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Abstract We couple to group field theory (GFT) a scalar field that encodes the entanglement between manifold sites. The scalar field provides a relational clock that enables the derivation of the Hamiltonian of the system from the GFT action. Inspecting the Hamiltonian, we show that a theory of emergent gravity arises, and that this can be recast according to the Ashtekar’s formulation of general relativity. The evolution of the GFT observables is regulated by the Shrödinger equation generated by the Hamiltonian. This is achieved by imposing a renormalization group (RG) flow that corresponds to a simplified Ricci flow. As a consequence of the quantization procedure, the Hamiltonian is recovered to be non-Hermitian, and can be related to the complex action formalism, in which the initial conditions and the related future evolution of the systems are dictated by the imaginary part of the action.

Future radar Earth observation missions, with reduced revisit times, will offer the capability to obtain valuable data applicable to agriculture and meteorology. They will contribute to a better understanding of some observed changes that exhibit time scales much shorter than present satellite revisit times. In the context of the preparatory studies in support of future radar mission proposals with reduced revisit time, such as the geosynchronous HydroTerra, the HydroSoil facility has been set up for C-band radar continuous monitoring of crops with a time resolution of 10 min and a spatial resolution of 1 m2. The data obtained for a corn crop observed along the life cycle has been analyzed to model radar backscattering dependence on crop development parameters. In this study, it is particularly noticeable that the interferometric coherence was measured over a 24-h interval, in contrast to previous studies. Coherence has shown a strong sensitivity to plant height and the phenological stage of the crop, which can be exploited to sense crop growth with radar measurements. However, due to the high density and size of the developed corn canopy, the relationship between coherence and crop height is limited to the first corn stages. For this reason, a new parameter named daily growth rate has been defined and found to be well correlated with the radar coherence.

Pesticides can induce target plants to release odors that are attractive or repellent to their herbivore insects. But, to date, the activity of volatile organic compounds (VOCs), singly or as mixtures, which play a crucial role in the olfactory behavior of herbivore insects, remains unclear. The objective of our research was to investigate the impact of thiamethoxam (TMX), a pesticide, on the emission of odors by wheat plants, and how these odors influence the behavior of grain aphids (Sitobion miscanthi). S. miscanthi showed a greater repellent response to the volatiles emitted by Thx-induced plants compared to those emitted by uncoated plants. Using gas chromatography–mass spectrometry (GCMS), we discovered that TMX greatly induced the release of VOCs in wheat plants. For instance, the levels of Bornyl acetate, 2-Oxepanone, Methyl acrylate, Cyclohexene, α-Pinene, and 1-Nonanol in coated wheat plants were significantly higher as compared to uncoated wheat plants. Moreover, varying concentrations also had an impact on the olfactory behavior of S. miscanthi. For instance, Cyclohexene exhibited clear attractiveness to aphids at concentrations of 100 μL/mL, whereas it displayed evident repellent properties at concentrations of 1 μL/mL and 10 μL/mL. These new findings demonstrate how TMX-induced VOCs affect the behavior of S. miscanthi and could help in developing innovative approaches to manage aphids by manipulating the emission of plant volatiles. Furthermore, these findings can also be utilized to evaluate substances that either attract or repel aphids, with the aim of implementing early monitoring and environmentally friendly methods to manage aphids, while simultaneously impeding the spread of viruses.

The utilization of solid waste as a resource is a beneficial approach to achieve pollution reduction and carbon reduction simultaneously. In this paper, we developed a quaternary solid waste-based cementitious materials (SWCMs) that can be used as a substitute for cement by utilizing four types of solid waste, namely ground granulated blast furnace slag (GGBS), steel slag (SS), ammonia-soda residue (ASR) and desulfurization gypsum (DG). The performance optimization and carbon emissions of SWCMs are investigated by response surface methodology and emission factor calculations. The results showed that a second-order polynomial model can accurately predict the compressive strength of mortar specimens of SWCMs, with prediction accuracies of 96.78 % and 87.17 % for compressive strengths at 3 days and 28 days, respectively. In terms of raw materials, DG content positively correlates with the compressive strength of the mortar containing SWCMs, moreover, ratios of GGBS to ASR of less than two or more than eight are beneficial. In addition, the production process of each ton of SWCMs emits 71.51 kg CO2, which is only 10 % of the production process of ordinary Portland cement. Overall, this work elucidates the influence of raw materials on the mechanical properties of quaternary SWCMs and quantifies their carbon reduction effects as a substitute for traditional cement, advancing the investigation and application of SWCMs in the realm of low-carbon materials.

