Increased Functional Brain Network Efficiency During Audiovisual Temporal Asynchrony Integration Task in Aging

Audiovisual integration significantly changes over the lifespan, but age-related functional connectivity in audiovisual temporal asynchrony integration tasks remains underexplored. In the present study, electroencephalograms (EEGs) of 27 young adults (22–25 years) and 25 old adults (61–76 years) were recorded during an audiovisual temporal asynchrony integration task with seven conditions [auditory (A), visual (V), AV, A50V, A100V, V50A and V100A]. We calculated the phase lag index (PLI)-weighted connectivity networks modulated by the audiovisual tasks and found that the PLI connections showed obvious dynamic changes after stimulus onset. In the theta (4–7 Hz) and alpha (8–13 Hz) bands, the AV and V50A conditions induced stronger functional connections and higher global and local efficiencies, reflecting a stronger audiovisual integration effect, which was attributed to the auditory information arriving at the primary auditory cortex earlier than the visual information reaching the primary visual cortex. Importantly, the functional connectivity and network efficiencies of old adults revealed higher global and local efficiencies and higher degree in both the theta and alpha bands. These larger network efficiencies indicated that old adults might experience more difficulties in attention and cognitive control during the audiovisual integration task with temporal asynchrony than young adults. There were significant associations between network efficiencies and peak time of integration only in young adults. We propose that an audiovisual task with multiple conditions might arouse the appropriate attention in young adults but would lead to a ceiling effect in old adults. Our findings provide new insights into the network topography of old adults during audiovisual integration and highlight higher functional connectivity and network efficiencies due to greater cognitive demand

A Convolutional Neural Network Combining Discriminative Dictionary Learning and Sequence Tracking for Left Ventricular Detection

Cardiac MRI left ventricular (LV) detection is frequently employed to assist cardiac registration or segmentation in computer-aided diagnosis of heart diseases. Focusing on the challenging problems in LV detection, such as the large span and varying size of LV areas in MRI, as well as the heterogeneous myocardial and blood pool parts in LV areas, a convolutional neural network (CNN) detection method combining discriminative dictionary learning and sequence tracking is proposed in this paper. To efficiently represent the different sub-objects in LV area, the method deploys discriminant dictionary to classify the superpixel oversegmented regions, then the target LV region is constructed by label merging and multi-scale adaptive anchors are generated in the target region for handling the varying sizes. Combining with non-differential anchors in regional proposal network, the left ventricle object is localized by the CNN based regression and classification strategy. In order to solve the problem of slow classification speed of discriminative dictionary, a fast generation module of left ventricular scale adaptive anchors based on sequence tracking is also proposed on the same individual. The method and its variants were tested on the heart atlas data set. Experimental results verified the effectiveness of the proposed method and according to some evaluation indicators, it obtained 92.95% in AP50 metric and it was the most competitive result compared to typical related methods. The combination of discriminative dictionary learning and scale adaptive anchor improves adaptability of the proposed algorithm to the varying left ventricular areas. This study would be beneficial in some cardiac image processing such as region-of-interest cropping and left ventricle volume measurement

Temperature Variation Characteristics and Model Optimization of Flocculation Sedimentation of Overflow Ultra-Fine Iron Tailings

In order to study the effect of temperature on the settling characteristics of overflow ultra-fine iron tailings, the settling velocity of overflow ultra-fine iron tailings at eight different temperatures at 10–80 °C was experimentally studied. The results show that, with the increase in slurry temperature, the flocculation settling velocity of overflow ultra-fine iron tailings increases first and then decreases. That is, when the temperature is less than 60 °C, the settling velocity of flocs increases with the increase in temperature. When the temperature is 60 °C, the settling velocity reaches the maximum 5.66 mm/s. When the temperature is more than 60 °C, the settling velocity of tailings flocs gradually decreases. In addition, with the increase in the test temperature, when the temperature is less than 60 °C, the particle size, fractal dimension, and density of tailings flocculant gradually increase, the gap of flocculant structure gradually decreases, and the floc structure becomes denser. When the temperature is higher than 60 °C, the particle size, fractal dimension, and density of flocs gradually decrease, and the gap between flocs is larger than that at 60 °C. On this basis, the temperature model of overflow ultra-fine iron tailings is established according to the analysis of particle settling process, and the settling model was optimized according to different settling areas. The mean absolute error between the optimized settling velocity and the actual velocity is 0.007, the root mean square error is 0.002, and the error is small. The theoretical calculation results are in good agreement with the experimental data, and the optimized flocculation settling model has an important role in promoting the theoretical study of the flocculation settling of such ultra-fine iron mineral particles, and can be used to guide the sedimentation and separation system to achieve good sedimentation treatment effect under the best working conditions as required

