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The development of oil and gas fields involves a typical multiphase percolation process. Over time, techniques such as injection, gas flooding, chemical flooding, and fracturing can cause mineral and sand particles in the original reservoir throat to gradually loosen and fall off. This particle loosening can adversely affect reservoir exploitation and reduce recovery efficiency. Therefore, studying the migration and flow field of suspended particles within porous media is considerable. However, current studies mainly address how particle migration and retention affect permeability and often overlook the dynamics of particle migration and their impact on flow fields within pore networks. The microscopic visualization model and microparticle image velocimetry (Mirco-PIV) technology were used to analyze particle retention and flow field changes in the main channel and boundary region of the two-dimensional porous glass model, and the laws were summarized. Results show that while initial flow velocity is higher in the main channel, particle retention in the main channel is more pronounced than that in the boundary region. Continuous particle injection reduces the flow velocity in the main channel, disturbing the original flow field and creating a “spot” flow field. Eventually, the main channel experiences a lower flow rate in the medium term than the boundary region, indicating that particles are transported more efficiently in high-flow zones. Retention mainly occurs near side walls, with high concentrations, leading to aggregation in the main channel, effectively plugging pores. Previous studies did not account for retention, aggregation, and interweaving. To our knowledge, this paper provides new insights into the interaction between particles and flow fields, offering direct visual evidence for two-dimensional conditions. As particles are injected, high flow rates transport a larger number of particles, increasing the possibility of retention and subsequently decreasing flow rates. This illustrates the interaction mechanism between particles and flow fields over time and space. Regarding flow velocity, the trends in the main channel and boundary region are inconsistent. As particles are continuously injected, the trunk road of the main channel changes, whereas the boundary region remains unaffected. In addition, particle distribution characteristics show that the core mechanism of blockage involves retention near the side wall, a reduction in the effective flow radius, and high concentration areas in the main channel. Current theories do not adequately address these issues and should be revised accordingly. The study used a combination of microscopy and micro-PIV to explore the retention and flow field of suspended particles in porous media, uncovering critical variations in these processes.

In order to solve the problem of difficulty in learning semantic pattern representations between user dynamic interest sequences using path based and knowledge graph based entity embedding methods, the author proposes research on spatiotemporal data modeling and prediction algorithms in intelligent management systems. The author first makes a preliminary analysis of the wireless network data (mainly the data of cellular mobile networks) obtained by Internet service providers, reveals that the data of adjacent base stations have temporal and spatial correlations, then establishes a hybrid deep learning model for spatio-temporal prediction, and proposes a new spatial model training algorithm. Finally, experiments were conducted using wireless network datasets to evaluate the performance of the model. The experimental results show that based on data analysis, it can be seen that the prediction of the system has effectively improved by 99 %. Conclusion: The spatiotemporal data modeling and prediction algorithm proposed by the author in the intelligent management system significantly improves prediction accuracy.

Sepsis, a life-threatening syndrome of organ damage resulting from dysregulated inflammatory response, is distinguished by overexpression of inflammatory cytokines, excessive generation of reactive oxygen/nitrogen species (RONS), heightened activation of pyroptosis, and suppression of autophagy. However, current clinical symptomatic supportive treatment has failed to reduce the high mortality. Herein, we developed self-assembled multifunctional carbon monoxide nanogenerators (Nano CO), as sepsis drug candidates, which can release CO in response to ROS, resulting in clearing bacteria and activating the heme oxygenase-1/CO system. This activation strengthened endogenous protection and scavenged multiple inflammatory mediators to alleviate the cytokine storm, including scavenging RONS and cfDNA, inhibiting macrophage activation, blocking pyroptosis and activating autophagy. Animal experiments show that Nano CO has a good therapeutic effect on mice with LPS-induced sepsis, which is manifested in hypothermia recovery, organ damage repair, and a 50% decrease in mortality rates. Taken together, these results illustrated the efficacy of multifunctional Nano CO to target clearance of multiple mediators in sepsis treatment and act against other refractory inflammation-related diseases.

Abstract The single transmitter and multiple receivers (STMR) mobile radar system is a special distributed radar system, which has stronger detection and survival capabilities. However, the high‐speed movement of the radar platforms easily produce the across‐range cell migration (RCM) of radar echo signal, which cause envelope shift effects within the coherent processing interval. Here, a motion compensation method for the STMR mobile radar system in the sea environment, to solve the problem of RCM is proposed. First, the target points and clutter points with the same Doppler velocity are obtained by the radon Fourier transform method. Second, using the range/Doppler difference between clutter and target under multi‐radar views, the target and clutter points are separated by the spatial range mapping. The simulation results show that the method can effectively improve the coherent accumulation effect of the target in the sea environment with low signal‐to‐clutter ratio (SCR).

