The Effect of Nano-SiO2 Dispersed Methods on Mechanical Properties of Cement Mortar

Nano-SiO2 is added to the cement by using different dispersion methods, through the macroscopic mechanical properties to characterize its dispersion in the cement, it can be used to explore the best experimental process. The results show that the compressive strength of cement samples with different dispersion methods is different. When the physical dispersion method is used, the intensity is not improved, but the ultrasonic dispersion method is the smallest, and the dispersion of nano-SiO2 is -9.11%. When the surfactant is used as dispersant, the dispersion of nano-SiO2 by Naphthalene water reducer is the best, and the compressive strength is increased by 6.68%. By using polymeric dispersing agent, polyethylene glycol has a certain effect on the dispersion of nano-SiO2, but it has some damage to the cement (set-retarder, etc.). Based on the above experiments, we have obtained the best dispersion method, which uses ultrasonic dispersion, and also needs to add naphthalene water reducer

Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection

Despite the fact that DeepFake forgery detection algorithms have achieved impressive performance on known manipulations, they often face disastrous performance degradation when generalized to an unseen manipulation. Some recent works show improvement in generalization but rely on features fragile to image distortions such as compression. To this end, we propose Diff-ID, a concise and effective approach that explains and measures the identity loss induced by facial manipulations. When testing on an image of a specific person, Diff-ID utilizes an authentic image of that person as a reference and aligns them to the same identity-insensitive attribute feature space by applying a face-swapping generator. We then visualize the identity loss between the test and the reference image from the image differences of the aligned pairs, and design a custom metric to quantify the identity loss. The metric is then proved to be effective in distinguishing the forgery images from the real ones. Extensive experiments show that our approach achieves high detection performance on DeepFake images and state-of-the-art generalization ability to unknown forgery methods, while also being robust to image distortions

Intelligent Multi-Modal Sensing-Communication Integration: Synesthesia of Machines

In the era of sixth-generation (6G) wireless communications, integrated sensing and communications (ISAC) is recognized as a promising solution to upgrade the physical system by endowing wireless communications with sensing capability. Existing ISAC is mainly oriented to static scenarios with radio-frequency (RF) sensors being the primary participants, thus lacking a comprehensive environment feature characterization and facing a severe performance bottleneck in dynamic environments. To date, extensive surveys on ISAC have been conducted but are limited to summarizing RF-based radar sensing. Currently, some research efforts have been devoted to exploring multi-modal sensing-communication integration but still lack a comprehensive review. Therefore, we generalize the concept of ISAC inspired by human synesthesia to establish a unified framework of intelligent multi-modal sensing-communication integration and provide a comprehensive review under such a framework in this paper. The so-termed Synesthesia of Machines (SoM) gives the clearest cognition of such intelligent integration and details its paradigm for the first time. We commence by justifying the necessity of the new paradigm. Subsequently, we offer a definition of SoM and zoom into the detailed paradigm, which is summarized as three operation modes. To facilitate SoM research, we overview the prerequisite of SoM research, i.e., mixed multi-modal (MMM) datasets. Then, we introduce the mapping relationships between multi-modal sensing and communications. Afterward, we cover the technological review on SoM-enhance-based and SoM-concert-based applications. To corroborate the superiority of SoM, we also present simulation results related to dual-function waveform and predictive beamforming design. Finally, we propose some potential directions to inspire future research efforts.Comment: This paper has been accepted by IEEE Communications Surveys & Tutorial

AMC: an adaptive multi-level cache algorithm in hybrid storage systems

Hybrid storage systems that consist of flash-based solid state drives (SSDs) and traditional disks are now widely used. In hybrid storage systems, there exists a two-level cache hierarchy that regard dynamic random access memory (DRAM) as the first level cache and SSD as the second level cache for disk storage. However, this two-level cache hierarchy typically uses independent cache replacement policies for each level, which makes cache resource management inefficient and reduces system performance. In this paper, we propose a novel adaptive multi-level cache (AMC) replacement algorithm in hybrid storage systems. The AMC algorithm adaptively adjusts cache blocks between DRAM and SSD cache levels using an integrated solution. AMC uses combined selective promote and demote operations to dynamically determine the level in which the blocks are to be cached. In this manner, the AMC algorithm achieves multi-level cache exclusiveness and makes cache resource management more efficient. By using real-life storage traces, our evaluation shows the proposed algorithm improves hybrid multi-level cache performance and also increases the SSD lifetime compared with traditional multi-level cache replacement algorithms

Study of Mechanical Properties and Durability of Alkali-Activated Coal Gangue-Slag Concrete