High-speed train operation may cause vibration near track facilities and propagate far through the ground, affecting people’s lives, work, and normal use of precision instruments in an urban environment. An efficient numerical method is proposed to calculate the non-uniform ground vibration under a moving high-speed railway load. The theory of stochastic variables is used to describe the soil spatial variability of the non-uniform layered elastic ground, and the coupled 2.5D random finite element method (FEM) is proposed to reduce the computational cost without losing accuracy. Vibration propagation and attenuation of the non-uniform layered ground are investigated and the effect of train speed and soil non-homogeneity are analyzed. Results show that (1) at cross speed and high speed, the homogeneity coefficient of the layered ground has the most important influence on the ground vibration amplitude; (2) the upward acceleration is much larger than the downward acceleration at most speeds, and at cross speed and high speed, the acceleration amplitude decreases with the increase in the homogeneity coefficient; (3) as train speed increases from 60 m/s to 130 m/s, the influencing range of the homogeneity coefficient increases to 10 m from 2 m; and (4) the phenomenon of an in increase in local rebound can be observed in the velocity and acceleration attenuation curve at cross speed when the ground soil has a weaker homogeneity.

Abstract Walnut shell is lightweight material with high‐strength and toughening characteristics, but it is different from other nut shells’ microstructure with two or three short sclerotic cell layers and long bundle fibers. It is essential to explore the fracture resistance biomechanism of lightweight walnut shell and how to prevent damage of bionic structure. In this study, it is found that the asymmetric mass center and geometric center dissipated impact energy to the whole shell without loading concentration in the loading area. Diaphragma juglandis is a special structure improved walnut shell's toughening. The S‐shape gradient porosity/elastic modulus distribution combined with pits on single auxetic sclerotic cells requires higher energy to crack expansion, then decreases its fracture behavior. These fantastic findings inspire to design fracture resistance devices including helmets, armor, automobile anti‐collision beams, and re‐entry capsule in spacecraft.

Background and AimsUlcerative colitis (UC) has become a global public health concern, and is in urgent need of novel therapies. Fecal microbiota transplantation (FMT) targeting gut microbiota has recently been applied to the treatment of UC. Despite its recent successes, it is still largely unknown how FMT functionally modulates the gut microbiota and improves the disease.MethodsWe prospectively collected fecal samples from the 40 mice (30 mice for dextran sulfate sodium (DSS)-induced, 10 for controls), followed by Propidium monoazide treatment for 16S rRNA gene sequencing. These 30 mice were divided equally into 3 groups, which were transplanted with original donor microbiota (DO), inactivated donor microbiota (DI) and saline, respectively. Subsequently, we used 16S rRNA gene sequencing to analyze the viable gut bacteria of ulcerative colitis (UC) mice and histological analysis to evaluate the effects of fecal microbiota transplantation (FMT) with viable microbiota.ResultsWe demonstrated that the community structure of viable bacteria was significantly different from fecal bacteria based on total DNA. Furthermore, the intestinal viable microbiota and colonic mucosal structure of mice were significantly changed by DSS induction. The histological analysis showed that only the mice treated with original donor microbiota group (HF) achieved a significant improvement. Compared with inactivated donor microbiota group (IF) and saline (NF), Lactobacillus and Halomonas were significantly enriched in the HF group.ConclusionWe inferred that only live bacteria from human donor reversed the histopathology and symptoms of UC in mice and altered the gut microbiota. The activity of gut microbiota in donor samples should be considered in FMT and that detailed analysis of viable microbiota is essential to understand the mechanisms by which FMT produces therapeutic effects in the future.

