Self-assembling anchored film basing on two tetrazole derivatives for application to protect copper in sulfuric acid environment

Two tetrazole compounds (BTA, BTTA) self-assembled on copper substrate and their inhibition effect toward copper corrosion in 0.5 M H2SO4 was evaluated through atomic force microscopy (AFM), scanning electron microscopy (SEM), weight loss measurement along with electrochemical techniques including electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization. Results indicate that BTTA can provide superior inhibition performance to BTA, and the highest inhibition efficiency values of 96.3% (BTA) and 99.8% (BTTA) were achieved respectively at 2 mM. Both tetrazole inhibitor films follow Langmuir model concerning both physical and chemical adsorption, which can be verified by X-ray photoelectronic spectroscopy (XPS) analysis. Besides, the negative value of adsorption free energy infers a spontaneous adsorption process of these tetrazole compounds on Cu surface. Molecular dynamics (MD) simulation reveals stronger multiple anchor adsorption of BTTA molecules than BTA because of the existence of S atom. (C) 2020 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology

Study on the Influence of Characteristics of Pore Structure on Adsorption Capacity of Tectonic Coals in Guizhou Province

The occurrence and migration of coalbed methane (CBM) is inseparably associated with the pore structure within the coal seams. Three Permian Longtan Formation tectonic coal samples (QL, XL, XT) from Guizhou Province were studied to determine pore size distribution and characteristics, as well as factors that influence adsorption. Adsorption test results show that all samples generally have “ink bottle”-type pores, with large pore capacity but poor connectivity. Furthermore, the fractal dimension Df, the tortuosity “τ”, and tortuous fractal dimension DT of samples were calculated. Among the studied tectonic coals, moisture, ash, tortuosity, and volatile fraction have a positive effect on the maximum adsorption capacity (VL), whereas intact coals’ tortuosity volatile has a negative correlation with the maximum adsorption capacity (VL)

Assessment of coal and gas outburst by AHP-GT combined model

In order to predict the risk of coal and gas outburst more effectively, five factors are considered, including coal seam gas pressure, initial gas release velocity, coal firmness coefficient, coal failure type and coal seam porosity. Combined with analytic hierarchy process (AHP) and grey target decision model(GT), the risk evaluation model of coal and gas outburst was established, and verified by five coal mines in Guizhou Province. The results show that the coal firmness coefficient has the greatest impact on coal and gas outburst, and the porosity has the smallest impact on coal and gas outburst. EH Coal Mine and SF Coal Mine are small outburst danger, DLT Coal Mine and QS Coal Mine are general outburst danger, and QH Coal Mine is large outburst danger. The evaluation results are consistent with the actual situation

Study on the Influence of Characteristics of Pore Structure on Adsorption Capacity of Tectonic Coals in Guizhou Province

The occurrence and migration of coalbed methane (CBM) is inseparably associated with the pore structure within the coal seams. Three Permian Longtan Formation tectonic coal samples (QL, XL, XT) from Guizhou Province were studied to determine pore size distribution and characteristics, as well as factors that influence adsorption. Adsorption test results show that all samples generally have “ink bottle”-type pores, with large pore capacity but poor connectivity. Furthermore, the fractal dimension Df, the tortuosity “τ”, and tortuous fractal dimension DT of samples were calculated. Among the studied tectonic coals, moisture, ash, tortuosity, and volatile fraction have a positive effect on the maximum adsorption capacity (VL), whereas intact coals’ tortuosity volatile has a negative correlation with the maximum adsorption capacity (VL)

Rethinking auditory affective descriptors through zero-shot emotion recognition in speech

International audienceZero-shot speech emotion recognition (SER) endows machines with the ability of sensing unseen-emotional states in speech, compared with conventional SER endeavors on supervised cases. On addressing the zero-shot SER task, auditory affective descriptors (AADs) are typically employed to transfer affective knowledge from seen- to unseen-emotional states. However, it remains unknown which types of AADs can well describe emotional states in speech during the transfer. In this regard, we define and research on three types of AADs, namely, per-emotion semantic-embedding, per-emotion manually annotated, and per-sample manually annotated AADs, through zero-shot emotion recognition in speech. This leads to a systematic design including prototype- and annotation-based zero-shot SER modules, relying on the input from per-emotion and per-sample AADs, respectively. We then perform extensive experimental comparisons between human and machines’ AADs on the French emotional speech corpus CINEMO for positive-negative (PN) and within-negative (WN) tasks. The experimental results indicate that semantic-embedding prototypes from pretrained models can outperform manually annotated emotional dimensions in zero-shot SER. The results further demonstrate that it is possible for machines to understand and describe affective information in speech better than human beings, with the help of sufficient pretrained models

Joint Trajectory and Scheduling Optimization for The Mobile UAV Aerial Base Station: A Fairness Version

Recently, unmanned aerial vehicles (UAVs) have been widely studied in the communication area to work as aerial base stations, due to the high probability of line of sight (LoS) and high flexibility. However, few works consider fairness for the users, which is one of the most important metrics for a network. In this paper, in order to maximize network capacity with the consideration of fairness, trajectory and scheduling of the mobile UAV aerial base station are jointly optimized. Firstly, the problem of maximizing network capacity with the consideration of fairness is formulated. On account of the coupling relationship of trajectory and scheduling, an alternate iteration approach that contains ant colony algorithm and genetic algorithm are then proposed to solve this intractable problem. Finally, the simulation results demonstrate the fairness enhance of the network and the validity and effectiveness of the proposed optimization approach

Spatio-temporal characterization of earthquake sequence parameters and forecasting of strong aftershocks in Xinjiang based on the ETAS model.

In this paper, the Integrated Nested Laplace Algorithm (INLA) is applied to the Epidemic Type Aftershock Sequence (ETAS) model, and the parameters of the ETAS model are obtained for the earthquake sequences active in different regions of Xinjiang. By analyzing the characteristics of the model parameters over time, the changes in each earthquake sequence are studied in more detail. The estimated values of the ETAS model parameters are used as inputs to forecast strong aftershocks in the next period. We find that there are significant differences in the aftershock triggering capacity and aftershock attenuation capacity of earthquake sequences in different seismic regions of Xinjiang. With different cutoff dates set, we observe the characteristics of the earthquake sequence parameters changing with time after the mainshock occurs, and the model parameters of the Ms7.3 earthquake sequence in Hotan region change significantly with time within 15 days after the earthquake. Compared with the MCMC algorithm, the ETAS model fitted with the INLA algorithm can forecast the number of earthquakes in the early period after the occurrence of strong aftershocks more effectively and can forecast the sudden occurrence time of earthquakes more accurately

Research on Airport Scheduling of FGAP Multi-Objective Programming Model Based on Uncertainty Theory

Based on the current background of airport management and flight-gate scheduling in China, this paper takes Shanghai Pudong International Airport’s flight number of the rising and landing aircraft in a certain day as the research object, and it establishes an uncertain FGAP (Flight-Gate Assignment Problem) multi-objective programming model under the framework of uncertainty theory. Using genetic algorithm to solve the model, the specific flight-gate assignment scheduling plan is given. The research results show that the model in this paper can effectively alleviate the problems, such as unbalanced flight-gate allocation and excessive operating pressure of a single gate, in the conventional model, and make the allocation and scheduling more reasonable and efficient. Finally, we give the future application of uncertainty theory in finance and management, as well as the prospect of combining it with symmetry in physics