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Aluminum nitride (AlN)-based ferroelectric films offer significant advantages, including compatibility with CMOS back-end processes, potential for sustainable miniaturization, and intrinsic stability in the ferroelectric phase. As promising emerging materials, they have attracted considerable attention for their broad application potential in nonvolatile ferroelectric memories. However, several key scientific and technological challenges remain, including the preparation of single-crystal materials, epitaxial growth, and doping, which hinder their progress in critical ferroelectric devices. To accelerate their development, further research is needed to elucidate the underlying physical mechanisms, such as growth dynamics and ferroelectric properties. This paper provides a comprehensive review of the preparation methods of AlN-based ferroelectric films, covering AlN, Al1−xScxN, Al1−xBxN, YxAl1−xN, and ScxAlyGa1−x−yN. We systematically analyze the similarities, differences, advantages, and limitations of various growth techniques. Furthermore, the ferroelectric properties of AlN and its doped variants are summarized and compared. Strategies for enhancing the ferroelectric performance of AlN-based films are discussed, with a focus on coercive field regulation under stress, suppression of leakage current, fatigue mechanism, and long-term stability. Then, a brief overview of the wide range of applications of AlN-based thin films in electronic and photonic devices is presented. Finally, the challenges associated with the commercialization of AlN-based ferroelectrics are presented, and critical issues for future research are outlined. By synthesizing insights on growth methods, ferroelectric properties, enhancement strategies, and applications, this review aims to facilitate the advancement and practical application of AlN-based ferroelectric materials and devices.

The remote sensing-based inversion of sound speed profile (SSP) enables the acquisition of high-spatial-resolution SSP without in situ measurements. The spatial division of the inversion grid is crucial for the accuracy of results, determining both the number of samples and the consistency of inversion relationships. The result of our research is the introduction of a physics-inspired self-organizing map (PISOM) that facilitates SSP inversion by clustering samples according to the physical perturbation law. The linear physical relationship between sea surface parameters and the SSP drives dimensionality reduction for the SOM, resulting in the clustering of samples exhibiting similar disturbance laws. Subsequently, samples within each cluster are generalized to construct the topology of the solution space for SSP reconstruction. The PISOM method significantly improves accuracy compared with the SOM method without clustering. The PISOM has an SSP reconstruction error of less than 2 m/s in 25% of cases, while the SOM method has none. The transmission loss calculation also shows promising results, with an error of only 0.5 dB at 30 km, 5.5 dB smaller than that of the SOM method. A physical interpretation of the neural network processing confirms that physics-inspired clustering can bring better precision gains than the previous spatial grid.

Nighttime light (NTL) remote sensing has emerged as a powerful tool in various fields such as urban expansion, socio-economic estimation, light pollution, and energy domains. However, current annual NTL products suffer from several critical limitations, including poor consistency, severe background noise, and limited comparability. These issues have significantly interfered with the research of long-term NTL trends and diminished the accuracy of related findings. Therefore, this study developed a de-difference smoothing algorithm for producing high-quality annual NTL products based on monthly National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. It enabled the construction of a continuous global high-quality NTL dataset, named the De-Difference Smoothed Nighttime Light (DDSNL), covering the period from 2012 to 2023. Comparative analyses were conducted to validate the accuracy and availability of the DDSNL product against the benchmark EOG NPP-VIIRS and NPP-VIIRS-like NTL datasets. The results showed that DDSNL products had strong correlation with the NTL distribution of EOG NPP-VIIRS, but little correlation with NPP-VIIRS-like. Notably, DDSNL demonstrated better background noise reduction and higher separability between NTL and non-NTL areas compared to EOG NPP-VIIRS NTL. In contrast to the complete exclusion of background in NPP-VIIRS-Like, the retention of background values in DDSNL leads to more reasonable representation in the urban fringes. In the analysis of NTL changes matching impervious surface changes, the DDSNL product demonstrated the least interference from noise, resulting in the smallest segmentation threshold and the highest matching accuracy. This indirectly demonstrates the spatial and temporal consistency of the annual DDSNL product, ensuring its reliability in change detection-related studies. The annual DDSNL product developed in this research exhibits high fidelity, strong consistency, and improved comparability, and can provide reliable data reference for applications in electrification and urban studies.