Stability assessment for underground excavations and key construction techniques

This book examines how the state of underground structures can be determined with the assistance of force, deformation and energy. It then analyzes mechanized shield methods, the New Austrian tunneling method (NATM) and conventional methods from this new perspective. The book gathers a wealth of cases reflecting the experiences of practitioners and administrators alike. Based on statistical and engineering studies of these cases, as well as lab and field experiments, it develops a stability assessment approach incorporating a stable equilibrium, which enables engineers to keep the structure and surrounding rocks safe as long as the stable equilibrium and deformation compliance are maintained. The book illustrates the implementation of the method in various tunneling contexts, including soil-rock mixed strata, tunneling beneath operating roads, underwater tunnels, and tunnel pit excavation. It offers a valuable guide for researchers, designers and engineers, especially those who are seeking to understand the underlying principles of underground excavation

Molecular Dynamics Study on the Leaching of Zinc-Bearing Dust Sludge by Choline Chloride-Malonic Acid

Molecular dynamics of the interaction between four metal oxides (ZnO, Fe2O3, Al2O3, and CaO) present in zinc-bearing dust sludge and choline chloride (ChCl)-malonic acid (MA)(1:2) was studied in this work using Materials Studio software. The interaction mechanism was revealed by analyzing the interaction energy and radial distribution function from the perspective of quantum mechanics, and the simulation results were verified by single factor leaching experiments. The calculation results show that the complete cleavage surface of the four metal oxides is the (001) surface, and ChCl-2MA forms a stable structure with multiple intermolecular hydrogen bonds centered on the chlorine atom. The dynamic simulation of the interaction model shows that strength of interaction between ChCl-2MA and the four metal oxides follows the order: ZnO > Fe2O3 > Al2O3 > CaO. ChCl-2MA mainly interacts with ZnO by chemical adsorption, while ChCl-2MA mainly interacts with Fe2O3, Al2O3, and CaO by physical adsorption. The radial distribution function shows that Cl in ChCl-2MA and C=O in MA form chemical bonds with Zn in ZnO, and the choline cation (Ch+) forms C-H···O with ZnO. Among these bonds, the Cl-Zn bond energy is stronger. During the interaction between ChCl-2MA and Fe2O3 and Al2O3, O-H···O and C-H···O are formed and interact with CaO by van der Waals force. Single factor leaching experiments show that, under the same leaching conditions, the leaching rate of ZnO by ChCl-2MA is greater than 90%, while the leaching rate of Fe2O3, Al2O3, and CaO is about 10%. These results indicate good selectivity of ChCl-2MA for ZnO in the zinc-bearing dust sludge. The above conclusions have important theoretical significance and provide an in-depth understanding of the leaching mechanisms of zinc-bearing dust sludge in deep eutectic solvents

Study on the floc-bubble adhesion behavior of hematite in static flow field

To investigate the adhesion of hematite flocs to gas bubbles in floc floatation, this paper develops an observation system for floc-bubble collision and adhesion with two charge-coupled device (CCD) cameras. The sizes of flocs and bubble were 45.36μm and 0.90mm, respectively, and the distance between a floc and the bubble center (sedimentation distance) was set to 0.25cm. Three surfactants, namely, sodium oleate, lauryl amine and sodium dodecyl sulfate (SDS), were selected for our research. Several experiments were conducted to disclose how surfactant concentration and pH affect the surface adhesion between hematite flocs and bubbles. Then, the adhesion mechanism was discussed in details based on the experimental results. The results show that the highest adhesion probability was achieved for the said floc and bubble at the lauryl amine concentration of 8mg/L, the sedimentation distance of 0.25cm and the pH of 9. After touching the bubble, the hermamite floc slid on the bubble surface, forming a stable three-phase interface after 67ms. Then, the radial position of the floc no longer changed, despite the floc motion on the bubble surface. According to the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and the potential energy of the van der Waals force, there was a repulsive force between the floc and the bubble in the absence of surfactant and an attractive force in the presence of the surfactant of lauryl amine. In addition, a thin solvation shell is conducive to the adhesion between the floc and the bubble

