Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

Effect of H2O2 concentration on electrochemical growth and properties of vertically oriented ZnO nanorods electrodeposited from chloride solutions

In this work, ZnO nanostructures are electrodeposited on a transparent conducting glass from chloride baths. The influence of H₂O₂ concentration on the electrochemical characteristics has been studied using cyclic voltammetry (CV) and chronoamperometry (CA) techniques. From the analysis of the current transients on the basis of the Scharifker–Hills model, it is found that nucleation mechanism is progressive with a typical three-dimensional (3D) nucleation and growth process; independently with the concentration of H₂O₂. However, the nucleation rate of the ZnO changes with the increase of H₂O₂ concentration. The Mott–Schottky measurements demonstrate an n-type semiconductor character for all samples with a carrier density varying between 5.14×10¹⁸ cm⁻³ and 1.47×10¹⁸ cm⁻³. Scanning electron microscopy (SEM) observations show arrays of vertically aligned ZnO nanorods (NRs) with good homogeneity. The X-ray diffraction (XRD) patterns show that the ZnO deposited crystallises according to a hexagonal Würtzite-type structure and with the c-axis perpendicular to the electrode surface. The directional growth along (002) crystallographic plane is very important for deposits obtained at 5 and 7 mM of H₂O₂. The high optical properties of the ZnO NRs with a low density of deep defects was checked by UV–vis transmittance analyses, the band gap energy of films varies between 3.23 and 3.31 eV with transparency around 80–90%.     

Applicability and toxicity evaluation of an adsorbent based on jujube for the removal of toxic heavy metals

The removal of heavy metals from industrial wastewater is important, owing to its eco-toxicity in aqueous environment. In this study, the mechanism and efficiency of the removal of toxic heavy metals by an eco-friendly adsorbent was investigated. Various types of adsorbents made from jujube were synthesized by varying the drying temperature of gel-type beads and elution method for jujube constituents. The maximum adsorption capacity for lead and copper ions was determined using the Langmuir isotherm model, with DJB-A-S-F (freeze-dried jujube bead made from a solution of squeezed autoclaved jujube) having the highest values at 60.44 mg/g (lead) and 20.33 mg/g (copper). In addition, the characteristics of the various adsorbents were determined by the Brunauer–Emmett–Teller (BET) method, scanning electron microscopy (SEM), and energy dispersive X-ray analysis (EDX). Gas chromatography–mass spectrometry (GC–MS) was used to identify the constituents of DJB-A-S-F before and after adsorption of heavy metals (Pb- and Cu-DJB-A-S-F). Furthermore, in vitro cytotoxicity assay was performed to investigate whether the binding of heavy metals to DJB-A-S-F increases cellular toxicity. As a result, no differences in cell viability between DJB-A-S-F and the ones coupled to heavy metals were observed, indicating that the developed adsorbents are non-cytotoxic with good compatibility. Thus, DJB-A-S-F is a promising adsorbent for the removal of toxic heavy metal cations from wastewater.     

The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.     

Impact of changes in crude oil trade network patterns on national economy

Crude oil is one of the most important energy sources for the development of the national economy. The regions along the Belt and Road are rich in crude oil resources. As the Belt and Road Initiative (B&R Initiative) progresses and develops further, an increasing numbers of countries are participating, which thus increases trade cooperation and changes the pattern of crude oil trade among countries along the Belt and Road (B&R countries). This change will have various impacts on the economies of different countries. Based on the complex network and econometric theory, we study the impact of crude oil trade pattern changes of the B&R countries on each country's GDP. We obtained the following results: (1) The impact of national trade influence on GDP was significant and positive, particularly after the initiative was proposed. (2) The centrality of the country's role in the trade network had a significant and favorable impact on GDP, but it was weakened after the initiative was introduced. (3) The impact of the country's import risk in the network on GDP was negative. (4) For countries with different economic levels, changes in the role of national trade had various effects on their GDPs.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

Comparative evaluation of the mesophilic and thermophilic biohydrogen production at optimized conditions using tequila vinasses as substrate

The objective of this work was to comparatively evaluate the production of biohydrogen (bio-H₂) from tequila vinasses at optimized mesophilic and thermophilic conditions and to elucidate the main metabolic routes involved. Optimal temperatures of 35 °C and 55 °C, and pH of 5.5 maximized the bio-H₂ production rates, 25.5 ± 0.01 NmL h⁻¹ and 169.9 ± 8.9 NmL h⁻¹ in the mesophilic and thermophilic regimens, respectively. During the operation of anaerobic sequencing batch reactors, the thermophilic process allowed a volumetric bio-H₂ production rate of 519 ± 13 NmL-H₂ L⁻¹ d⁻¹ equivalent to 750 ± 19 NmL-H₂ L_vinasse⁻¹, while the mesophilic one 448 ± 23 NmL-H₂ L⁻¹ d⁻¹ and 647 ± 33 NmL-H₂ L_vinasse⁻¹, respectively. Furthermore, the gas produced under thermophilic conditions showed high hydrogen content (86.5%). Finally, formate degradation and glucose fermentation to acetic and butyric acids were the main metabolic routes involved in bio-H₂ production under thermophilic conditions, while at mesophilic conditions, the lactate and formate degradation pathways governed.     

Effect of microbial hydrogen consumption on the hydrogen permeation behaviour of AISI 4135 steel under cathodic protection

The feasibility of microbial hydrogen consumption to mitigate the hydrogen embrittlement (HE) under different cathodic potentials was evaluated using the Devanathan-Stachurski electrochemical test and the hydrogen permeation efficiency η. The hydrogen permeation efficiency η in the presence of strain GA-1 was lower than that in sterile medium. The cathodic potential inhibited the adherence of strain GA-1 to AISI 4135 steel surface, thereby reducing the hydrogen consumption of strain GA-1. The adherent GA-1 cells were capable of consuming ‘cathodic hydrogen’ and reducing the proportions of absorbed hydrogen, indicating that it is theoretically possible to control HE by hydrogen-consuming microbes.