a real-life tourism e-commerce dataset, the results demonstrate the proposed model yields significant performance advantages over several competitive methods. Further analyses from different attention weights provide insights of attentive multi-view learning and gated fusion network, respectively.

As wealth and status rise for middle class (MC) consumers in emerging markets (EMs), they increasingly acquire gold for both consumption and investment. The authors delineate a conceptual map for gold consumption drawing insights from the context of MC in EMs. Perceived benefits of gold and disposable income directly determine the attractiveness and availability of gold for individual consumers. Cultural, institutional and economic factors account for country variations in gold consumption. Based on theoretical considerations and empirical evidence, we contend that gold consumption and disposable income have a curvilinear relationship: as EMs mature and MC consumers’ shopping baskets become more diverse and sophisticated, their gold consumption decreases and eventually stabilizes.

The effects of different conditions such as time, pH, the initial concentration of the metal ions, temperature and additional cations like Ca(II) and Mg(II) ions on desorption of Cd(II) from tourmaline at acidic conditions were investigated. The results indicated that the desorption of Cd(II) depended significantly on all the above-mentioned parameters. The desorption kinetics closely followed the pseudo-second-order model. And the desorption of Cd(II) followed the Freundlich isotherm model better than Langmuir isotherm model. The maximum desorption capacity of tourmaline for Cd(II), evaluated using a Langmuir equilibrium model, were 2.74 and 13.17 mg/g at an initial pH 4.0 under temperature 25 and 35 °C after the 1440 min equilibrium time, respectively. Thermodynamic parameters indicated that the desorption processes were viable, spontaneous and endothermic in nature. Additionally, Mg(II) and Ca(II) ions can both facilitate the efficiency of desorption, and Mg(II) ions promoted the process of desorption more better than Ca(II) ions. Thus, this study showed that tourmaline was quite an effective adsorbent for the removal of heavy metals in the acidic condition because its desorption capacity was too low to cause secondary pollution. Tourmaline may be used as a stable adsorbent for removing pollutants from environment, especially soil.

In the present study, the characteristics of a representative advanced rotational hydrodynamic cavitation reactor (ARHCR) in pilot scale were experimentally investigated. The cavitation generation mechanism was analyzed with respects to experimental flow visualization. The variation regularity of the thermal performance under a full range of operational conditions (i.e., various rotational speeds (2600 to 4200 rpm) and flow rates (1 to 2.6 m3/h)) was analyzed by establishing polynomial model and response surface. A critical flow rate of 1.2 (≤2800 rpm) or 1.4 m3/h (>2800 rpm) was found out for the present ARHCR for the first time, the thermal performance can be greatly enhanced when the critical flow rate was reached. The achieved heat generation rate and thermal efficiency can be as high as 57.21 MJ/h and 79.99%, respectively. The effects of the operational conditions on the thermal performance were evaluated and discussed. Finally, the thermal and disinfection performance of the present ARHCR was compared with that of previous devices. The ARHCR achieved a disinfection rate of 100% for Escherichia coli with an expense of $2.72/m3 at the optimal condition. The disinfection result indicated that the treatment rate of the present ARHCR was approximately 140 times higher than that of the recently reported ARHCR, with 50 times lower expenses. The findings of this work can strongly contribute to the fundamental understanding, design, and application of ARHCRs in water treatment.

The adsorption of Cd(II), Zn(II) and Ni(II) from aqueous solutions in binary and ternary component systems by tourmaline was investigated. Kinetic data were accurately fitted to pseudo-second order and internal diffusion models, which indicated that the adsorption of heavy metals occurred on the interior surface of the sorbent and internal diffusion was the controlling mechanism during heavy metal ion adsorption but was not the only rate-controlling step. Additionally, tourmaline had a very good adsorption capacity for Cd(II), Zn(II) and Ni(II) in multi-component aqueous solutions at strongly acidic pH values (in contrast to industrial wastewater pH values). This good adsorption capacity is attributed to the fact that tourmaline can automatically adjust the pH values of acidic (except pH 2.0 and 3.0), neutral or alkaline aqueous solutions to 6.0. Adsorption isotherms and separation factors showed that tourmaline displays a high selectivity toward one metal in a two-component or a three-component system with an affinity order of Cd(II) > Zn(II) > Ni(II). Thermodynamic parameters indicated that heavy metal adsorption was feasible, spontaneous, and endothermic. Therefore, tourmaline should be explored as a material for removing pollutants from the strongly acidic wastewater.