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.     

Recent advances during CH4 dry reforming for syngas production: A mini review

Given the continuing issues of environment and energy, methane dry reforming for syngas production have sparked interest among researchers, but struggled with the process immaturity owing to catalyst deactivation. This review summarizes the recent advances in the development of efficient and stable catalysts with strong resistance to coking and metal sintering, including the application of novel materials, the assessment of advanced characterizations and the compatibility to improved reaction system. One feasible option is the crystalline oxide catalysts (perovskite, pyrochlore, spinel and LDHs), which feature a fine metal dispersion and surface confinement effect via a metal exsolution strategy and exhibit superior reactivity and stability. Some new materials (h-BN, clays and MOFs) also extend the option because of their unique morphology and microstructure. It also is elaborated that progresses were achieved in advanced characterizations application, leading to success in the establishment of reaction mechanisms and attributions to the formed robust catalysts. In addition, the perspective described the upgrade of reaction system to a higher reaction efficiency and milder reaction conditions. The combination of efficient reaction systems and robust catalysts paves a way for a scaling-up application of the process.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Reusable Polyacrylonitrile-Sulfur Extractor of Heavy Metal Ions from Wastewater

Mercury, lead, and cadmium are among the most toxic and carcinogenic heavy metal ions (HMIs), posing serious threats to the sustainability of aquatic ecosystems and public health. There is an urgent need to remove these ions from water by a cheap but green process. Traditional methods have insufficient removal efficiency and reusability. Structurally robust, large surface-area adsorbents functionalized with high-selectivity affinity to HMIs are attractive filter materials. Here, an adsorbent prepared by vulcanization of polyacrylonitrile (PAN), a nitrogen-rich polymer, is reported, giving rise to PAN-S nanoparticles with cyclic π-conjugated backbone and electronic conductivity. PAN-S can be coated on ultra-robust melamine (ML) foam by simple dipping and drying. In agreement with hard/soft acid/base theory, N- and S-containing soft Lewis bases have strong binding to Hg²⁺, Pb²⁺, Cu²⁺, and Cd²⁺, with extraordinary capture efficiency and performance stability. Furthermore, the used filters, when collected and electrochemically biased in a recycling bath, can release the HMIs into the bath and electrodeposit on the counter-electrode as metallic Hg⁰, Pb⁰, Cu⁰, and Cd⁰, and the PAN-S@ML filter can then be reused at least 6 times as new. The electronically conductive PAN-S@ML filter can be fabricated cheaply and holds promise for scale-up applications.     

煤炭资源型城市转型模式研究：以徐州贾汪区为例

煤炭资源型城市为我国经济发展提供了重要的资源和能源支持,研究资源型城市转型的经验模式对调整区域经济结构、确保社会稳定和改善生态环境具有重要的实践意义。本文采用文献综述法和实证分析法,研究我国东部煤炭资源枯竭型城市转型所面临的共性难题,并以徐州贾汪区转型探索经历为例,总结城市转型的"徐州贾汪区模式",主要包括放大正向外部效应、长期坚持矿地融合、大力建设矿区社会生态系统恢复力三条路径。研究结果表明,煤炭城市转型发展的共性问题相互联系、相互影响,是一个系统性难题,必须引入系统性思维。我国东部矿区普遍人口密集,农业发达、沉陷积水是最主要的共性特征,煤炭开采产生的社会问题、经济问题、生态问题、环境问题基本相同,转型发展模式值得互鉴。     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

The role of microbial electrogenesis in regulating methane and nitrous oxide emissions from constructed wetland-microbial fuel cell

This study assesses a sustainable solution to greenhouse gases (GHGs) mitigation using constructed wetland-microbial fuel cells (CW-MFC). Roots of wetland plant Acorus Calamus L. are placed in biological anode to better enable anode microorganisms to obtain rhizosphere secretion for power improvement. Three selected cathode materials have a large difference in GHG emissions, and among them, carbon fiber felt (CFF) shows the lowest emissions of methane and nitrous oxide, which are 0.77 ± 0.04 mg/(m²·h) and 130.78 ± 13.08 μg/(m²·h), respectively. The CFF CW-MFC achieves the maximum power density of 2.99 W/m³. As the influent pH value is adjusted from acidic to alkaline, the GHGs emissions are reduced. The addition of Ni inhibits GHGs emission but decreases the electricity, the power density is reduced to 1.09 W/m³, and the methane and nitrous oxide emission fluxes decline to 0.20 ± 0.04 mg/(m²·h) and 15.49 ± 1.86 μg/(m²·h), respectively. Low C/N ratio reduces methane emission, while high C/N ratio effectively inhibits nitrous oxide emission. At the influent pH 8 and C/N = 5:1, the methane emission flux is approximately 10.60 ± 0.27 mg/(m²·h), and the nitrous oxide emission flux is only 10.90 ± 1.10 μg/(m²·h). Based on the above experimental results by controlling variable factors, it is proposed that CW-MFC offers an environment-friendly solution to regulate GHG emissions.     

A novel method of shrimp blanching by CO2 heat pump: Quality,energy, and economy analysis

To reduce the energy consumption of the shrimp blanching process and improve the economic value of the blanched product, a transcritical CO₂ heat pump blanching system (THPB system) was designed in this paper. The trends of astaxanthin were investigated at atmospheric pressure near boiling temperature, combined with the color and structural properties of shrimp samples, and the optimal blanching times of 270 s and 240 s were obtained at 90°C and 95°C, respectively. In contrast to the fuel blanching system (FB system) at 100°C, the annual standard coal consumption of the THPB system with 90°C blanching is decreased by 79%, and the annual operating cost can be saved by CNY 63,800, with a payback period of about 3.13 years.Industrial relevanceBlanching is one of the effective ways to prolong the shelf life of shrimp. However, the research on the blanching time and temperature of shrimp is not comprehensive. In addition, the traditional fuel blanching process has high energy consumption and pollution, and can no longer meet the quality requirements of the modern food processing industry. Heat pump has been shown to have better performance in food drying, but it is less used in blanching. The information presented in this study may provide other insights into food processing.     

Synergistic Effects of Polybenzimidazole and Aramide on Enhancing Flame-Retardancy and Solubility

Aromatic and functional polymers with processibility derived from biobased starting materials are prerequisite considering sustainable society. Poly(2,5-benzimidazole)s are rigid-rod polymers to show ultrahigh thermal stability such as flame retardance, while usually suffer from poor solubility. Here, poly(benzimidazole-co-amide)s are synthesized from two biobased monomers, 3,4-diaminobenzoic acid and a semirigid comonomer, 4-aminohydrocinnamic acid. The copolymers with an amide composition of 80 mol% and higher are soluble in widely used polar solvents to fabricate the films keeping high flame retardance, which is comparable with popular high-performance polymers such as aromatic polyimides, polyetheretherketone, polyphenylene sulfide, etc.