BackgroundDepression is a significant risk factor affecting the mental health of older adults. In the context of accelerated population aging and the policy of “delayed retirement,” self-employment has become an important alternative for older adults. Thus, studying the difference in depression levels between self-employed older adults and retirees, along with the mechanisms behind these differences, has emerged as a crucial theoretical and practical issue.MethodsThis research, based on panel data from the China Health and Retirement Longitudinal Study for the years 2011, 2013, 2015, and 2018, employed fixed-effect, instrumental variable, mediation models to analyze the difference in depression levels between self-employed older adults and retirees, as well as the mediating mechanisms involved.ResultsThe findings indicate that self-employed older adults have lower levels of depression than retirees. The results of the mediating mechanism analysis suggest that self-employment can indirectly lower the depression levels of older adults by frequent social participation and greater life satisfaction. However, heterogeneity analysis revealed significant urban–rural differences and different types of self-employment in the impact of self-employment on the depression levels of older adults.ConclusionsThe results of this study are of great significance for enhancing the mental health of older adults and provide empirical support for China and other developing countries in formulating more effective aging policies and building a more beneficial aging society.

Abstract This article introduces a high‐precision SAR echo simulation method aimed at providing a large‐scale SAR echo simulation algorithm that includes complex target information. This method independently simulates targets and ground clutter, calculating the shadow areas of targets and the dihedral effects between targets and the ground by constructing virtual rough surfaces and using ray tracing. Furthermore, this method can provide data sources for algorithms that improve detector performance using shadow or specular reflection characteristics. Finally, after comparing the simulation results with the publicly available MSTAR dataset, the experimental results show that this method ensures the accuracy of the results. This research provides a rich data source for the study of SAR detection and tracking algorithms and offers strong support for practical applications.

Abstract Reactive oxygen species (ROS) has emerged as potent therapeutic agents for biofilm-associated bacterial infections. Chemodynamic therapy (CDT), involving the generation of high-energy ROS, displays great potential in the therapy of bacterial infections. However, challenges such as insufficient hydrogen peroxide (H2O2) and over-expressed glutathione (GSH) levels within the microenvironment of bacterial biofilms severely limit the antibacterial efficacy of CDT. Herein, we have developed a multifunctional nanoplatform (CuS@CaO2@Dex) by integrating copper sulfide (CuS) and calcium peroxide (CaO2) into dextran (Dex)-coated nanoparticles. This innovative platform enhanced ROS generation for highly efficient biofilm elimination by simultaneously supplying H2O2 and depleting GSH. The Dex-coating facilitated the penetrability of CuS@CaO2@Dex into biofilms, while CaO2 generated a substantial amount of H2O2 in the acidic biofilm microenvironment. CuS, through a Fenton-like reaction, catalyzed the conversion of self-supplied H2O2 into hydroxyl radicals (•OH) and consumed the overexpressed GSH. Additionally, the incorporation of near-infrared II (NIR II) laser irradiation enhanced the photothermal properties of CuS, improving the catalytic efficiency of the Fenton-like reaction for enhanced antibacterial effects. In vivo experiments have demonstrated that CuS@CaO2@Dex exhibited remarkable antibacterial and antibiofilm efficacy, exceptional wound healing capabilities, and notable biosafety. In summary, the Dex-coated nanoplatform proposed in this study, with its self-sterilization capability through ROS, holds significant potential for future biomedical applications.

Horizontal well, dissolver, nitrogen, and steam (HDNS) combined flooding is mainly applied to shallow and thin heavy oil reservoirs to enhance oil recovery. Due to the lack of pore-scale mechanism studies, it is impossible to clarify the oil displacement mechanism of each slug in the process combination and the influence of their interaction on enhanced oil recovery (EOR). Therefore, in this study, HDNS combined flooding technology was simulated in a two-dimensional visualization microscopic model, and three viscosity reducer systems and multi-cycle combined flooding processes were considered. In combination with an emulsification and viscosity reduction experiment, two-dimensional microscopic multiphase seepage experiments were carried out to compare the dynamic seepage law and microscopic occurrence state of multiphase fluids in different systems. The results showed that the ability of three viscosity reducers to improve viscosity reduction efficiency in HDNS combined flooding was A > B > C, and their contributions to the recovery reached 65%, 41%, and 30%, respectively. In the system where a high viscosity reduction efficiency was shown by the viscosity reducer, the enhancements of both sweeping efficiency and displacement efficiency were primarily influenced by the viscosity reducer flooding. Steam flooding collaborated to improve displacement efficiency. The thermal insulation characteristics of N2 flooding may not provide a gain effect. In the system where a low viscosity reduction efficiency was shown by the viscosity reducer, the steam flooding was more important, contributing to 57% of the sweeping efficiency. Nitrogen was helpful for expanding the sweep area of the subsequent steam and viscosity reducer, and the gain effect of the thermal insulation steam chamber significantly improved the displacement efficiency of the subsequent steam flooding by 25%. The interaction of each slug in HDNS combined flooding resulted in the additive effect of increasing production. In actual production, it is necessary to optimize the process and screen the viscosity reducer according to the actual conditions of the reservoir and the characteristics of different viscosity reducers.