Herein, a new geopolymer is recognized as a potential alternative cementing material of ordinary Portland cement (OPC), which is used for reducing carbon emissions and efficiently recycling the waste. Therefore this paper mainly studied the alkali-activated coal gangue-slag concrete (ACSC) was prepared by using the coal gangue-slag and Na2SiO3 and NaOH complex activator. The ratio of coal gangue (calcined and uncalcined) coarse aggregate replacing the gravel was 0%, 30%, 50%, 70%, and 100%. The water and salt freeze-thaw resistance, compressive strength, chloride permeation, microstructure, performance mechanism, inner freeze-thaw damage distribution, and mechanics models of ACSC were investigated. Results show that ACSC displayed excellent early age compressive strength, and the compact degree and uniformity of structure were better compared with the ordinary Portland cement (OPC) when the coal gangue replacement rate was less than 50%. The ACSC demonstrated the best chloride penetration resistance under 30% uncalcined coal gangue content, which was less than 27.75% lower than that of using OPC. At the same number cycles, especially in the salt freezing, the calcined coal gangue had lowered advantages of improving resistance freeze-thaw damage resistance. Water and salt accumulative freeze-thaw damage mechanics models of ACSC were established by using the relative dynamic elasticity modulus. The exponential function model was superior to the power function model with better precision and relativity, and the models accurately reflected the freeze-thaw damage effect

Salt Tolerance Evaluation of Cucumber Germplasm under Sodium Chloride Stress

Cucumber (Cucumis sativus L.) is an important horticultural crop worldwide. Sodium (Na+) and chloride (Cl−) in the surface soil are the major limiting factors in coastal areas of Shandong Province in China. Therefore, to understand the mechanism used by cucumber to adapt to sodium chloride (NaCl), we analyzed the phenotypic and physiological indicators of eighteen cucumber germplasms after three days under 100 and 150 mM NaCl treatment. A cluster analysis revealed that eighteen germplasms could be divided into five groups based on their physiological indicators. The first three groups consisted of seven salt-tolerant and medium salt-tolerant germplasms, including HLT1128h, Zhenni, and MC2065. The two remaining groups consisted of five medium salt-sensitive germplasms, including DM26h and M1-2-h-10, and six salt-sensitive germplasms including M1XT and 228. A principal component analysis revealed that the trend of comprehensive scores was consistent with the segmental cluster analysis and survival rates of cucumber seedlings. Overall, the phenotype, comprehensive survival rate, cluster analysis, and principal component analysis revealed that the salt-tolerant and salt-sensitive germplasms were Zhenni, F11-15, MC2065, M1XT, M1-2-h-10, and DM26h. The results of this study will provide references to identify or screen salt-tolerant cucumber germplasms and lay a foundation for breeding salt-tolerant cucumber varieties

3D Airborne EM Forward Modeling Based on Time-Domain Spectral Element Method

Airborne electromagnetic (AEM) method uses aircraft as a carrier to tow EM instruments for geophysical survey. Because of its huge amount of data, the traditional AEM data inversions take one-dimensional (1D) models. However, the underground earth is very complicated, the inversions based on 1D models can frequently deliver wrong results, so that the modeling and inversion for three-dimensional (3D) models are more practical. In order to obtain precise underground electrical structures, it is important to have a highly effective and efficient 3D forward modeling algorithm as it is the basis for EM inversions. In this paper, we use time-domain spectral element (SETD) method based on Gauss-Lobatto-Chebyshev (GLC) polynomials to develop a 3D forward algorithm for modeling the time-domain AEM responses. The spectral element method combines the flexibility of finite-element method in model discretization and the high accuracy of spectral method. Starting from the Maxwell\u27s equations in time-domain, we derive the vector Helmholtz equation for the secondary electric field. We use the high-order GLC vector interpolation functions to perform spectral expansion of the EM field and use the Galerkin weighted residual method and the backward Euler scheme to do the space- and time-discretization to the controlling equations. After integrating the equations for all elements into a large linear equations system, we solve it by the multifrontal massively parallel solver (MUMPS) direct solver and calculate the magnetic field responses by the Faraday\u27s law. By comparing with 1D semi-analytical solutions for a layered earth model, we validate our SETD method and analyze the influence of the mesh size and the order of interpolation functions on the accuracy of our 3D forward modeling. The numerical experiments for typical models show that applying SETD method to 3D time-domain AEM forward modeling we can achieve high accuracy by either refining the mesh or increasing the order of interpolation functions

Exploitation of enrofloxacin-loaded docosanoic acid solid lipid nanoparticle suspension as oral and intramuscular sustained release formulations for pig

In our previous study, enrofloxacin-loaded docosanoic acid solid lipid nanoparticles (SLNs) could be effectively delivered to cells in vitro. In this study, its properties and exploitation as possible oral and intramuscular sustained release formulations for pigs were studied after being made into suspension. The re-dispersed time and sedimentation rate of the nanosuspension were 55 s and 1, respectively. It showed good stability when stored away from light and sustained release in pH = 7.4 PBS buffer. The suspension exhibited no irritation at the injection site and good palatability. Compared with commercial injection and soluble powder, the nanosuspension increased the bioavailability of enrofloxacin by 1.63 and 2.38 folds, and extended the mean residence time (MRT) of the drug from 11.27 and 12.33 to 37.76 and 35.15 h after intragastric and intramuscular administration, respectively. These results suggest that docosanoic acid SLN suspension (DAS) might be a promising oral and intramuscular sustained release formulation to enhance the pharmacological activity of enrofloxacin