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Energy-resolved neutron imaging is an effective way to investigate the internal structure and residual stress of materials. Different sample sizes have varying requirements for the detector's imaging field of view (FOV) and spatial resolution. Therefore, a dual-mode energy-resolved neutron imaging detector was developed, which mainly consisted of a neutron scintillator screen, a mirror, imaging lenses, and a time-stamping optical fast camera. This detector could operate in a large FOV mode or a high spatial resolution mode. To evaluate the performance of the detector, the neutron wavelength spectra and the multiple spatial resolution tests were conducted at CSNS. The results demonstrated that the detector accurately measured the neutron wavelength spectra selected by a bandwidth chopper. The best spatial resolution was about 20 μm in high spatial resolution mode after event reconstruction, and a FOV of 45.0 mm × 45.0 mm was obtained in large FOV mode. The feasibility was validated to change the spatial resolution and FOV by replacing the scintillator screen and adjusting the lens magnification.

In view of the electromagnetic interference existing in the well, it can greatly interfere with the voltage signal of the operational amplifier terminal collected by the dynamometer, and then affect the accuracy of the pressure value measured by the sensor. The design uses the domestic HC32L176 micro controller unit as the main control chip. Develop a dynamometer which uses the chip. Collect the voltage signal through the oscilloscope. Select the appropriate wavelet basis function, the number of decomposition layers, threshold rule and threshold function to decomposesignals containing noise. Filter out the high-frequency components of different layers,and then reconstruct the signal to obtain the denoising signal . Through Matlab simulation and practical test, the results show that the wavelet transform can achieve a good denoising of the collected voltage signal, and improve the reliability and stability of the bolt and cable dynamometer.

Reconfigurable intelligent surface (RIS) employs passive beamforming to control the wireless propagation channel, which benefits the wireless communication capacity and the received energy efficiency of wireless power transfer (WPT) systems. Such beamforming schemes are classified as discrete and non-convex integer programming problems. In this paper, we propose a Monte-Carlo (MC) based random energy passive beamforming of RIS to achieve the maximum received power of electromagnetic (EM) WPT systems. Generally, the Gibbs sampling and re-sampling methods are employed to generate phase shift vector samples. And the sample with the maximum received power is considered the optimal solution. In order to adapt to the application scenarios, we develop two types of passive beamforming algorithms based on such MC sampling methods. The first passive beamforming uses an approximation of the integer programming as the initial sample, which is calculated based on the channel information. And the second one is a purely randomized algorithm with the only total received power feedback. The proposed methods present several advantages for RIS control, e.g., fast convergence, easy implementation, robustness to the channel noise, and limited feedback requirement, and they are applicable even if the channel information is unknown. According to the simulation results, our proposed methods outperform other approximation and genetic algorithms. With our methods, the WPT system even significantly improves the power efficiency in the nonline-of-sight (NLOS) environment.

Abstract Ammonia-oxidizing archaea and bacteria (AOA and AOB, respectively) are important intermediate links in the nitrogen cycle. Apart from the AOA and AOB communities in soil, we further investigated co-occurrence patterns and microbial assembly processes subjected to inorganic and organic fertilizer treatments for over 35 years. The amoA copy numbers and AOA and AOB communities were found to be similar for the CK and organic fertilizer treatments. Inorganic fertilizers decreased the AOA gene copy numbers by 0.75–0.93-fold and increased the AOB gene copy numbers by 1.89–3.32-fold compared to those of the CK treatment. The inorganic fertilizer increased Nitrososphaera and Nitrosospira. The predominant bacteria in organic fertilizer was Nitrosomonadales. Furthermore, the inorganic fertilizer increased the complexity of the co-occurrence pattern of AOA and decreased the complexity pattern of AOB comparing with organic fertilizer. Different fertilizer had an insignificant effect on the microbial assembly process of AOA. However, great difference exists in the AOB community assembly process: deterministic process dominated in organic fertilizer treatment and stochastic processes dominated in inorganic fertilizer treatment, respectively. Redundancy analysis indicated that the soil pH, NO3 −N, and available phosphorus contents were the main factors affecting the changes in the AOA and AOB communities. Overall, this findings expanded our knowledge concerning AOA and AOB, and ammonia‐oxidizing microorganisms were more disturbed by inorganic fertilizers than organic fertilizers.