The corner reflector is an effective means of interference for radar seekers due to its high jamming intensity, wide frequency band, and combat effectiveness ratio. Properly arranging multiple corner reflectors in an array can form dilution jamming that resembles ships, substantially enhancing the interference effect. This results in a significant decline in the precision attack efficiency of radar seekers. Hence, it is critical to accurately identify corner reflector array. The common recognition methods involve extracting features on the high-resolution range profile (HRRP) and polarization domain. However, the former is constrained by the number of corner reflectors, while the latter is affected by the accuracy of polarization measurement, both of which have limited performance on the identification of corner reflector array. In terms of the evident variations in physical structures, there must be differences in their scattering characteristics. To highlight the differences, this paper proposes a new method based on the concept of mismatched filtering, which involves changing the frequency modulation slope of the chirp signal in the filter. Then, the variance of width and intervals within a specific scope are extracted as features to characterize these differences, and an identification process is designed in combination with the support vector machine. The simulation experiments demonstrate that the proposed method exhibits stable discriminative performance and can effectively combat dilution jamming. Its accuracy rate exceeds 0.86 when the signal-to-noise ratio is greater than 0 dB. Compared to the HRRP methods, the recognition accuracy of the proposed algorithm improves 15% in relation to variations in the quantity of corner reflectors.

In the field of radar target detection, the conventional approach is to employ the range profile energy accumulation method for detecting extended targets. However, this method becomes ineffective when dealing with non-stationary and non-uniform radar clutter scenarios, as well as long-distance targets with weak radar cross sections (RCSs). In such cases, the signal-to-noise ratio (SNR) of the target echo is severely degraded, rendering the energy accumulation detection algorithm unreliable. To address this issue, this paper presents a new extended target detection method based on the maximum eigenvalue of the Hermitian matrix. This method utilizes a detection model that incorporates observed data and employs the likelihood ratio test (LRT) theory to derive the maximum eigenvalue detector at low SNR. Specifically, the detector constructs a matrix using a sliding window block with the available data and then computes the maximum eigenvalue of the covariance matrix. Subsequently, the maximum eigenvalue matrix is transformed into a one-dimensional eigenvalue image, enabling extended target detection through analogy with the energy accumulation detection method. Furthermore, this paper analyzes the proposed extended target detection method from both theoretical and experimental perspectives, validating it through field-measured data. The results obtained from the measured data demonstrate that the method effectively enhances the SNR in low SNR conditions, thereby improving target detection performance. Additionally, the method exhibits robustness across different scattering center targets.

Abstract Based on random finite set, the probability hypothesis density (PHD) filter and the cardinalized PHD (CPHD) filter have been proposed for multitarget tracking as they are computational tractable. But the classical PHD and CPHD filter is not applicable when a target generates multiple detections. The general PHD filter was proposed to apply the PHD filter to arbitrary clutter and target measurement process. However, as a filter with better performance than the PHD filter, the CPHD filter for multiple-detection tracking is not proposed except the extended target CPHD filter and the multisensor CPHD filter. In our work, the general CPHD filter, which allows the clutter process and target measurement process to be arbitrary and performs better than the general PHD filter, is proposed. The proposed general CPHD filter is the general form of all kinds of CPHD filters, as well as all kinds of PHD filters and Bernoulli filters. In the simulation, the multiple-detection model of the over-the-horizon radar is used to demonstrate the tracking performance. The simulation results show that the proposed filter improves the accuracy of the state estimates and reduces the variance of the estimated number of targets.