Simulation and Validation of Discrete Element Parameter Calibration for Fine-Grained Iron Tailings

In order to improve the calculation efficiency of a discrete element EDEM (Discrete Element Method) numerical simulation software for micron particles, the particle model is linearly enlarged. At the same time, the parameters of the amplified particles were calibrated according to the Hertz-Mindlin with JKR (Johnson-Kendall-Roberts) contact model to make the amplified particles have the same particle flow characteristics as the actual particles. Actual tests were utilized to gather the angle of repose of the microfine iron tailings, which was then used as a reference value for response surface studies based on the JKR contact model from six factors connected to the fine iron tailings particles. The Plackett-Burman test was used to identify three parameters that had a significant effect on the rest angle: static friction factor; rolling friction factor; and JKR surface energy. The Box-Behnken experiment was used to establish a second-order regression model of the rest angle, and the significant parameters and the optimized parameters were: surface energy JKR coefficient 0.459; particle-particle static friction coefficient 0.393; and particle-particle dynamic friction coefficient 0.393, with a dynamic friction coefficient between particles of 0.106. By entering the parameters into the discrete element program, the angle of repose generated from the simulations was compared with the real test values, and the error was 1.56%. The contact parameters obtained can be used in the discrete element simulation of the amplified particles of fine-grained iron tailings, providing an EDEM model reference for the numerical simulation of fine-grained iron tailings particles. There is no discernible difference between the actual and simulated angles

Self-Centering Precast Unit as Energy Dissipation Members in Precast Segmental Bridge Columns

This research aims to present a new generation of seismic-resisting systems designed for precast reinforced concrete (RC) bridge piers in modern sustainable cities to withstand moderate to high seismic activity. The proposed system consists of two self-centering (SC) systems operating in parallel to bring together all features of the required resiliency during a seismic action. The first/main system is a hollow core precast segmental bridge column, and the second is composed of an SC precast unit and energy dissipation (ED) steel reinforcements positioned in the main pier segment’s hollow core. To study the performance of the proposed system, a finite element model was first developed to capture the behavior of experimentally tested precast bridge columns. After validation, the created model was systematically studied to investigate the performance of the entire proposed system under cyclic loading. The effects of three parameters related to the ED system were investigated, including the reinforcement ratio, the unbonded length of ED bars, and the SC post-tensioned force ratio. Furthermore, the impact of FRP wrapping on the lower part of the core column of the ED system was also investigated. An analytical model predicting the characteristic points of the lateral response of the proposed system based on the superposition concept is also proposed. The FE results showed that the entire proposed system is a new design-based resilient system with the ability to dissipate energy without compromising the SC capacity of the main resisting system. Compared to the typical precast hollow core segmental column, a 6% reinforcement ratio of the ED unit can cause a 60% increase in lateral resistance and a 220% increase in the ED capacity. The analytical model can successfully be applied in the design of the proposed system to provide customized ED capabilities and controlled lateral resistance

Selective Flocculation Separation of Fine Hematite from Quartz Using a Novel Grafted Copolymer Flocculant

Beneficiation of ultrafine mineral particles (typically with an average size less than 20 µm) remains a critical problem for the mineral processing industry. Selective flocculation technique has been found to show great potential to tackle this problem, whose success mainly depends on the selective adsorption of a flocculant on the target mineral particles. In this work, a novel copolymer flocculant was synthesized by grafting starch and acrylamide, which for the first time, was employed in the flocculation separation of fine hematite from quartz. The composites of the grafted copolymer flocculant (GCF) were characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The single mineral flocculation results showed that at the pH of 10–11 and GCF concentration of 125 mg/L, hematite flocs with a compact texture were formed, whose average diameter and fractal dimension reached 36 µm and 2.02, respectively; while quartz flocs were barely observed, and the average diameter of particles stayed at approximately 20 µm. Furthermore, the selective flocculation separation was confirmed in the mixed mineral flocculation. From adsorption tests and zeta potential measurements, it is shown that GCF tended to adsorb more selectively and intensely on hematite surfaces compared with quartz. This study provides a valuable reference for the efficient recovery of fine hematite particles