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Rapid, accurate detection of heavy-metal content is extremely important for precise risk control and targeted remediation. Herein, a general modeling method and process based on the relationship between Pxrf measured values and site parameters are explored to construct a Pxrf correction model suitable to improve each site’s measurement accuracy. Results show a significant correlation between Pb, Mn, and Zn Pxrf measured values and actual concentrations, with correlation coefficients between 0.8 and 0.93. Through the correlation analysis, the correlation coefficient between the water content and the measured value of pxrf is in the range of 0.2–0.5. Pxrf measurement of all heavy metals was weakly affected by soil organic matter content, with correlation coefficients all lower than 0.5. Model transformation effectively improved the correlation between measured Pxrf value and actual concentration, and transformation increased the correlations of Sr, Mn, and Cu by around 0.11. Model verification results showed that the Pb, Zn, Fe, and Mn models can be used to improve Pxrf method detection accuracy.

Aiming at severe soil secondary salinization, poor water retention and insufficient salt tolerance of conventional acrylic-based modifiers in arid and semi-arid regions of China, a poly(ethylene glycol) maleate citrate (PEGMC) crosslinking monomer was synthesized through esterification, and a dual covalent–hydrogen crosslinked P(PEGMC/AA) hydrogel was fabricated via free radical copolymerization with acrylic acid (AA). The hydrogel was characterized by NMR, FTIR, SEM, TGA and elemental mapping, while its binding mechanism with saline–alkali ions was elucidated through DFT calculations and molecular dynamics simulations. Its amelioration performance was evaluated through swelling, soil water retention, desalination and pot germination experiments. The hydrogel exhibited outstanding water absorbency, salt resistance and dry–wet cycling stability, with swelling ratios of 712 g/g in deionized water and 285 g/g in 0.9% NaCl solution, and remained 200 g/g after four dry–wet cycles. It enhanced soil water retention remarkably (over 93% after 72 h). At 0.30% dosage, soil salt content declined from 7.1 g/kg to 1.3 g/kg with desalination efficiency exceeding 80%, owing to porous physical adsorption and chemical chelation toward Na+, Ca2+ and Mg2+, with a binding energy of −136.936 kJ/mol. Pot tests revealed that crop germination rate rose from 19% (blank) to 75% under severe saline–alkali stress. Meanwhile, the hydrogel inhibited nutrient leaching and favored soil-water conservation. This work first incorporated PEGMC monomer into agricultural hydrogels to construct a stable dual crosslinked network, clarifying its synergistic mechanisms for salt fixation and water retention macroscopically and microscopically. It provides a promising functional material and theoretical basis for green, efficient in situ amelioration of dryland saline–alkali soil.

Porous graphitic carbon nitride (g-C3N4) was prepared by dicyandiamide and urea via the pyrolysis method, which possessed enhanced visible-light-driven photocatalytic performance. Its surface area was increased from 17.12 to 48.00 m2/g. The porous structure not only enhanced the light capture capacity, but also accelerated the mass transfer ability. The Di (Dicyandiamide)/Ur (Urea) composite possessed better photocatalytic activity for Rhodamine B in visible light than that of g-C3N4. Moreover, the Di/Ur-4:5 composite showed the best photoactivity, which was almost 5.8 times that of g-C3N4. The enhanced photocatalytic activity showed that holes and superoxide radical played a key role in the process of photodegradation, which was ascribed to the enhanced separation of photogenerated carriers. The efficient separation of photogenerated electron-hole pairs may be owing to the higher surface area, O dopant, and pore volumes, which can not only improve the trapping opportunities of charge carriers but also the retarded charge carrier recombination. Therefore, it is expected that the composite would be a promising candidate material for organic pollutant degradation.

Affected by artificial intelligence and automation technology, robotic arms have become increasingly widespread. However, traditional impedance control algorithms have been unable to adapt robotic arms to increasingly complex environmental changes. Therefore, an adaptive impedance control algorithm based on variable stiffness, neural networks, and motion trajectories is developed. Then, it is used for intelligent control of robotic arms. This method employs an impedance relationship model and dynamically optimizes inertia, damping, and stiffness parameters through PD algorithm. The physical quantities such as joint angular acceleration and end displacement are input into the neural network, which outputs key stiffness and interference to estimate the unknown environment in real-time. An adaptive trajectory generation module is designed and combined with contact force feedback to achieve collaborative optimization. The experimental results showed that in terms of contact force with the environment, the error rate between the contact force controlled by this algorithm and the expected value was about 2%. In terms of joint position, the error between the selected joint position in the experiment and the expected value was kept within 0.5%. When running under the motion trajectory generated by the algorithm, the error of each parameter value was less than 1%. The adaptive impedance control algorithm can significantly improve the stability, accuracy, and safety of robotic arm control. The research results have potential applications in improving the environmental adaptability of robotic arms.