Finding the densest subgraph has tremendous potential in computer vision and social network research, among other domains. In computer vision, it can demonstrate essential structures, and in social network research, it aids in identifying closely associated communities. The densest subgraph problem is finding a subgraph with maximum mean density. However, most densest subgraph-finding algorithms are based on edge-weighted graphs, where edge weights can only represent a single value dimension, whereas practical applications involve multiple dimensions. To resolve the challenge, we propose two algorithms for resolving the densest subgraph problem in a vertex-weighted graph. First, we present an exact algorithm that builds upon Goldberg’s original algorithm. Through theoretical exploration and analysis, we rigorously verify our proposed algorithm’s correctness and confirm that it can efficiently run in polynomial time O(n(n + m)log2n) is its temporal complexity. Our approach can be applied to identify closely related subgroups demonstrating the maximum average density in real-life situations. Additionally, we consistently offer an approximation algorithm that guarantees an accurate approximation ratio of 2. In conclusion, our contributions enrich theoretical foundations for addressing the densest subgraph problem.

To model fuzzy numbers with the confidence degree and better account for information uncertainty, Zadeh came up with the notion of Z-numbers, which can effectively combine the objective information of things with subjective human interpretation of perceptive information, thereby improving the human comprehension of natural language. Although many numbers are in fact Z-numbers, their higher computational complexity often prevents their recognition as such. In order to reduce computational complexity, this paper reviews the development and research direction of Z-numbers and deduces the operational rules for symmetric triangular Z-numbers. We first transform them into classical fuzzy numbers. Using linear programming, the extension principle of Zadeh, the convolution formula, and fuzzy number algorithms, we determine the operational rules for the basic operations of symmetric triangular Z-numbers, which are number-multiplication, addition, subtraction, multiplication, power, and division. Our operational rules reduce the complexity of calculation, improve computational efficiency, and effectively reduce the information difference while being applicable to other complex operations. This paper innovatively combines Z-numbers with classical fuzzy numbers in Z-number operations, and as such represents a continuation and innovation of the research on the operational laws of Z-numbers.

In order to prepare biomass-derived carbon materials with high specific capacitance at a low activation temperature (≤700 °C), nanoporous carbon materials were prepared from zanthoxylum bungeanum peels and seeds via the pyrolysis and KOH-activation processes. The results show that the optimal activation temperatures are 700 °C and 600 °C for peels and seeds. Benefiting from the hierarchical pore structure (micropores, mesopores, and macropores), the abundant heteroatoms (N, S, and O) containing functional groups, and plentiful electrochemical active sites, the PAC-700 and SAC-600 derive the large capacities of ~211.0 and ~219.7 F g−1 at 1.0 A g−1 in 6 M KOH within the three-electrode configuration. Furthermore, the symmetrical supercapacitors display a high energy density of 22.9 and 22.4 Wh kg−1 at 7500 W kg−1 assembled with PAC-700 and SAC-600, along with exceptional capacitance retention of 99.1% and 93.4% over 10,000 cycles at 1.0 A g−1. More significantly, the contribution here will stimulate the extensive development of low-temperature activation processes and nanoporous carbon materials for electrochemical energy storage and beyond.

This paper takes a tunnel through a landslide in Northwest China as an example, constructs a mechanical model of a tunnel–landslide orthogonal system, and explores the deformation mechanism of a tunnel–landslide system and the technology of early warnings of near-slips. Given the problem that it is difficult to accurately monitor the deformation and damage characteristics of the tunnel–landslide system using conventional methods, FLAC3D was used to analyze the deformation mechanism of the tunnel–landslide orthogonal system and numerical simulation of the NPR constant resistance large deformation anchors for the early warning of near-slips. Based on the strength reduction method, by reducing the mechanical parameters of the shear strength of the slip zone and simulating different degrees of landslides, we obtained the change rules of the displacement and the axial force of the NPR constant-resistance large deformation anchor cable in the tunnel–landslide orthogonal system, established the warning mode of the Newtonian force tunnel–landslide orthogonal system, and successfully issued a near-slip warning in actual engineering applications. The above research is of great significance to the stability monitoring and risk assessment of tunnel–landslide systems.

