Using a deep-learning approach to infer and forecast the Indonesian Throughflow transport from sea surface height

The Indonesian Throughflow (ITF) connects the tropical Pacific and Indian Oceans and is critical to the regional and global climate systems. Previous research indicates that the Indo-Pacific pressure gradient is a major driver of the ITF, implying the possibility of forecasting ITF transport by the sea surface height (SSH) of the Indo-Pacific Ocean. Here we used a deep-learning approach with the convolutional neural network (CNN) model to reproduce ITF transport. The CNN model was trained with a random selection of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations and verified with residual components of the CMIP6 simulations. A test of the training results showed that the CNN model with SSH is able to reproduce approximately 90% of the total variance of ITF transport. The CNN model with CMIP6 was then transformed to the Simple Ocean Data Assimilation (SODA) dataset and this transformed model reproduced approximately 80% of the total variance of ITF transport in the SODA. A time series of ITF transport, verified by Monitoring the ITF (MITF) and International Nusantara Stratification and Transport (INSTANT) measurements of ITF, was then produced by the model using satellite observations from 1993 to 2021. We discovered that the CNN model can make a valid prediction with a lead time of 7 months, implying that the ITF transport can be predicted using the deep-learning approach with SSH data

Numerical Simulation on the Gas Explosion Propagation Related to Roadway

AbstractBased on the combustion, explosions and air dynamics and related theory etc, this paper describes the mathematical model of gas explosion in detail, combined with the gas explosion transmission mechanism, make a research on two wave-three area structure of gas explosion and the energy change rule of the array face of precursor wave and the array face of flame wave, with the fluid dynamics analysis Fluent software, this paper makes a numerical simulation and analysis on the overpressure transmission rule when gas explosion takes place in different types roadways. The results of the study show that: Fluent software can be used to accurately simulate gas explosion condition, when explosion wave spreads in the roadway turns, the bigger of the overpressure value in corner, the stronger of the destructive power; when tunnel has bifurcation, the overpressure will release in bifurcation, but explosions wave with flame wave will produce more powerful destruction effect. The research results can be used as a certain reference for how to prevent and control the gas explosion, and how to reduce the power of the gas explosion etc

Iterative Reconstruction Based on Latent Diffusion Model for Sparse Data Reconstruction

Reconstructing Computed tomography (CT) images from sparse measurement is a well-known ill-posed inverse problem. The Iterative Reconstruction (IR) algorithm is a solution to inverse problems. However, recent IR methods require paired data and the approximation of the inverse projection matrix. To address those problems, we present Latent Diffusion Iterative Reconstruction (LDIR), a pioneering zero-shot method that extends IR with a pre-trained Latent Diffusion Model (LDM) as a accurate and efficient data prior. By approximating the prior distribution with an unconditional latent diffusion model, LDIR is the first method to successfully integrate iterative reconstruction and LDM in an unsupervised manner. LDIR makes the reconstruction of high-resolution images more efficient. Moreover, LDIR utilizes the gradient from the data-fidelity term to guide the sampling process of the LDM, therefore, LDIR does not need the approximation of the inverse projection matrix and can solve various CT reconstruction tasks with a single model. Additionally, for enhancing the sample consistency of the reconstruction, we introduce a novel approach that uses historical gradient information to guide the gradient. Our experiments on extremely sparse CT data reconstruction tasks show that LDIR outperforms other state-of-the-art unsupervised and even exceeds supervised methods, establishing it as a leading technique in terms of both quantity and quality. Furthermore, LDIR also achieves competitive performance on nature image tasks. It is worth noting that LDIR also exhibits significantly faster execution times and lower memory consumption compared to methods with similar network settings. Our code will be publicly available

Effects of ageing on the surface characteristics and Cu(ii) adsorption behaviour of rice husk biochar in soil

The properties of rice husk biochar during the ageing process in soil and the resulting impacts on sorption capacity with respect to Cu(ii) were assessed. Rice husk-derived biochar was placed in fabric bags and buried in a plastic incubator filled with soil for 0–240 d. The aged biochar was then characterised and its sorption capacity compared with control (unaged) biochar in batch sorption experiments. The structural composition and morphology of the biochar before and after ageing were analysed based on element composition, scanning electron microscopy (SEM) coupled with energy X-ray dispersive spectroscopy (EDS), diffuse reflectance infrared Fourier transform infrared spectroscopy (DRIFTS), and X-ray photoelectron spectroscopy (XPS). The concentration of O, atomic O/C ratios, and carboxyl and hydroxyl functional groups increased at the surface of the biochar during ageing, which together indicated oxidation. Within the biochar particles, O/C ratios progressively increased towards their outer surfaces. Furthermore, ageing for more than 120 d facilitated Cu(ii) sorption as oxygen-containing groups were able to develop. The maximum adsorption capacity (qm) of biochar increased by 1.24 ∼ 1.32 times after ageing in the soil for 240 d. It is suggested that biochar surface properties were gradually altered during environmental exposure and the aged rice husk biochar showed increased performance in Cu(ii) adsorption. However, the performance of aged biochar as a soil remediator or conditioner will be affected by the ageing process and interactions among different soil components. As such, further research is required to evaluate these complex effects