Multi element compound-specific stable isotope analysis (ME-CSIA) is a tool to assess (bio)chemical reactions of molecules in the environment based on their isotopic fingerprints. To that effect, ME-CSIA concepts are initially developed with laboratory model experiments to determine the isotope fractionation factors specific for distinct (bio)chemical reactions. Here, we determined for the first time the carbon and hydrogen isotope fractionation factors for the monooxygenation of the short-chain alkanes ethane, propane, and butane. As model organism we used Thauera butanivorans strain Bu-B1211 which employs a non-haem iron monooxygenase (butane monooxygenase) to activate alkanes. Monooxygenation of alkanes was associated with strong carbon and hydrogen isotope effects: εbulkC = −2.95 ± 0.5 ‰ for ethane, −2.68 ± 0.1 ‰ for propane, −1.19 ± 0.18 ‰ for butane; εbulkH = −56.3 ± 15 ‰ for ethane, −40.5 ± 2.3 ‰ for propane, −14.6 ± 3.6 ‰ for butane. This resulted in lambda (Λ ≈ εHbulk/εCbulk) values of 16.2 ± 3.7 for ethane, 13.2 ± 0.7 for propane, and 11.4 ± 2.8 for butane. The results show that ME-CSIA can be used to track the occurrence and impact of monooxygenase-dependent aerobic processes converting short-chain alkanes in natural settings like marine and terrestrial seeps, gas reservoirs, and other geological formations impacted by natural gas.

Abstract The likelihood ratio function of the target plays a crucial role in applications such as tracking before detection (TBD). In the framework of random finite sets, the performance of radar target TBD based on particle filters is limited by the performance of the likelihood ratio function. Traditional likelihood ratio functions only consider the likelihood ratio between the target and background noise, thus requiring a high signal‐to‐noise (SNR) ratio for the input signal. In scenarios where the observation time interval is extremely short, there exists a strong autocorrelation between the complex amplitudes of the radar target at different time instants. Based on this characteristic, an autoregressive model is utilized to establish the autocorrelation of the target complex amplitudes and update the target's complex amplitudes using a Kalman filter. The likelihood ratio is derived from the model and it is compared with the traditional likelihood ratio under pulse‐Doppler radar. This comparison aims to demonstrate the effectiveness of the proposed likelihood ratio. Due to the fact that this likelihood ratio only requires the extraction of the complex amplitudes of the target scattering centre, without the need to extract the energy around the scattering centre like traditional point spread function methods, the algorithm complexity is greatly reduced, enabling real‐time operation of the proposed method.

Abstract Building a novel and efficient photothermal antibacterial nanoplatform is a promising strategy for precise bacterial elimination. Herein, a nanocomposite NiO NPs@AuNPs@Van (NAV) for selective MRSA removal was constructed by electrostatic self-assembly of highly photothermal magnetic NiO NPs and vancomycin (Van)-modified gold nanoparticles (AuNPs). In the presence of MRSA and under NIR irradiation, Van-mediated AuNPs can self-aggregate on MRSA surface, generating photothermal effect in situ and killing 99.6% MRSA in conjunction with magnetic NiO NPs. Additionally, the photothermal efficiency can be improved by magnetic enrichment due to the excellent magnetism of NAV, thereby enhancing the bactericidal effect at a lower experimental dose. In vitro antibacterial experiments and full-thickness skin wound healing test demonstrated that this combination therapy could effectively accelerate wound healing in MRSA-infected mice, increase collagen coverage, reduce IL-6 and TNF-α content, and upregulate VEGF expression. Biological safety experiments confirmed that NAV has good biocompatibility in vivo and in vitro. Overall, this work reveals a new type of nanocomposite with enhanced photothermal antibacterial activity as a potential nano-antibacterial agent for treating bacteria-infected wounds.

The molecular mechanisms of Rhizoma Chuanxiong (Chuanxiong, CX) and Rhei Radix et Rhizoma (Dahuang, DH) in treating acute kidney injury (AKI) and subsequent renal fibrosis (RF) were investigated in this study by applying network pharmacology and experimental validation. The results showed that aloe-emodin, (−)-catechin, beta-sitosterol, and folic acid were the core active ingredients, and TP53, AKT1, CSF1R, and TGFBR1 were the core target genes. Enrichment analyses showed that the key signaling pathways were the MAPK and IL-17 signaling pathways. In vivo experiments confirmed that Chuanxiong and Dahuang pretreatments significantly inhibited the levels of SCr, BUN, UNAG, and UGGT in contrast media-induced acute kidney injury (CIAKI) rats (p < 0.001). The results of Western blotting showed that compared with the control group, the protein levels of p-p38/p38 MAPK, p53, and Bax in the contrast media-induced acute kidney injury group were significantly increased, and the levels of Bcl-2 were significantly reduced (p < 0.001). Chuanxiong and Dahuang interventions significantly reversed the expression levels of these proteins (p < 0.01). The localization and quantification of p-p53 expression in immunohistochemistry technology also support the aforementioned results. In conclusion, our data also suggest that Chuanxiong and Dahuang may inhibit tubular epithelial cell apoptosis and improve acute kidney injury and renal fibrosis by inhibiting p38 MAPK/p53 signaling.