The sea surface roughness parameterization and the universal stability function are key components of the evaporation duct prediction model based on the Monin–Obukhov similarity theory. They determine the model’s performance, which in turn affects the efficiency and accuracy of electromagnetic applications at sea. In this study, we collected layered meteorological and hydrological observation data and preprocessed them to obtain near-surface reference modified refractivity profiles. We then optimized the sea surface roughness parameterization and the universal stability function using particle swarm optimization and simulated annealing algorithms. The results show that the particle swarm optimization algorithm outperforms the simulated annealing algorithm. Compared to the original model, the particle swarm optimization algorithm improved the prediction accuracy of the model by 5.09% under stable conditions and by 9.97% under unstable conditions, demonstrating the feasibility of the proposed method for optimizing the evaporation duct prediction model. Subsequently, we compared the electromagnetic wave propagation path losses under two different evaporation duct heights and modified refractivity profile states, confirming that the modified refractivity profile is more suitable as the accuracy criterion for the evaporation duct prediction model.

The gas sensitivity of the W defect in WS2 (VW/WS2) to five toxic gases—HCHO, CH4, CH3HO, CH3OH, and CH3CH3—has been examined in this article. These five gases were adsorbed on the VW/WS2 surface, and the band, density of state (DOS), charge density difference (CDD), work function (W), current–voltage (I–V) characteristic, and sensitivity of adsorption systems were determined. Interestingly, for HCHO-VW/WS2, the energy level contribution of HCHO is closer to the Fermi level, the charge transfer (B) is the largest (0.104 e), the increase in W is more obvious than other adsorption systems, the slope of the I–V characteristic changes more obviously, and the calculated sensitivity is the highest. To sum up, VW/WS2 is more sensitive to HCHO. In conclusion, VW/WS2 has a great deal of promise for producing HCHO chemical sensors due to its high sensitivity and selectivity for HCHO, which can aid in the precise and efficient detection of toxic gases.

The frequent occurrences of cyberbullying on social platforms have sparked a great deal of social conflict, and bystander intervention plays a crucial role in preventing the escalation of cyberbullying. This research examines the impact of victim self-disclosure on bystander intervention in cyberbullying through two experimental studies. The studies collected data from March to July of 2022, utilizing a convenience sampling approach to recruit university students as experiment participants. Study 1 recruited 247 valid participants, while Study 2 recruited 522 eligible participants. The results of Study 1 indicate that the perceptible dimensions (frequency, privacy, and valence) of victim self-disclosure impact bystander intervention. Specifically, in a low privacy context, positive self-disclosure increases bystander intervention, while negative self-disclosure does the opposite. The results of Study 2 suggest that the valence of self-disclosure affects bystander intervention through the mediation of victim blaming, with interpersonal distance moderating the impact of victim self-disclosure valence on the extent of victim blaming. This moderated mediation model clarifies the psychological process by which the valence of victim self-disclosure affects bystander intervention. The findings of this study contribute to the understanding of the social psychological process behind bystander intervention, providing a scientific basis and pathway for reducing cyberbullying and fostering a harmonious online environment.

The COVID-19 pandemic has brought enormous challenges to both employees and organizations all over the world. Previous studies have found high turnover rates among prison officers since the outbreak of COVID-19. This cross-sectional study aimed to investigate the mediating role of job burnout between job demands and turnover intention, as well as the moderating role of the perceived efficacy in overcoming COVID-19 in Chinese prison officers. In total, 1316 prison officers were recruited to complete an online questionnaire between May 2022 and June 2022 (during the COVID-19 pandemic). The bootstrapping approach was used to assess the moderated mediation model in this study. The results showed that prison officers’ job demands were positively associated with their turnover intention. Job burnout mediated the relationship between job demands and turnover intention. Perceived efficacy in overcoming COVID-19 moderated the effect of job burnout on turnover intention. Based on these results, suggestions were provided to reduce the high turnover rate of prison officers in public health events like the COVID-19 pandemic.

Dredging materials from reef flats have become an important source of sand and aggregates for meeting the infrastructure needs of coral-lined shores in subtropical and tropical regions, especially for low-lying atoll islands. Dredging at the reef flats can generate artificial excavation pits, which not only have profound influences on coral ecological stability but also deeply affect the hydrodynamic characteristics of coral reefs. To deepen the understanding of the influence of excavation on the wave hydrodynamics of fringing reefs, the wave propagation, wave transformation, wave setup, and wave runup processes of regular waves on fringing reefs with artificial pits have been systematically analyzed using a non-hydrostatic numerical wave solver (NHWAVE). The effects of some significant factors have been carefully investigated. According to the study findings, the existence of artificial pits can result in a slight decrease in the wave height around the artificial pit. The time-mean maximum of wave runup height at the backreef slope can be reduced to some extent when the artificial pit is present. When placed close to the reef edge, the artificial pit can have noticeable effects on the hydrodynamic characteristics of fringing reefs, particularly the wave setup along the reef flat. It is hoped that the study findings can provide further reference for evaluation of the influences of artificial pits on the wave hydrodynamics of fringing reefs.