The impact of predators of mosquito larvae on Wolbachia spreading dynamics

Dengue fever creates more than 390 million cases worldwide yearly. The most effective way to deal with this mosquito-borne disease is to control the vectors. In this work we consider two weapons, the endosymbiotic bacteria Wolbachia and predators of mosquito larvae, for combating the disease. As Wolbachia-infected mosquitoes are less able to transmit dengue virus, releasing infected mosquitoes to invade wild mosquito populations helps to reduce dengue transmission. Besides this measure, the introduction of predators of mosquito larvae can control mosquito population. To evaluate the impact of the predators on Wolbachia spreading dynamics, we develop a stage-structured five-dimensional model, which links the predator-prey dynamics with the Wolbachia spreading. By comparatively analysing the dynamics of the models without and with predators, we observe that the introduction of the predators augments the number of coexistence equilibria and impedes Wolbachia spreading. Some numerical simulations are presented to support and expand our theoretical results

Experimental study on the transporting and crushing effect of gas on coal powder during the develop stage of coal and gas outburst in roadway

Abstract In recent years, coal and gas outburst disasters are still occurring and difficult to prevent, seriously endangering the safety of coal mine production. It is well known that the transporting and crushing of outburst coal is the main pathway of energy dissipation during the coal and gas outburst process. However, a consensus regarding how much gas involves in outburst and affects energy dissipation is still lacking. Quantitative study on the gas effect on migration and fragmentation characteristics of outburst coal in restricted roadway space can improve the energy model and guide the prevention and control of gas outburst. In this paper, an improved visual coal and gas outburst dynamic effect simulation experiment system was used to conduct outburst simulation experiments at different gas pressure conditions. The results showed that the movement of outburst coal in the roadway has experienced various flow patterns. In the initial stage of the outburst, under low gas pressure condition, the motion of the outburst coal was dominated by stratified flow. However, as the gas pressure increases, the initial acceleration increases, and the outburst coal mainly move forward rapidly in the form of plug flow. The average velocity at 0.3, 0.5, and 0.8 MPa gas pressure condition were 6.75, 22.22 and 35.81 m/s, respectively. Gas also has a crushing effect on outburst coal. With increasing gas pressure, the number of coal powder particles of the same mass increased significantly, and the range of the particle size distribution of the particles decreaed, and the median particle size decreased. As the gas pressure increases, the outburst intensity gradually increases, and the total energy involved in the outburst work also increases. However, the energy dissipation pathways are different. At 0.3 MPa, the energy dissipation is dominated by crushing energy, which is about six times the ejection energy. As the gas pressure increased to 0.8 MPa, the proportion of the ejection energy gradually increases to about twice that of the crushing energy. Under the experimental conditions, 2.71–13.43% of the adsorbed gas involves in the outburst (AGIO) through rapid desorption, and the proportion increases with increasing gas pressure. This paper improves the energy model of coal and gas outburst, which is applicable to risk assessment and prevention of outburst disasters

Periodic Orbits of a Mosquito Suppression Model Based on Sterile Mosquitoes

In this work, we investigate the existence and stability of periodic orbits of a mosquito population suppression model based on sterile mosquitoes. The model switches between two sub-equations as the actual number of sterile mosquitoes in the wild is assumed to take two constant values alternately. Employing the Poincaré map method, we show that the model has at most two T-periodic solutions when the release amount is not sufficient to eradicate the wild mosquitoes, and then obtain some sufficient conditions for the model to admit a unique or exactly two T-periodic solutions. In particular, we observe that the model displays bistability when it admits exactly two T-periodic solutions: the origin and the larger periodic solution are asymptotically stable, and the smaller periodic solution is unstable. Finally, we give two numerical examples to support our lemmas and theorems

A New Method for Measuring the Rotational Angles of a Precision Spherical Joint Using Eddy Current Sensors