Coal fire is a global catastrophe that causes resource waste, economic loss, and environmental pollution. Accurate detection of surface abnormalities induced by coal fires (such as thermal anomalies and land deformation) is critical for coal fire monitoring and extinguishment. However, the conventional thermal anomaly detection methods do not consider the temporal variation of land surface temperature (LST). Moreover, previous studies have not applied the polarimetric persistent scatterer interferometry(PolPSI) technique for coal-fire-related ground deformation monitoring, which is supposed to have better performance than conventional persistent scatterer interferometry (PSI) approaches. To this end, in this study, a spatio-temporal temperature-based thresholding (STTBT) algorithm is proposed to detect thermal anomalies, firstly. Then, the ground deformation obtained by the PolPSI method is combined with the detected thermal anomalies for the coal fire detection. Besides, a two-stage bandpass filter is employed to assist in detecting the suspected coal fire. The results in the Fukang coal fire area, China, demonstrate that, compared with the conventional methods, the proposed STTBT mothed achieves higher accuracy of thermal anomalies detection, thereby can able to detect coal fire areas more effectively. In addition, PolPSI has better performance than PSI in ground deformation monitoring over coal fire areas. The proposed STTBT combined with PolPSI can serve as a powerful tool for detecting and monitoring underground coal fires.

From the requirements of enterprise digital transformation and the challenges faced by big data platform, the construction ideas and principles of unified data lake were expounded.A unifid data lake construction scheme based on BSS/MSS/OSS cross domain fusion was proposed, which adopted logical unification, physical dispersion, unified data directory, unified security management and application of decoupling fusion.The construction practice of unified data lake was described in recent two years.

Underground coal fire is a global geological disaster that causes the loss of resources as well as environmental pollution. Xinjiang, China, is one of the regions suffering from serious underground coal fires. The accurate monitoring of underground coal fires is critical for management and extinguishment, and many remote sensing-based approaches have been developed for monitoring over large areas. Among them, the multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been recently employed for underground coal fires-related ground deformation monitoring. However, MT-InSAR involves a relatively high computational cost, especially when the monitoring area is large. We propose to use a more cost-efficient Stacking-InSAR technique to monitor ground deformation over underground coal fire areas in this study. Considering the effects of atmosphere on Stacking-InSAR, an ERA5 data-based estimation model is employed to mitigate the atmospheric phase of interferograms before stacking. Thus, an adaptive ERA5-Corrected Stacking-InSAR method is proposed in this study, and it is tested over the Fukang coal fire area in Xinjiang, China. Based on original and corrected interferograms, four groups of ground deformation results were obtained, and the possible coal fire areas were identified. In this paper, the ERA5 atmospheric delay products based on the estimation model along the LOS direction (D-LOS) effectively mitigate the atmospheric phase. The accuracy of ground deformation monitoring over a coal fire area has been improved by the proposed method choosing interferograms adaptively for stacking. The proposed Adaptive ERA5-Corrected Stacking-InSAR method can be used for efficient ground deformation monitoring over large coal fire areas.

Anterior Cervical Discectomy and Fusion (ACDF) is the preferred surgical method for the treatment of severe cervical degenerative disc disease with radiculopathy or myelopathy, of which the objectives are to restore the normal height of intervertebral space and cervical lordosis through the implantation of cervical interbody fusion cage. The biomechanical performance of a cervical interbody fusion cage, which plays a significant role in achieving the goals of ACDF, is influenced by multiple factors. In this paper, various studies focusing on the biomechanical performance of cervical interbody fusion cage are reviewed. Furthermore, the research methods, biomechanical evaluation parameters and data analysis methods of these research are analyzed in order to obtain a comprehensive understanding of the progress and limitations of research in this field. Although great progress has been made to clarify the biomechanical behaviors of cervical interbody fusion cage, there is still controversy regarding the issues such as the relative contribution of multiple factors to the performance of cage, the interactions among these factors, as well as whether the effects of factors change with the process of intervertebral osseointegration and so on. Thus, investigations are still needed to improve the comprehension of cervical interbody fusion cage biomechanically.