In recent years, Kubernetes (K8s) has become a dominant resource management and scheduling system in the cloud. In practical scenarios, short-running cloud workloads are usually scheduled through different scheduling algorithms provided by Kubernetes. For example, artificial intelligence (AI) workloads are scheduled through different Volcano scheduling algorithms, such as GANG_MRP, GANG_LRP, and GANG_BRA. One key challenge is that the selection of scheduling algorithms has considerable impacts on job performance results. However, it takes a prohibitively long time to select the optimal algorithm because applying one algorithm in one single job may take a few minutes to complete. This poses the urgent requirement of a simulator that can quickly evaluate the performance impacts of different algorithms, while also considering scheduling-related factors, such as cluster resources, job structures and scheduler configurations. In this paper, we design and implement a Kubernetes simulator called K8sSim, which incorporates typical Kubernetes and Volcano scheduling algorithms for both generic and AI workloads, and provides an accurate simulation of their scheduling process in real clusters. We use real cluster traces from Alibaba to evaluate the effectiveness of K8sSim, and the evaluation results show that (i) compared to the real cluster, K8sSim can accurately evaluate the performance of different scheduling algorithms with similar CloseRate (a novel metric we define to intuitively show the simulation accuracy), and (ii) it can also quickly obtain the scheduling results of different scheduling algorithms by accelerating the scheduling time by an average of 38.56×.

The low-lying reef islands distributed in the tropical and subtropical coastal regions are highly vulnerable to the devastating damages of surges and waves during the severe weather events. Over the past two decades, extreme waves have caused tremendous loss and damages to the tropical and subtropical coastal regions. Previous research has focused on the wave hydrodynamics of tsunami waves, as well as regular and irregular waves on the fringing reefs. The complex wave hydrodynamics of extreme waves on the fringing reefs are rarely studied. By applying the nonhydrostatic numerical flow solver (NHWAVE), transformation and breaking process of the crest- and trough-focused wave groups on the fringing reef are analyzed in this study. Influences of the major factors, i.e., water depth, significant wave height, peak wave period, forereef slope and backreef slope, and ridge width, are discussed in detail. The results show that there are complex interactions between the fringing reef and the focused wave group. Breaking waves of high intensity can form at the reef crest. Meanwhile, due to the wave breakings at the reef crest and bottom friction of the reef flat, the local wave height can be effectively reduced. Within the complex wave hydrodynamics of focused waves on the fringing reef, most of the wave energy can be dissipated. In addition, hydrodynamic difference between the crest- and trough-focused waves on the fringing reef is very limited. The research results of this study will further help researchers to better understand the wave hydrodynamics of extreme waves over the fringing reefs.

Chinese Herbal Medicines (CHMs) can be identified by experts according to their odors. However, the identification of these medicines is subjective and requires long-term experience. The samples of Acanthopanacis Cortex and Periplocae Cortex used were dried cortexes, which are often confused in the market due to their similar appearance, but their chemical composition and odor are different. The clinical use of the two herbs is different, but the phenomenon of being confused with each other often occurs. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two species for fast and robust discrimination, in order to provide a scientific basis for avoiding confusion and misuse in the process of production, circulation and clinical use. In this study, the odor and volatile components of these two medicinal materials were detected by the E-nose and by gas chromatography–mass spectrometry (GC-MS), respectively. An E-nose combined with pattern analysis methods such as principal component analysis (PCA) and partial least squares (PLS) was used to discriminate the cortex samples. The E-nose was used to determine the odors of the samples and enable rapid differentiation of Acanthopanacis Cortex and Periplocae Cortex. GC-MS was utilized to reveal the differences between the volatile constituents of Acanthopanacis Cortex and Periplocae Cortex. In all, 82 components including 9 co-contained components were extracted by chromatographic peak integration and matching, and 24 constituents could be used as chemical markers to distinguish these two species. The E-nose detection technology is able to discriminate between Acanthopanacis Cortex and Periplocae Cortex, with GC-MS providing support to determine the material basis of the E-nose sensors’ response. The proposed method is rapid, simple, eco-friendly and can successfully differentiate these two medicinal materials by their odors. It can be applied to quality control links such as online detection, and also provide reference for the establishment of other rapid detection methods. The further development and utilization of this technology is conducive to the further supervision of the quality of CHMs and the healthy development of the industry.