Drug-induced acute kidney injury (DI-AKI) is one of the leading causes of kidney injury, is associated with high mortality and morbidity, and limits the clinical use of certain therapeutic or diagnostic agents, such as antineoplastic drugs, antibiotics, immunosuppressants, non-steroidal anti-inflammatory drugs, and contrast media. In recent years, numerous studies have shown that many Chinese meteria medica, metabolites derived from botanical drugs, and Chinese medicinal formulas confer protective effects against DI-AKI by targeting a variety of cellular or molecular mechanisms, such as oxidative stress, inflammatory, cell necrosis, apoptosis, and autophagy. This review summarizes the research status of common DI-AKI with Chinese meteria medica interventions, including cisplatin, gentamicin, contrast agents, methotrexate, and acetaminophen. At the same time, this review introduces the metabolites with application prospects represented by ginseng saponins, tetramethylpyrazine, panax notoginseng saponins, and curcumin. Overall, this review provides a reference for the development of promising nephroprotectants.

Abstract Background The study of symbiotic nitrogen fixation between (SNF) legumes and rhizobia has always been a hot frontier in scientific research. Nanotechnology provides a new strategy for biological nitrogen fixation research. However, how to construct abiotic nano-structure-biological system, using the special properties of nanomaterials, to realize the self-enhancement of biological nitrogen fixation capacity is important. Results In order to construct a more efficient SNF system, in this study, we applied manganese ferrite nanoparticles (MF-NPs) with sustainable diatomic catalysis to produce reactive oxygen species (ROS), thus regulating the nodulation pathway and increasing the number of nodules in soybean (Glycine max), eventually enhancing symbiotic nitrogen fixation. Symbiosis cultivation of MF-NPs and soybean plants resulted in 50.85% and 61.4% increase in nodule weight and number, respectively, thus inducing a 151.36% nitrogen fixation efficiency increase, finally leading to a 25.70% biomass accumulation increase despite no substantial effect on the nitrogenase activity per unit. Transcriptome sequencing analysis showed that of 36 differentially expressed genes (DEGs), 31 DEGs related to soybean nodulation were upregulated in late rhizobium inoculation stage (12 d), indicating that the increase of nodules was derived from nodule-related genes (Nod-R) continuous inductions by MF-NPs. Conclusions Our results indicated that the nodule number could be effectively increased by extending the nodulation period without threatening the vegetative growth of plants or triggering the autoregulation of nodulation (AON) pathway. This study provides an effective strategy for induction of super-conventional nodulation. Graphical Abstract

Understanding the mechanical properties of rock is of great significance for the development of unconventional reservoirs. However, a large number of bedding makes the mechanical laws of rock unclear. To investigate the effect of bedding properties on the uniaxial mechanical properties of rock, the coal model containing bedding is developed based on the continuous–discontinuous method, and the effect of bedding angle, bedding strength, bedding number, and loading rate on the uniaxial mechanical properties of rock is investigated. The failure morphology, stress–strain evolution, peak stress, and fracture degrees are analyzed and discussed in detail. The reliability of the numerical model in this paper has been verified by comparison with the indoor experiments. The results show that when the bedding angle is 0°, the peak stress of the rock is maximum, 8.16 MPa, and when the bedding angle is 90°, the fracture degree of the rock is maximum, 3.74%. For the different bedding strengths, the peak stress first decreases linearly with the decrease of the bedding strength. The peak stress barely varies when the bedding strength is less than 0.5 MPa. The fracture degree of the rock shows a nonlinear increase with the increase in bedding strength. For different bedding numbers, the activation of the bedding is not related to the bedding number. The loading speed also has a great influence on the mechanical properties of rock. With the increase in loading rate, the difficulty of bedding activation gradually increases, and the complexity of fractures gradually increases. This study aims to further improve the understanding of the effect of bedding properties on the uniaxial mechanical properties of rock.