The pure corrosion, pure erosion and erosion-corrosion behaviours of X65 carbon steel in corrosive fluid and slurry of different pH were studied at low flow velocity. Results show that the corrosion pattern changed from general corrosion to pitting damage along with the occurrence of erosion in pH = 3 solution and it is postulated that this feature might be associated with changes in the cathodic reaction. The sand impacts would cause the transient of main cathodic reaction from hydrogen evolution to oxygen reduction. Density and connected small pits generated in pH = 7 solution containing sand particles. While, the increase of the solution pH from 7 to 11 resulted in more scattered and serious pitting damage, which is caused by more focused initial anodes. The occurrence of pitting damage has complicated the analysis of the electrochemical results. The sand impacts in pH = 13 solution could cause the local breakdown of passive film, leading to a significant decrease of pitting resistance.

Microbial diversity is an important indicator of soil fertility and plays an indispensable role in farmland ecosystem sustainability. The short-term effects of fertilization and rhizobium inoculation on soil microbial diversity and community structure have been explored extensively; however, few studies have evaluated their long-term effects. Here, we applied quantitative polymerase chain reaction (qPCR) and amplicon sequencing to characterize the effect of 10-year fertilizer and rhizobium inoculation on bacterial communities in soybean bulk and rhizosphere soils at the flowering–podding and maturity stages. Four treatments were examined: non-fertilization control (CK), phosphorus and potassium fertilization (PK), nitrogen and PK fertilization (PK + N), and PK fertilization and Bradyrhizobium japonicum 5821 (PK + R). Long-term co-application of rhizobium and PK promoted soybean nodule dry weight by 33.94% compared with PK + N, and increased soybean yield by average of 32.25%, 5.90%, and 5.00% compared with CK, PK, and PK + N, respectively. The pH of PK + R was significantly higher than that of PK and PK + N at the flowering–podding stage. The bacterial abundance at the flowering–podding stage was positively correlated with soybean yield, but not at the maturity stage. The significant different class Gemmatimonadetes, and the genera Gemmatimonas, and Ellin6067 in soil at the flowering–podding stage were negatively correlated with soybean yield. However, the bacterial community at class and genus levels at maturity had no significant effect on soybean yield. The key bacterial communities that determine soybean yield were concentrated in the flowering–podding stage, not at maturity stage. Rhizosphere effect, growth period, and treatment synergies resulted in significant differences in soil bacterial community composition. Soil organic matter (OM), total nitrogen (TN), pH, and available phosphorus (AP) were the main variables affecting bacterial community structure. Overall, long-term co-application of rhizobium and fertilizer not only increased soybean yield, but also altered soil bacterial community structure through niche reconstruction and microbial interaction. Rhizobium inoculation plays key role in reducing nitrogen fertilizer application and promoting sustainable agriculture practices.

In order to explore the antioxidant effect of the British red kidney bean antioxidant peptide components, ultrafiltration and dextran gel G-15 chromatography technology were used to classify the antioxidant products prepared by alkaline protease enzymatic hydrolysis of the British red kidney bean antioxidant protein, and the effect of components with higher antioxidant activity on PC12 cells damaged by H2O2 was studied. The results showed that the antioxidant peptide component BRKBAPC-2 could alleviate the cell growth inhibitory effect of H2O2 on PC12. With the increasing of peptide concentration, the level of intracellular reactive oxygen species (ROS) levels, malondialdehyde (MDA) content and lactate dehydrogenase (LDH) extracellular activity were all reduced, the activity of superoxide dismutase (SOD), catalase (CAT) and the content of reduced glutathione (GSH) were all increased, especially when the concentration of BRKBAPC-2 was 200 μg/mL, ROS level was 32.53%, MDA content was 0.96 nmol/μg prot, LDH extracellular activity was 202.12 U/L, compared with the model group, they were significantly reduced (P

Indigenous soil microbial biomass (ISMB) plays a key role in maintaining essential functions and biodiversity of soil health. One of the critical unknowns is how the indigenous microorganisms respond to different fertilizers which is directly related to agricultural production. Therefore, we used Mi-Seq sequencing and network analyses to compare the response of ISMB to biogas residue and chemical fertilizers. The results showed that crop production was profoundly influenced by levels of ISMB present and is further dependent on the strategy of fertilizer application. Higher ISMB primarily manifests through retention of richer microbial abundance, a balanced community structure, and tightened co-occurrence within a certain proportion of Nitrospirae, Rhizophlyctidaceae, and Gemmatimonadetes. Compared to chemical fertilizer, biogas residue resulted in higher production with more strongly linked nodes such as Actinobacteria, Chloroflexi and Gemmatimonadetes. Under the same level of ISMB, the microbial diversity was richer and co-occurrence was tighter when biogas residues were applied compared with chemical fertilizer. In addition, the higher level of ISMB with biogas residue applied had a lower abundance of potential fungal pathogens in both bulk and rhizosphere soil compared with chemical fertilizer. This study provides critical data to understand the influence of ISMB and biogas residue on soil ecological system.