During severe weather, the runup of the devasting surges and waves can cause extensive damages to the coastal facilities and results in significant loss of life. Therefore, it becomes necessary to find reliable measures to reduce the wave runup in coastal regions. As a natural barrier to the shorelines, coastal vegetation has great potential to attenuate wave runup and to prevent the coastal communities from extreme floodings and huge land loss. This study numerically discusses the influences of the emergent vegetation patch on the runup processes of extreme wave groups by applying a nonhydrostatic flow solver. Influences of the major factors, i.e., water depth, peak wave period, significant wave height, and density and length of the vegetation patch, are analyzed in detail. Research findings indicate that the presence of the emergent vegetation patch can substantially dissipate most of the incident wave energy and effectively reduce the maximum wave runup heights of extreme wave groups at the sloped beach. It is hoped that the research results of this study will be helpful to the design of coastal soft protection measures.

The stability and validity of the BDS-3 precise point positioning ambiguity solution (PPP-AR) is becoming more and more important along with the development of BDS-3 orbit and clock products over long durations. Satellite phase fractional cycle biases (FCBs) are key in PPP-AR, so it is important to ensure the validity and stability of FCBs over a long duration. In this study, we analyzed the validity and stability of BDS-3 phase FCBs by estimating them. The BDS-3 FCB experiments showed that BDS-3 FCBs have the same stability as GPS/GAL/BDS-2. BDS-3 widelane (WL) FCBs also have stable characteristics and the maximal fluctuation value of WL FCBs was found to be 0.2 cycles in a month. BDS-3 narrowlane (NL) FCBs were found to be unstable and the maximal fluctuation value of NL FCBs was more than 0.25 cycles over one day. Analyzing the posteriori residual errors of BDS-3 WL and NL ambiguities showed that the BDS-3 FCBs had the same accuracy as GPS/GAL/BDS-2. However, the ambiguity-fixed rate of BDS-3 was about 70%, which was less than GPS/GAL/BDS-2 in PPP-AR experiments. For this reason, we analyzed the quality of data and the accuracy of orbit and clock products by using different analysis center products. The results showed that the low accuracy of the BDS-3 orbit and clock products was the main reason for the low-ambiguity fixed rate.

As protection for nuclear power plants is quite necessary, the nuclear fuel is sealed in zirconium alloy thin wall cladding. During service, fuel rods might be damaged caused by wall-thickness thinning, cladding corrosion and cracking, etc. This will cause the coolant to enter into the fuel rod, which may lead to the failure of the fuel assembly. However, current diagnostic methods have limitations due to the special structure of the fuel assembly and the underwater and radioactive environment. In this paper, a novel inspection method is proposed to recognize the failure of a fuel rod. The fuel rod failure can be detected based on the presence or absence of coolant inside the fuel rod by using an ultrasonic plate wave. The inspection model and process algorithm are proposed for in-service inspection. The relationship between signal and scanning position is established and analyzed. Both ultrasound field simulation and experiment have been carried out for validation. The corresponding results illustrate that the failed nuclear fuel rod of the whole fuel assembly (including the internal rods) can be effectively detected without the influence of the near-field region by using the proposed method.

An isothermal compression experiment was conducted to study the rheological behavior of Al-4.57Zn-1.50Mg-1.92Cu high-strength aluminum alloy at strain rates ranging from 0.1 to 20 s−1 and temperatures in the range of 573 to 773 K. Then, the effects of strain, strain rate, and deformation temperature on material deformation were investigated through orthogonal experiment analysis. According to the research results, strain rate and temperature had significant effects on the level of flow stress. Besides, the constitutive equation was established and demonstrated as applicable to predict the performance accurately. Meanwhile, the processing map under a true strain of 1.1 was built, to assess the deformation safety in different domains. Furthermore, the evolutionary trend of microstructure was observed by means of Scanning Electron Microscope, Electron Back-Scattered Diffraction and Transmission Electron Microscope. It was discovered that dynamic recovery and small-scale dynamic recrystallization played a major role in the softening mechanism of alloy during hot deformation. Moreover, dynamic recrystallization was found to have a significant impact on the hot deformation behavior of the alloys.