Structural damage induces extensive parameter changes of an aircraft, which leads to the mismatch problem between the offline model and a flying aircraft. Due to extensive parameter changes, motion of a damaged aircraft is difficultly described with a mathematical model. This article uses disturbances in accelerations and angular accelerations to quantify the effects of extensive parameter changes, and derives a mathematical model for a damaged aircraft. Provided that the flight controller of a damaged aircraft has a fixed structure, the mismatch problem may cause the aircraft unstable. Based on the proposed mathematical model, this article proposed a reconfigurable nonlinear dynamic inversion (RNDI) controller for attitude control of a structurally damaged aircraft, which synthesizes a nonlinear disturbance observer (NDO) with a modified nonlinear dynamic inversion (NDI) controller. The NDO is explored to estimate the disturbances in angular accelerations. Afterwards, the estimations are fed into the modified NDI controller realizes control structure reconfiguration. Conventional NDI control law and model reference adaptive control (MRAC) law are compared, and simulation results demonstrate that the proposed RNDI control law is robust to structural damage and possesses satisfactory control performance.

The Xinjiang is an important coal production base in China and also a serious coal fire disaster area. Coal fires not only waste resources, but also cause air pollution and damage to the ecological environment. Hence, it is very important to identify and monitor the underground coal fire areas accurately and efficiently for the control of coal fires. Interferometric synthetic aperture radar (InSAR) technology identifies and monitors coal fire areas by monitoring surface subsidence caused by burned out area. Compared with traditional coal fire monitoring technology, InSAR technology has the advantages of all-weather and high efficiency. But the fire areas are often distributed in wild areas, this factor significantly limits the application of the traditional Persistent Scatterer interferometry (PSI) technology. In addition, Xinjiang coal fires are mostly located in historical goafs, so it is necessary to distinguish the subsidence caused by mining and coal fires. Therefore, distributed scatterer interferometry (DSI) technology is used to monitor the Miquan fire area in Xinjiang in this paper. The results show that compared with PSI technology, DSI technology can expand the number of effective monitoring points 124 times. On this basis, spatio-temporal analysis of surface subsidence in the study area suggests that the subsidence caused by mining and coal fires exhibits significantly different space-time evolution rules. Therefore, in the future, the coal fire area and mining area can be separated and identified according to these rules. The final identified coal fire area contains all measured coal fire points, and accurately monitors the fire extinguishing area.

Abstract The dielectric properties of an active KTaO3 hybrid metamaterial structure and its tunability under external electric fields are investigated at room temperature by means of terahertz time-domain spectroscopy. Application of the electric field leads to an appreciable tuning of the dielectric loss, which is up to 17%. Meanwhile, the refractive index also changes appreciably. These findings are attributed to the internal space charge field in the crystal caused by the excited free carriers.