Performance evaluation of microorganisms that have emulsifying and degrading effects on crude oil has been extensively conducted in the laboratory. However, the ultimate goal of microbial enhanced oil recovery is field application, so the pilot simulation experiments are crucial. In this study, a micro-visualization model and the real cores were chosen to investigate the actual recovery efficiency and the mechanism of the consortium bacteria B-ALL, which has been proven to have good emulsification and degradation effects in lab studies in porous media. At the same time, the cast thin sections and rate-controlled porosimetry were combined to analyze the pore throat structure of the displacement core. It was found that the recovery efficiency was positively correlated with the microbial injection volume as well as the incubation time. For the microscopic model with high pores and high permeability, the efficiency of secondary water flooding can be increased by 44.77% after six days of incubation with two pore volume microbes. For the real tight cores, the maximum secondary water flooding efficiency under the same condition was 6.98%. Through visual modeling, microorganisms increase the oil washing efficiency mainly by emulsification and changing the wettability. The generated oil droplets will play a role in plugging and improving the wave efficiency. However, tight reservoirs have the characteristics of large pores and small throats, and curved and necking throats are developed, greatly reducing permeability. The microbial recovery efficiency was lower under shorter cultivation times. This study provides a practical basis for the application of consortium bacteria in tight oil fields to enhance recovery.

During microbial-enhanced oil recovery (MEOR), surfactant-producing microorganisms are reported to improve displacement efficiency. However, the sweep efficiency could be improved by emulsified droplets or be reduced by low-IFT (interfacial tension)-induced fingering flow. Therefore, whether sweep efficiency can be improved by surfactant-producing microorganisms is currently unclear. To reveal the EOR mechanisms by surfactant-producing microorganisms, a 2D micro-model was used to conduct a long-term pore-scale experiment. In the results, 19.4% of the original oil in place (OOIP) was recovered, and surfactant-producing microorganisms can improve not only displacement efficiency (16.9% of the OOIP in the main stream) but also sweep efficiency (27.7% of the OOIP in the margin). Furthermore, the sweep efficiency was improved during flooding and shut-in periods. For instance, 19.5% of the OOIP in margins migrated to the main stream during the 1st shut-in period. Regarding mechanisms of sweep, it was improved by Jamin’s effect during the flooding period, while during the shut-in period, the oil migration was attributed to the spontaneously spreading biomass and their wettability altering the biosurfactant. This long-term experiment revealed that the dominant oil recovery mechanisms were altering with declining oil saturation, based on which sweep efficiency contributed to oil recovery only at oil saturation higher than 40.5%. While at lower oil saturation, only displacement efficiency could be improved.

This article presents a high-precision airborne video synthetic aperture radar (SAR) raw echo simulation method aimed at addressing the issue of simulation accuracy in video SAR image generation. The proposed method employs separate techniques for simulating targets and ground clutter, utilizing pre-existing SAR images for clutter simulation and employing the shooting and bouncing rays (SBR) approach to generate target echoes. Additionally, the method accounts for target-generated shadows to enhance the realism of the simulation results. The fast simulation algorithm is implemented using the C++ programming language and the Accelerated Massive Parallelism (AMP) framework, providing a fusion technique for integrating clutter and target simulations. By combining the two types of simulated data to form the final SAR image, the method achieves efficient and accurate simulation technology. Experimental results demonstrate that this method not only improves computational speed but also ensures the accuracy and stability of the simulation outcomes. This research holds significant implications for the development of algorithms pertaining to video SAR target detection and tracking, providing robust support for practical applications.

Drug-resistant bacteria and infectious diseases associated with biofilms pose a significant global health threat. The integration and advancement of nanotechnology in antibacterial research offer a promising avenue to combat bacterial resistance. Nanomaterials possess numerous advantages, such as customizable designs, adjustable shapes and sizes, and the ability to synergistically utilize multiple active components, allowing for precise targeting based on specific microenvironmental variations. They serve as a promising alternative to antibiotics with diverse medical applications. Here, we discuss the formation of bacterial resistance and antibacterial strategies, and focuses on utilizing the distinctive physicochemical properties of nanomaterials to achieve inherent antibacterial effects by investigating the mechanisms of bacterial resistance. Additionally, we discuss the advancements in developing intelligent nanoscale antibacterial agents that exhibit responsiveness to both endogenous and exogenous responsive stimuli. These nanomaterials hold potential for enhanced antibacterial efficacy by utilizing stimuli such as pH, temperature, light, or ultrasound. Finally, we provide a comprehensive outlook on the existing challenges and future clinical prospects, offering valuable insights for the development of safer and more effective antibacterial nanomaterials.