Laser printing has become a promising alternative for large-scale fabrication of functional devices. Here, laser-induced forward transfer (LIFT) of nanosilica was successfully achieved using a lower-cost nanosecond laser with a center wavelength of 1064 nm. To enhance the light absorption of silica, a small amount of graphene oxide (GO) was added to the fumed silica. Investigations were conducted to give an insight into the role of GO in the LIFT process. Pattern deposition was achieved with a minimum line width of 221 μm. The scattering can be tuned from ~2.5% to ~17.5% by changing the laser fluence. The patternable transparent display based on laser transferred nanosilica (LTNS) film was also demonstrated, showing its capability to deliver information on multiple levels. This LIFT based technique promotes fast, flexible, and low-cost manufacturing of scattering-based translucent screens or patterns for transparent displays.

To achieve carbon neutrality in the EU, it is important to renovate the existing EU residential buildings for a higher building energy efficiency. This study examines the impacts of several novel renovation technologies on energy consumption, CO2 emissions and indoor climates in southern European residential buildings through building-level simulations. Three typical residential buildings in South Europe were chosen as the demo buildings to implement the novel technologies. The technologies were classified into passive, ventilation and generation packages, and then simulated independently under the intermittent and continuous heating schedules. Additionally, two final combinations of renovation technologies were also simulated to demonstrate the maximum energy and CO2 emissions reduction potential of the demo buildings. All novel retrofit technologies manifested obvious effects on the energy consumption and CO2 emissions. Nevertheless, the effects were significantly affected by the heating schedule. When the intermittent heating schedule was switched to the continuous heating schedule, the relative energy conservation and CO2 emissions reduction potential of the thermal insulation improvement measures (e.g., bio-aerogel thermal insulation) increased, while those of the generation measures (e.g., solar assisted heat pump) diminished. Renovation with the final combinations reduced the primary energy consumption by up to 66%, 74% and 65% in the continuously heated Greek, Portuguese and Spanish demo buildings, the corresponding CO2 emissions reductions of which were 65%, 75% and 74%, respectively.

Satellite phase fractional cycle biases (FCBs) are crucial to precise point positioning with ambiguity resolution (PPP–AR), and they can improve the accuracy and reliability of a solution. Traditional methods need multiple iterations and need to keep the same reference when estimating satellite phase fractional cycle biases. In this paper, we propose an improved fast estimation of FCB, which does not need any iterations and can select any reference when estimating FCB. We compare the suitability and precision of a traditional and a proposed method by BDS-3 experiments. The results of the FCB experiments show that the calculated time of the proposed method is less than the traditional method and that computation efficiency is increased by 34.71%. These two methods have a similar rate of fixed epochs and ambiguities in the static and dynamic models. However, the time to first fix (TTFF) of the proposed method decreased by 19.69% and 28.83% for the static and dynamic models, respectively. The results show that the proposed method has a better convergence time in PPP–AR.

In the context of the problem of image blur and nonlinear reflectance difference between bands in the registration of hyperspectral images, the conventional method has a large registration error and is even unable to complete the registration. This paper proposes a robust and efficient registration algorithm based on iterative clustering for interband registration of hyperspectral images. The algorithm starts by extracting feature points using the scale-invariant feature transform (SIFT) to achieve initial putative matching. Subsequently, feature matching is performed using four-dimensional descriptors based on the geometric, radiometric, and feature properties of the data. An efficient iterative clustering method is proposed to perform cluster analysis on the proposed descriptors and extract the correct matching points. In addition, we use an adaptive strategy to analyze the key parameters and extract values automatically during the iterative process. We designed four experiments to prove that our method solves the problem of blurred image registration and multi-modal registration of hyperspectral images. It has high robustness to multiple scenes, multiple satellites, and multiple transformations, and it is better than other similar feature matching algorithms.

Autophagy, an evolutionarily conserved mechanism to remove redundant or dangerous cellular components, plays an important role in innate immunity and defense against pathogens, which, in turn, can regulate autophagy to establish infection within a host. However, for Entamoeba histolytica, an intestinal protozoan parasite causing human amoebic colitis, the interaction with the host cell autophagy mechanism has not been investigated. In this study, we found that E. histolytica peroxiredoxin (Prx), an antioxidant enzyme critical for parasite survival during the invasion of host tissues, could activate autophagy in macrophages. The formation of autophagosomes in macrophages treated with recombinant Prx of E. histolytica for 24 h was revealed by immunofluorescence and immunoblotting in RAW264.7 cells and in mice. Prx was cytotoxic for RAW264.7 macrophages after 48-h treatment, which was partly attributed to autophagy-dependent cell death. RNA interference experiments revealed that Prx induced autophagy mostly through the toll-like receptor 4 (TLR4)–TIR domain-containing adaptor-inducing interferon (TRIF) pathway. The C-terminal part of Prx comprising 100 amino acids was the key functional domain to activate autophagy. These results indicated that Prx of E. histolytica could induce autophagy and cytotoxic effects in macrophages, revealing a new pathogenic mechanism activated by E. histolytica in host cells.