Landfilling is one of the important methods in hazardous waste treatment. In order to prevent the landfill leachate from connecting with external groundwater and prevent leachate from flowing into external polluted water bodies and soil, vertical anti-seepage membranes will be installed along the perimeter of the reservoir area. Given the structural characteristics of vertical HDPE membranes and site conditions, this study proposes the application of three-dimensional high-density electrical resistivity (3D-HDER) tomography for the detection of these membranes. Compared with the traditional resistivity method, the high-density resistivity method can realize automatic switching of electrode device type, electrode spacing and measuring points during the measurement process, thereby improving detection accuracy and work efficiency. By employing 3D-HDER for data collection on vertical HDPE membranes and inverting the subsurface resistivity distribution, the presence of leaks can be inferred based on the distribution of low-resistivity anomalies in the target underground area, thereby facilitating the integrity assessment of the vertical HDPE membranes. This research was applied in a practical investigation at a municipal landfill site in Hunan Province, where field tests were conducted, and the effectiveness of 3D-HDER in detecting vertical HDPE membranes was validated through excavation. The experimental results indicate that: (1) 3DHDER is capable of effectively and accurately locating shallow leaks, and (2) low resistivity anomalies were observed in the vicinity of the leaks.

To address the issue of industrial and mining wastewater leakage, this paper proposes a novel detection method for underground non-pressurized pipelines based on the combination of multiple electrical methods. The method integrates the high-density electrical method and the natural potential method, utilizing the naturally powered natural potential method for real-time monitoring. When a suspected leakage is de- tected, the high-density electrical method is used for precise localization and analysis of the leakage, enabling effective monitoring of industrial and mining wastewater leakage. A corresponding portable detection system has been designed, and both the detection method and the system have been validated through experiments.

To address leakage caused by the deterioration of non-membrane impervious structures, such as impervious tanks used in industrial and mining sites, this paper develops a leakage monitoring system based on multi-electrical method fusion. By jointly analyzing the spatial potential distribution and the amplitude and phase parameters obtained from the complex resistivity method, the proposed system can identify leakage from industrial and mining wastewater facilities. The portable detection system developed has been verified by experiments, and its detection results have good reliability.

Spread Transform Dither Modulation (STDM) has good performance in robustness against Additive White Gaussian Noise (AWGN) and re-quantization, so it has been widely used in image watermarking algorithms. However, STDM cannot resist Fixed Gain Attack (FGA). In the paper, we introduce an adaptive function into the traditional STDM algorithm, so that it can automatically adjust the amount of distortion according to the text line spacing in the document. Then we give an improved adaptive function to make our algorithm robust to FGA. Analysis and experimental results show that the algorithm proposed in this paper has good invisibility and high robustness against AWGN and FGA.

Porous graphitic carbon nitride (g-C N ) was prepared by dicyandiamide and urea via the pyrolysis method, which possessed enhanced visible-light-driven photocatalytic performance. Its surface area was increased from 17.12 to 48.00 m /g. The porous structure not only enhanced the light capture capacity, but also accelerated the mass transfer ability. The Di (Dicyandiamide)/Ur (Urea) composite possessed better photocatalytic activity for Rhodamine B in visible light than that of g-C N . Moreover, the Di/Ur-4:5 composite showed the best photoactivity, which was almost 5.8 times that of g-C N . The enhanced photocatalytic activity showed that holes and superoxide radical played a key role in the process of photodegradation, which was ascribed to the enhanced separation of photogenerated carriers. The efficient separation of photogenerated electron-hole pairs may be owing to the higher surface area, O dopant, and pore volumes, which can not only improve the trapping opportunities of charge carriers but also the retarded charge carrier recombination. Therefore, it is expected that the composite would be a promising candidate material for organic pollutant degradation.

Different pollutants affect electrical characteristics of soil, e.g., electric resistivity and capacity. The most extensively used non-intrusive methods in mapping these physical characteristics are electrical method. To better understand the effect of different hydrogeological and environmental process on resistivity and phase of complex resistivity under water-saturated soil, we carried out a controlled laboratory experiment where the host material was simulated by sand soil and the hydrogeological and environmental processes by groundwater table rise, seawater intrusion and heavy metal contamination. The experiment measured the resistivity and phase of soil saturated and unsaturated, with different pollutants added, together with their time-lapse change in a well-controlled column. With the involvement of more measurement parameters, complex resistivity method can provide more information than resistivity method, thereby having better performance in the detection and monitoring of changes in electrical properties of complex contaminated sites. For example, it is capable of discriminating the different contamination process, in this case, e.g., seawater intrusion and heavy metal contamination. In addition, it is still sensitive to the change of pollutant concentration even in site with high added concentration. Furthermore, simulating the saltwater-intruded site contaminated by manganese, it was found that the change of resistivity (ρ) can hardly be observed, while the responses of phase (φ) are so obvious that can be clearly observed.