Abstract A simple fabrication of end-bonded contacts InAsSb NW (nanowire) array detector to weak light is demonstrated in this study. The detector is fabricated using InAsSb NW array grown by molecular beam epitaxy on GaAs substrate. The metal-induced gap states are induced by the end-bonded contact which suppresses the dark current at various temperatures. The existence of the interface dipole due to the interfacial gap states enhances the light excitation around the local field and thus upgrades the photoresponsivity and photodetectivity to the weak light. The light intensity of the infrared light source in this report is 14 nW/cm2 which is about 3 to 4 orders of magnitude less than the laser source. The responsivity of the detector has reached 28.57 A/W at room temperature with the light (945 nm) radiation, while the detectivity is 4.81 × 1011 cm·Hz1/2 W−1. Anomalous temperature-dependent performance emerges at the variable temperature experiments, and we discussed the detailed mechanism behind the nonlinear relationship between the photoresponse of the device and temperatures. Besides, the optoelectronic characteristics of the detector clarified that the light-trapping effect and photogating effect of the NWs can enhance the photoresponse to the weak light across ultraviolet to near-infrared. These results highlight the feasibility of the InAsSb NW array detector to the infrared weak light without a cooling system.

In this paper, based on the gneiss outcrop of Bozhong 196 gas field in China, uniaxial compression and Brazil splitting tests were conducted by using cores of different orientations. The following compression properties were studied: the elastic compression modulus, Poisson’s ratio and compressive strength of the gneiss outcrop. The following tensile properties were studied: the tensile modulus, the tensile strength and peak energy rate of gneiss outcrop. The results demonstrate the following: (1) The elastic compression modulus, compressive strength, tensile strength and peak energy rate of gneiss specimens with horizontal core-taking are greater than those with vertical core-taking. (2) The elastic compression modulus, Poisson’s ratio and compressive strength of horizontally cored gneiss specimens are 29.688–45.760 GPa, 0.186–0.386, and 174.94–147.80 MPa, respectively; the elastic compression modulus, Poisson’s ratio and compressive strength of the vertical gneiss specimens are 26.541–32.602 GPa, 0.429–0.476 and 169.37–134.46 MPa. (3) The tensile modulus of the horizontal gneiss specimens is 4.93–5.98 GPa. The tensile modulus of the vertical gneiss specimens is 0.96–2.11 GPa. The tensile modulus of the horizontal gneiss specimens is five times that of the vertical gneiss specimens. The elastic compression modulus of gneiss is 5–20 times that of the tensile modulus. (4) The tensile strength and peak energy rate of horizontally cored gneiss specimens are 14.33–17.55 MPa and 2598.67–4049.53 J/m2, respectively. The tensile strength of the vertical gneiss specimens is 6.12–9.65 MPa, and the peak energy rate is 715.74–1515.30 J/m2. (5) There is a good linear relationship between the peak energy rate and tensile strength of gneiss. The research results can provide a scientific and reasonable reference for in situ fracturing of Bozhong 196 gas field.

Spontaneous imbibition has been considered as a significant method to enhanced oil recovery (EOR) in unconventional reservoirs. The main impediment to comprehending the variation characteristics of spontaneous imbibition at different pore scales was the reservoir’s opacity. To this end, a series of spontaneous imbibition experiments of visualized oil-wet microtubes with six different diameters (10 μm~60 μm) were performed, as were the corresponding macroscopic core imbibition tests with six different permeabilities under the same conditions. The results showed that formation brine mostly advanced along the wall surface of a capillary during the imbibition process, and some were even isolated within a capillary. The imbibition recovery in the capillary with a diameter of 10 μm was the highest (27.81%), which was more than three times that of the capillary with a diameter of 60 μm (8.3%). There was a good power function decline relationship between capillary diameter and imbibition recovery, and 30 μm appeared to be a critical inflection point in both capillary tube and macroscopic core imbibition tests. In addition, the majority of the detained residual oil clusters not only cut off the continuity of formation brine but also increased the imbibition flow resistance, accelerating the imbibition to balance. This research provides a new perspective for comprehending the imbibition characteristics at different pore scales.

The cooperative imaging of the bistatic radar is an important research topic for missile-borne radar detection. The existing missile-borne radar detection system is mainly based on the target plot information separately extracted by each radar for data level fusion, without considering the gain brought by the cooperative processing of the radar target echo signal. In this paper, a random frequency-hopping waveform is designed for the bistatic radar to achieve efficient motion compensation. A coherent processing algorithm for bistatic echo signals is designed to achieve band fusion and improve the signal quality and range resolution of the radar. Simulation and high-frequency electromagnetic calculation data were used to verify the effectiveness of the proposed method.

Endogenous triggered delivery of antibiotics over an external triggered delivery has distinct advantages. Here, the authors report on a nanoreactor triggered by bacterial toxin to trigger a drug release mechanism and capture the toxin for reduced toxicity of toxins and improved immune response.