Rhizosphere microbial communities are vital for plant growth and soil sustainability; however, the composition of rhizobacterial communities, especially the assembly process and co-occurrence pattern among microbiota after the inoculation of some beneficial bacteria, remains considerably unclear. In this study, we investigated the structure of rhizomicrobial communities, their assembly process, and interactions contrasting when Bradyrhizobium japonicum 5038 and Bacillus aryabhattai MB35-5 are co-inoculated or Bradyrhizobium japonicum 5038 mono-inoculated in black and cinnamon soils of soybean fields. The obtained results indicated that the Chao and Shannon indices were all higher in cinnamon soil than that in black soil. In black soil, the co-inoculation increased the Shannon indices of bacteria comparing with that of the mono-inoculation. In cinnamon soil, the co-inoculation decreased the Chao indices of fungi comparing with that of mono-inoculation. Compared with the mono-inoculation, the interactions of microorganisms of co-inoculation in the co-occurrence pattern increased in complexity, and the nodes and edges of co-inoculation increased by 10.94, 40.18 and 4.82, 16.91% for bacteria and fungi, respectively. The co-inoculation of Bradyrhizobium japonicum 5038 and Bacillus aryabhattai MB35-5 increased the contribution of stochastic processes comparing with Bradyrhizobium japonicum 5038 inoculation in the assembly process of soil microorganisms, and owing to the limitation of species diffusion might restrict the direction of pathogenic microorganism movement. These findings support the feasibility of rebuilding the rhizosphere microbial system via specific microbial strain inoculation and provide evidence that the co-inoculation of Bradyrhizobium japonicum 5038 and Bacillus aryabhattai MB35-5 can be adopted as an excellent compound rhizobia agent resource for the sustainable development of agriculture.

A partial pre-rusted wire beam electrode (WBE) was designed to study the influence of the rust layer on rebar corrosion in the carbonated simulated concrete pore solution (SCPS). The results show that the passive film generated on the pre-rusted steel area is more fragile than that formed on the fine polished steel area in carbonaceous media. Nevertheless, the pitting corrosion resulting from the presence of chloride ions still tends to occur on the fine polished steel surface due to the local acidification process being hindered by the rust layer. The rust layer could play a more important role than the passive film in inhibiting the initiation of chloride-induced corrosion on rebar. The expansion path of the corrosion product would be blocked by the rust layer, leading to the pit propagating in the fine polished region. Furthermore, the growth of pitting corrosion is greatly accelerated due to the catalytic cathodic reaction of the rust layer.

Within the framework of modified Layzer-type potential flow theory [V. N. Goncharov, “Analytical model of nonlinear, single-mode, classical Rayleigh-Taylor instability at arbitrary Atwood numbers,” Phys. Rev. Lett. 88, 134502 (2002)], we study bubble growth in compressible Rayleigh–Taylor (RT) and Richtmyer–Meshkov (RM) instabilities. It is known from adiabatic equations that the density ρ and adiabatic index γ are compressibility-related factors for a given static pressure p. Here, we introduce a dynamically varying stagnation point pressure P̃=p±12ρ̃η̇02, which relates time-varying quantities, such as fluid density ρ̃, pressure P̃, and bubble tip velocity η̇0, and then, we analytically derive the governing equations for time evolution of bubbles in the RT and RM instabilities of compressible fluids. For the RT instability, the upper fluid adiabatic index γu and density ρu increase the bubble amplitude and velocity, but they decrease the bubble curvature radius at the early stage, while the lower fluid adiabatic index γl and density ρl have opposite effects on those of γu and ρu, which is consistent with recent results. For the RM instability, γu and ρu decrease the bubble amplitude and velocity, but they increase the bubble curvature radius at the early stage; however, γl and ρl have opposite effects on those of γu and ρu. Moreover, we find a good agreement between our three-dimensional results of the RM bubble amplitude and recent numerical simulations.

