Preparation of Kaolin Composites and Its Adsorption for Sb(Ⅲ)

Antimony is an important element in the production of flame retardants and semiconductor materials. In the process of antimony mining, it may cause local environmental pollution, which has adverse effects on human health, and the development of economical and efficient adsorbents to remove antimony from wastewater has become a hot research topic. In this paper, the hydrothermal synthesis method was adopted, and purified Kaolin was selected as the carrier, potassium permanganate, manganese chloride and ferric chloride are the metal sources, urea is the precipitant, and sodium dodecyl benzene sulfonate is the structure guide agent. Under the conditions of 5% mass fraction of dispersant, loading temperature of 140 ℃, reaction time of 8 h, mass ratio of iron to manganese of 1.84:1, and mass of precipitant of 0.9 g, the composites prepared were effective in adsorbing the Sb(Ⅲ) from the wastewater. The optimum adsorption efficiency of the prepared composites on Sb(Ⅲ) is 92.83%, which showed excellent adsorption performance

Learning to Accelerate Symbolic Execution via Code Transformation

Symbolic execution is an effective but expensive technique for automated test generation. Over the years, a large number of refined symbolic execution techniques have been proposed to improve its efficiency. However, the symbolic execution efficiency problem remains, and largely limits the application of symbolic execution in practice. Orthogonal to refined symbolic execution, in this paper we propose to accelerate symbolic execution through semantic-preserving code transformation on the target programs. During the initial stage of this direction, we adopt a particular code transformation, compiler optimization, which is initially proposed to accelerate program concrete execution by transforming the source program into another semantic-preserving target program with increased efficiency (e.g., faster or smaller). However, compiler optimizations are mostly designed to accelerate program concrete execution rather than symbolic execution. Recent work also reported that unified settings on compiler optimizations that can accelerate symbolic execution for any program do not exist at all. Therefore, in this work we propose a machine-learning based approach to tuning compiler optimizations to accelerate symbolic execution, whose results may also aid further design of specific code transformations for symbolic execution. In particular, the proposed approach LEO separates source-code functions and libraries through our program-splitter, and predicts individual compiler optimization (i.e., whether a type of code transformation is chosen) separately through analyzing the performance of existing symbolic execution. Finally, LEO applies symbolic execution on the code transformed by compiler optimization (through our local-optimizer). We conduct an empirical study on GNU Coreutils programs using the KLEE symbolic execution engine. The results show that LEO significantly accelerates symbolic execution, outperforming the default KLEE configurations (i.e., turning on/off all compiler optimizations) in various settings, e.g., with the default training/testing time, LEO achieves the highest line coverage in 50/68 programs, and its average improvement rate on all programs is 46.48%/88.92% in terms of line coverage compared with turning on/off all compiler optimizations

Digital identity, privacy security, and their legal safeguards in the Metaverse

The Metaverse is the digitization of the real world, supported by big data, AI, 5G, cloud computing, blockchain, encryption algorithm, perception technology, digital twin, virtual engine, and other technologies that interact with human behavior and thoughts in avatars through digital identity. Cracking the trust problem brought by the avatar depends on the privacy security and authentication technology for individuals using digital identities to enter the Metaverse. To accomplish personal domination of the avatar, metaverse users need privacy data feeding and emotion projection. They must be equipped with proprietary algorithms to process and analyze the complex data generated in adaptive interactions, which challenges the privacy security of user data in the Metaverse. Distinguishing the significance of different identifiers in personal identity generation while imposing different behavioral regulatory requirements on data processing levels may better balance the relationship between personal privacy security and digital identity protection and data utilization in the Metaverse. In response to digital identity issues, there is an objective need to establish a unified digital identity authentication system to gain the general trust of society. Further, the remedies for a right to personality can be applied to the scenario of unlawful infringement of digital identity and privacy security

Study on Dust Removal Technology of Explosive Water Mist in Drill and Blast Tunnelling

In view of the problem that high concentration of dust is easily generated during rock tunnel drilling and blasting construction, explosive water mist to reduce dust is given in this paper. Water bag is set up on tunnel face and explosive water mist is used to reduce blasting dust concentration. With the help of numerical simulation software FLUENT and combined with theoretical analysis, The key parameters of explosion fog and dust reduction technology are obtained: water bag spacing, blasting time difference, water bag layout position, etc., which provides a theoretical basis for practical application of the technology. At the same time, combined with the field test of Huangtai tunnel blasting, the dust concentration with and without water mist was measured, respectively. The results show that the maximum dust removal rate of the tunnel section under the dust removal measures with water mist can reach 80.85%, the average dust removal rate can reach 65.16%. So, the dust removal effect is remarkable

Preparation of Material for Adsorption Ag(I) in the Solution

The application of silver in electronics, jewelry, catalytic and other industries often produces a large amount of silver-containing wastewater, which causes serious impact to the surrounding environment and human health, while silver has a certain economic value attached to it. Therefore, how to effectively treat and recover Ag(?) from the silver-containing wastewater is a hot topic of concern at present. In order to seek an efficient and environmentally friendly adsorbent, this paper compared the adsorption efficiency of purified, thermally modified, acid modified and thermally-acid modified Bentonite on silver, selected an economical and reasonable purified clay as a carrier, and then completed the preparation of modified Bentonite as well as the optimization of conditions with sodium silicate as a surfactant and 3-mercaptopropyltrimethoxysilane as a modifier. The experiments showed that under the conditions of sodium silicate dosage of 15% of Bentonite, Bentonite and modifier dosage of 1:1, solution pH of 9, temperature of 45 °C and modification time of 5 h, the synthesized sulfhydryl modified Bentonite has good adsorption performance on Ag(?), and its adsorption capacity can reach 293.7 mg·g-1