The rheology of a partially hydrolyzed polyacrylamide (HPAM) solution plays an important role in its oil recovery during polymer flooding. However, multiple factors in brine, such as sulfide ions, cause a dramatic loss in the viscosity and oil recovery. To better understand the sulfide-induced viscosity loss and the consequent flow mechanisms in pore networks, the morphology of polymer solutions with and without sulfide ion was observed by scanning electron microscopy; and the variations of the pore scale flow fields were demonstrated by a microscopic visualization seepage experiment combined with Micro-PIV (Microscale Particle Image Velocimetry). The results showed that, with the presence of sulfide ion, the microstructure of the polymer changed from a uniform three-dimensional network structure to loose and uneven floccules, which resulted in viscosity loss (over 70% with 5-mg/L sulfide ion). Moreover, higher concentrations of sulfide ions (5 mg/L and 10 mg/L) resulted in earlier shear thinning characteristics than those with lower sulfide concentrations. Due to viscosity loss, the average flow velocity in the main stream of the microscopic seepage experiment increased more significantly than that without sulfide. However, the viscosity loss alone cannot independently explain the severe viscous fingering during the subsequent post-water flooding, which was about five times greater than that of the primary water flooding in terms of the velocity ratio between the mainstream and margin. A further pore-scale flow field analysis exhibited an eccentric and a bimodal velocity distribution in the throat along the radial and axial directions, respectively. The former distribution indicated that the adsorbed polymer on the pore wall was broken through by hydraulic shear due to the collapsed structure caused by sulfide ion. The latter suggested that another sulfide-induced impact was an earlier-occurring non-Newtonian characteristic with a low shear rate. Therefore, instead of viscosity loss, elastic loss is the dominant mechanism affecting the characteristics of the aggregate flow field under the action of sulfide. Microscopic flooding combined with Micro-PIV is a feasible and essential method to reveal pore scale flow mechanisms.

In this paper, a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro pores–complex fracture networks–wellbore during the development of shale reservoirs by means of horizontal well fracturing. First, hydraulic fractures were induced by means of Brazilian splitting tests. Second, the forms of the hydraulic fractures inside the rock samples were observed by means of X-ray CT scanning to measure the opening of hydraulic fractures. Third, based on the multi-scale unified flowing model, morphological description of fractures and gas flowing mechanism in the matrix–complex fracture network–wellbore, the productivity equation of single-stage horizontal well fracturing which includes diffusion, slipping and desorption was established. And fourthly, a productivity prediction model of horizontal well multi-stage fracturing in the shale reservoir was established considering the interference between the multi-stage fracturing zones and the pressure drop in the horizontal wellbore. The following results were obtained. First, hydraulic fractures are in the form of a complex network. Second, the measured opening of hydraulic fractures is in the range of 4.25–453 μm, averaging 112 μm. Third, shale gas flowing in different shapes of fracture networks follows different nonlinear flowing laws. Forth, as the fracture density in the strongly stimulated zones rises and the distribution range of the hydraulic fractures in strongly/weakly stimulated zones enlarges, gas production increases gradually. As the interference occurs in the flowing zones of fracture networks between fractured sections, the increasing amplitude of gas production rates decreases. Fifth, when the length of a simulated horizontal well is 1500 m and the half length of a fracture network in the strongly stimulated zone is 100 m, the productivity effect of stage 10 fracturing is the best. Therefore, it is necessary to control fracturing degree reasonably and optimize fracturing parameters, so as to provide a theoretical support for the optimization design of shale gas reservoir fracturing. Keywords: Shale gas, Reservoir, Fracturing, Horizontal well, Complex fracture network, Multi-zone coupling, Multi-scale, Interference, Productivity capacity

Selecting the optimal reference satellite is an important component of high-precision relative positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision (PDOP) value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Multipath effect is the main factor of deteriorating target detection performance in low grazing angle scenario, which results from reflections on the ground/sea surface. Amplitudes of the received signals fluctuate acutely due to the random phase variations of reflected signals along different paths; thereby the performances of target detection and tracking are heavily influenced. This paper deals with target detection in low grazing angle scenario with orthogonal frequency division multiplexing (OFDM) radar. Realistic physical and statistical effects are incorporated into the multipath propagation model. By taking advantage of multipath propagation that provides spatial diversity of radar system and frequency diversity of OFDM waveform, we derive a detection method based on generalized likelihood ratio test (GLRT). Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. Simulation results show that the detection performance can be improved due to the multipath effect and adaptive OFDM waveform design.