In order to numerically investigate the free surface flow evolution in a cylindrical tank, a regular structured grid system in the cylindrical coordinates is usually applied to solve control equations based on the incompressible two-phase flow model. Since the grid spacing in the azimuthal direction is proportionate to the radial distance in a regular structured grid system, very small grid spacing would be obtained in the azimuthal direction and it would require a very small computational time step to satisfy the stability restriction. Moreover, serious mass disequilibrium problems may happen through the convection of the free surface with the Volume of Fluid (VOF) method. Therefore in the present paper, the zonal embedded grid technique was implemented to overcome those problems by gradually adjusting the mesh resolution in different grid blocks. Over the embedded grid system, a finite volume algorithm was developed to solve the Navier−Stokes equations in the three-dimensional cylindrical coordinates. A high-resolution scheme was applied to resolve the free surface between the air and water phases based on the VOF method. Computation of liquid convection under a given velocity field shows that the VOF method implemented with a zonal embedded grid is more advanced in keeping mass continuity than that with regular structured grid system. Furthermore, the proposed model was also applied to simulate the sharp transient evolution of circular dam breaking flow. The simulation results were validated against the commercial software Fluent, which shows a good agreement, and the proposed model does not yield any free surface oscillation.

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy.

The occurrence and densities of opportunistic pathogens (OPs), the microbial community structure, and their associations with sediment elements from eight water storage tanks in Ohio, West Virginia, and Texas were investigated. The elemental composition of sediments was measured through X-ray fluorescence (XRF) spectra. The occurrence and densities of OPs and amoeba hosts (i.e., Legionella spp. and L. pneumophila, Mycobacterium spp., P. aeruginosa, V. vermiformis, Acanthamoeba spp.) were determined using genus- or species-specific qPCR assays. Microbial community analysis was performed using next generation sequencing on the Illumina Miseq platform. Mycobacterium spp. were most frequently detected in the sediments and water samples (88% and 88%), followed by Legionella spp. (50% and 50%), Acanthamoeba spp. (63% and 13%), V. vermiformis (50% and 25%), and P. aeruginosa (0 and 50%) by qPCR method. Comamonadaceae (22.8%), Sphingomonadaceae (10.3%), and Oxalobacteraceae (10.1%) were the most dominant families by sequencing method. Microbial communities in water samples were mostly separated with those in sediment samples, suggesting differences of communities between two matrices even in the same location. There were associations of OPs with microbial communities. Both OPs and microbial community structures were positively associated with some elements (Al and K) in sediments mainly from pipe material corrosions. Opportunistic pathogens presented in both water and sediments, and the latter could act as a reservoir of microbial contamination. There appears to be an association between potential opportunistic pathogens and microbial community structures. These microbial communities may be influenced by constituents within storage tank sediments. The results imply that compositions of microbial community and elements may influence and indicate microbial water quality and pipeline corrosion, and that these constituents may be important for optimal storage tank management within a distribution system.

A flexible acoustic pressure sensor was developed based on the change in electrical resistance of three-dimensional (3D) graphene change under the acoustic waves action. The sensor was constructed by 3D graphene foam (GF) wrapped in flexible polydimethylsiloxane (PDMS). Tuning forks and human physiological tests indicated that the acoustic pressure sensor can sensitively detect the deformation and the acoustic pressure in real time. The results are of significance to the development of graphene-based applications in the field of health monitoring, in vitro diagnostics, advanced therapies, and transient pressure detection.