In nuclear reactors, inelastic neutron scattering is a significant energy-loss mechanism which has deep impacts on designments of nuclear reactor and radiation shielding. Iron is an important material in reactor. However, for the existing nuclear data for iron, there exists an obvious divergence for the inelastic scattering cross sections and the related gamma production sections. Therefore the precise measurements are urgently needed for satisfying the demanding to design new nuclear reactors (fast reactors), Accelerator Driven Subcritical System (ADS), and other nuclear apparatus. In this paper, we report a new system with an array of HPGe detectors, electronics and acquisition system. Experiments had been carried out on three neutron facilities.

Wireless sensor networks (WSNs) have recently gained popularity for a wide spectrum of applications. Monitoring tasks can be performed in various environments. This may be beneficial in many scenarios, but it certainly exhibits new challenges in terms of security due to increased data transmission over the wireless channel with potentially unknown threats. Among possible security issues are timing attacks, which are not prevented by traditional cryptographic security. Moreover, the limited energy and memory resources prohibit the use of complex security mechanisms in such systems. Therefore, balancing between security and the associated energy consumption becomes a crucial challenge. This paper proposes a secure scheme for WSNs while maintaining the requirement of the security-performance tradeoff. In order to proceed to a quantitative treatment of this problem, a hybrid continuous-time Markov chain (CTMC) and queueing model are put forward, and the tradeoff analysis of the security and performance attributes is carried out. By extending and transforming this model, the mean time to security attributes failure is evaluated. Through tradeoff analysis, we show that our scheme can enhance the security of WSNs, and the optimal rekeying rate of the performance and security tradeoff can be obtained.

In practical localization system design, researchers need to consider several aspects to make the positioning efficiently and effectively, e.g., the available auxiliary information, sensing devices, equipment deployment and the environment. Then, these practical concerns turn out to be the technical problems, e.g., the sequential position state propagation, the target-anchor geometry effect, the Non-line-of-sight (NLOS) identification and the related prior information. It is necessary to construct an efficient framework that can exploit multiple available information and guide the system design. In this paper, we propose a scalable method to analyze system performance based on the Cramér–Rao lower bound (CRLB), which can fuse all of the information adaptively. Firstly, we use an abstract function to represent all of the wireless localization system model. Then, the unknown vector of the CRLB consists of two parts: the first part is the estimated vector, and the second part is the auxiliary vector, which helps improve the estimation accuracy. Accordingly, the Fisher information matrix is divided into two parts: the state matrix and the auxiliary matrix. Unlike the theoretical analysis, our CRLB can be a practical fundamental limit to denote the system that fuses multiple information in the complicated environment, e.g., recursive Bayesian estimation based on the hidden Markov model, the map matching method and the NLOS identification and mitigation methods. Thus, the theoretical results are approaching the real case more. In addition, our method is more adaptable than other CRLBs when considering more unknown important factors. We use the proposed method to analyze the wireless sensor network-based indoor localization system. The influence of the hybrid LOS/NLOS channels, the building layout information and the relative height differences between the target and anchors are analyzed. It is demonstrated that our method exploits all of the available information for the indoor localization systems and serves as an indicator for practical system evaluation.

Particle filters (PFs) are widely used for nonlinear signal processing in wireless sensor networks (WSNs). However, the measurement uncertainty makes the WSN observations unreliable to the actual case and also degrades the estimation accuracy of the PFs. In addition to the algorithm design, few works focus on improving the likelihood calculation method, since it can be pre-assumed by a given distribution model. In this paper, we propose a novel PF method, which is based on a new likelihood fusion method for WSNs and can further improve the estimation performance. We firstly use a dynamic Gaussian model to describe the nonparametric features of the measurement uncertainty. Then, we propose a likelihood adaptation method that employs the prior information and a belief factor to reduce the measurement noise. The optimal belief factor is attained by deriving the minimum Kullback–Leibler divergence. The likelihood adaptation method can be integrated into any PFs, and we use our method to develop three versions of adaptive PFs for a target tracking system using wireless sensor network. The simulation and experimental results demonstrate that our likelihood adaptation method has greatly improved the estimation performance of PFs in a high noise environment. In addition, the adaptive PFs are highly adaptable to the environment without imposing computational complexity.