Underground coal fires have become a worldwide disaster, which brings serious environmental pollution and massive energy waste. Xinjiang is one of the regions that is seriously affected by the underground coal fires. After years of extinguishing, the underground coal fire areas in Xinjiang have not been significantly reduced yet. To extinguish underground coal fires, it is critical to identify and monitor them. Recently, remote sensing technologies have been showing great potential in coal fires’ identification and monitoring. The thermal infrared technology is usually used to detect thermal anomalies in coal fire areas, and the Differential Synthetic Aperture Radar Interferometry (DInSAR) technology for the detection of coal fires related to ground subsidence. However, non-coal fire thermal anomalies caused by ground objects with low specific heat capacity, and surface subsidence caused by mining and crustal activities have seriously affected the detection accuracy of coal fire areas. To improve coal fires’ detection accuracy by using remote sensing technologies, this study firstly obtains temperature, normalized difference vegetation index (NDVI), and subsidence information based on Landsat8 and Sentinel-1 data, respectively. Then, a multi-source information strength and weakness constraint method (SWCM) is proposed for coal fire identification and analysis. The results show that the proposed SWCM has the highest coal fire identification accuracy among the employed methods. Moreover, it can significantly reduce the commission and omission error caused by non-coal fire-related thermal anomalies and subsidence. Specifically, the commission error is reduced by 70.4% on average, and the omission error is reduced by 30.6%. Based on the results, the spatio-temporal change characteristics of the coal fire areas have been obtained. In addition, it is found that there is a significant negative correlation between the time-series temperature and the subsidence rate of the coal fire areas (R2 reaches 0.82), which indicates the feasibility of using both temperature and subsidence to identify and monitor underground coal fires.

In this paper, combined with experiments and theoretical calculations, the effect of urban low-calorific value sludge on the slagging characteristics of easy-slagging coals is studied. The results show that when the melting point of sludge ash is lower than that of coal ash, the ash melting point of the mixture after the two blends will be lower than the melting point of raw coal ash. When SiO2 and Al2O3, which are relatively high in sludge, are used as single additives, the ash melting point of coal will first decrease and then increase. As the mixing ratio of sludge increases, coal ash slagging characteristics show a trend of gradual relief. For coals that are prone to slagging and rich in alkali metals, they can be appropriately mixed with sludge rich in silicon and aluminum compounds or additives to improve Slagging characteristics.

Dipeptidyl peptidase 4 (DPP4) is recognised as an attractive anti-diabetic drug target, and several DPP4 inhibitors are already on the market. As members of the same gene family, dipeptidyl peptidase 8 (DPP8) and dipeptidyl peptidase 9 (DPP9) share high sequence and structural homology as well as functional activity with DPP4. However, the inhibition of their activities was reported to cause severe toxicities. Thus, the development of DPP4 inhibitors that do not have DPP8 and DPP9 inhibitory activity is critical for safe anti-diabetic therapy. To achieve this goal, we established a selective evaluation method for DPP4 inhibitors based on recombinant human DPP8 and DPP9 proteins expressed by Rosetta cells. In this method, we used purified recombinant 120 kDa DPP8 or DPP9 protein from the Rosetta expression system. The optimum concentrations of the recombinant DPP8 and DPP9 proteins were 30 ng/mL and 20 ng/mL, respectively, and the corresponding concentrations of their substrates were both 0.2 mmol/L. This method was highly reproducible and reliable for the evaluation of the DPP8 and DPP9 selectivity for DPP4 inhibitor candidates, which would provide valuable guidance in the development of safe DPP4 inhibitors.

Although arsenite [As(III)] is non-essential and toxic for plants, it is effectively absorbed through various transporters into the roots. Here we identified a calcium-dependent protein kinase (CPK31) response for As(III) tolerance in Arabidopsis. We identified CPK31 as an interacting protein of a nodulin 26-like intrinsic protein (NIP1;1), an aquaporin involved in As(III) uptake. Similarly to the nip1;1 mutants, the loss-of-function mutants of CPK31 improved the tolerance against As(III) but not As(V), and accumulated less As(III) in roots than that of the wild-type plants. The promoter-β-glucuronidase and quantitative Real-Time PCR analysis revealed that CPK31 displayed overlapping expression profiles with NIP1;1 in the roots, suggesting that they might function together in roots. Indeed, the cpk31 nip1;1 double mutants exhibited stronger As(III) tolerance than cpk31 mutants, but similar to nip1;1 mutants, supporting the idea that CPK31 might serve as an upstream regulator of NIP1;1. Furthermore, transient CPK31 overexpression induced by dexamethasone caused the decrease in As(III) tolerance of transgenic Arabidopsis lines. These findings reveal that CPK31 is a key factor in As(III) response in plants.