Precision spherical joint is a spherical motion pair that can realize rotation with three degrees of freedom. This joint is widely used in robots, parallel mechanisms, and high-end medical equipment, as well as in aerospace and other fields. However, the rotation orientation and angle cannot be determined when the joint is in passive motion. The real-time determination of the rotation orientation and angle is crucial to the improvement of the motion control accuracy of the equipment where the joint is installed in. In this study, a new measurement method that utilizes eddy current sensors is proposed to identify the special features of the joint ball and realize angle measurements indirectly. The basic idea is to manufacture the specific shape features on the ball without affecting its movement accuracy and mechanical performance. An eddy current sensor array is distributed in the ball socket. When the ball head rotates, the features on the ball opposite to the sensor, as well as the output signal of every eddy current sensor, change. The measurement model that establishes the relationship between the output signal of the eddy current sensor array and the rotation direction and angle of the ball head is constructed by learning and training an artificial neural network. A prototype is developed using the proposed scheme, and the model simulation and feasibility experiment are subsequently performed. Results show that the root mean square angular error of a single axis within a range of ±14° is approximately 20 min, which suggests the feasibility of the proposed method

Experimental Investigation on Influence Factors of Acoustic Emission Activity in Coal Failure Process

Stress-dominated coal and gas outburst disaster has become one of the main safety problems in deep coal mines. Acoustic emission (AE) or microseismic technology has been viewed as a promising method that can effectively reflect the stress and stability status of rock mass. The AE activity precursor of coal failure is the theoretical basis of this technology. In this study, AE experiments in failure process of coal specimens with different properties and under different stress conditions were performed in laboratory to explore influence factors and their effect of AE activity, and AE activity pattern classification was proposed based on the failure type of coal. The results indicate that the AE activity of different coals under loading are associated with the failure phase, and the evolution pattern of AE activity depends on the failure type of stressed coal. Both the mechanical property and the external stress condition have an important influential effect on the failure type and AE activity pattern in coal failure process. The internal mechanical property decides the inherent tendency of stressed coals to perform brittle or ductile behavior, and the responded AE activity pattern. The contrast of fissure distribution of specimens suggested that fissure structure in coal significantly affects the fracturing mode of coal in uniaxial compression and the AE activity pattern. The external stress condition has a transition effect on AE event energy distribution and AE activity pattern. Under the effect of external stress condition, the energy distribution of AE events was transforming between relative disperse and relative concentration, the failure type and AE activity evolution pattern of coal could appear the brittle-ductile transition. Based on the view of failure type, the pattern of AE activity of coal failure can be classified into three types, i.e., ductile, brittle, and semi-brittle pattern. It is suggested that the high-level AE activity can be viewed as the precursor of brittle instability of coal, and relative quiet phenomenon of AE activity as the precursor of ductile or semi-brittle instability. The research achievement can provide a theoretical base for the prewarning criteria establishment of coal and rock dynamic disasters at depth and improve the insight of AE activity in the coal failure process

Enhancement of the Bioavailability and Anti-Inflammatory Activity of Glycyrrhetinic Acid via Novel Soluplus®—A Glycyrrhetinic Acid Solid Dispersion

Glycyrrhetinic acid (GA) is an anti-inflammatory drug with potential for development. However, the poor solubility of GA in water leads to extremely low bioavailability, which limits its clinical applications. Solid dispersions have become some of the most effective strategies for improving the solubility of poorly soluble drugs. Soluplus®, a non-cytotoxic amphiphilic solubilizer, significantly improves the solubility of BCS II drugs and improves the bioavailability of insoluble drugs. l-arginine (L-Arg) can be used as a small molecular weight excipient to assist in improving the solubility of insoluble drugs. In this study, we developed a new formulation for oral administration by reacting GA and L-Arg to form salts by co-solvent evaporation and then adding the polymer-solvent Soluplus® with an amphiphilic chemical structure to prepare a solid dispersion GA-SD. The chemical and physical properties of GA-SD were characterized by DLS, TEM, XRD, FT-IR and TG. The anti-inflammatory activity of GA-SD was verified by LPS stimulation of RAW 267.5 cells simulating a cellular inflammation model, TPA-induced ear edema model in mice, and ethanol-induced gastric ulcer model. The results showed that the amide bond and salt formation of GA-SD greatly improved GA solubility. GA-SD effectively improved the anti-inflammatory effect of free GA in vivo and in vitro, and GA-SD had no significant effect on liver and kidney function, no significant tissue toxicity, and good biosafety. In conclusion, GA-SD with L-Arg and Soluplus® is an effective method to improve the solubility and bioavailability of GA. As a safe and effective solid dispersion, it is a promising anti-inflammatory oral formulation and provides some references for other oral drug candidates with low bioavailability