As one of the most representative natural products among flavonoids, quercetin (QUE) has been reported to exhibit beneficial effects on gut health in recent years. In this study, we utilized a dextran sulfate sodium (DSS)-induced colitis mice model to explore the protective effects and underlying mechanisms of QUE on colitis. Our data demonstrated that QUE oral gavage administration significantly ameliorates the symptoms and histopathological changes associated with colitis. Additionally, the concentration of mucin-2, the number of goblet cells, and the expression of tight junction proteins (such as ZO-1, Occludin, and Claudin-1) were all found to be increased. Furthermore, QUE treatment regulated the levels of inflammatory cytokines and macrophage polarization, as well as the oxidative stress-related pathway (Nrf2/HO-1) and associated enzymes. Additionally, 16S rDNA sequencing revealed that QUE treatment rebalances the alterations in colon microbiota composition (inlcuding Bacteroidaceae , Bacteroides , and Odoribacter ) in DSS-induced colitis mice. The analysis of network dynamics reveals a significant correlation between gut microbial communities and microenvironmental factors associated with inflammation and oxidative stress, in conjunction with the previously mentioned findings. Collectively, our results suggest that QUE has the potential to treat colitis by maintaining the mucosal barrier, modulating inflammation, and reducing oxidation stress, which may depend on the reversal of gut microbiota dysbiosis.

The daylily ( Hemerocallis citrina Baroni) flower is a traditional raw food material that is rich in a variety of nutrients. In particular, the content of polysaccharides in daylily is abundant and has been widely used as a functional component in food, cosmetics, medicine, and other industries. However, studies on the structure-effective relationship of daylily flower polysaccharides are still lacking. In view of this, daylily flower polysaccharides were isolated and purified, and their physical and chemical properties, structure, antioxidant activity, and adhesion-promoting effect on probiotics were evaluated. The results showed that a novel water-soluble polysaccharide (DPW) with an average molecular weight ( M w ) of 2.224 kDa could be successfully isolated using column chromatography. Monosaccharide composition analysis showed that DPW only comprised glucose and fructose, with a molar ratio of 0.242:0.758. Through methylation and nuclear magnetic resonance (NMR) analysis, it was inferred that DPW belonged to the fructans group with a structure of α-D-Glcp-1→2-β-D-Fruf-1→(2-β-D-Fruf-1) n →. Antioxidant analysis showed that DPW showed strong 2-Phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-Oxide (PTIO-scavenging activity with IC 50 of 1.54 mg/mL. DPW of 1.25 to 5 mg/mL could significantly increase the adhesion rate of Lactobacillus acidophilu , Lactobacillus casei , Bifidobacterium adolescentis , and Lactobacillus plantarum on Caco-2 cells. Considering the above results, the present study provides a theoretical basis and practical support for the development and application of daylily polysaccharides as a functional active ingredient.

Dental pulp pericytes are reported to have the capacity to generate odontoblasts and express multiple cytokines and chemokines that regulate the local immune microenvironment, thus participating in the repair of dental pulp injury in vivo. However, it has not yet been reported whether the transplantation of exogenous pericytes can effectively treat pulpitis, and the underlying molecular mechanism remains unknown. In this study, using a lineage-tracing mouse model, we showed that most dental pulp pericytes are derived from cranial neural crest. Then, we demonstrated that the ablation of pericytes could induce a pulpitis-like phenotype in uninfected dental pulp in mice, and we showed that the significant loss of pericytes occurs during pupal inflammation, implying that the transplantation of pericytes may help to restore dental pulp homeostasis during pulpitis. Subsequently, we successfully generated pericytes with immunomodulatory activity from human pluripotent stem cells through the intermediate stage of the cranial neural crest with a high level of efficiency. Most strikingly, for the first time we showed that, compared with the untreated pulpitis group, the transplantation of hPSC-derived pericytes could substantially inhibit vascular permeability (the extravascular deposition of fibrinogen, ** p < 0.01), alleviate pulpal inflammation (TCR + cell infiltration, * p < 0.05), and promote the regeneration of dentin (** p < 0.01) in the mouse model of pulpitis. In addition, we discovered that the knockdown of latent transforming growth factor beta binding protein 1 ( LTBP1 ) remarkably suppressed the immunoregulation ability of pericytes in vitro and compromised their in vivo regenerative potential in pulpitis. These results indicate that the transplantation of pericytes could efficiently rescue the aberrant phenotype of pulpal inflammation, which may be partially due to LTBP1 -mediated T cell suppression.

Substantial single-species studies have reported the facility of nitric oxide (NO) in alleviating heavy metal-induced stress in plants. Understanding the mechanisms of NO-involved stress alleviation is progressing; however, a quantitative description of the alleviative capacity of NO against heavy metal stress is still lacking. We combined the results of 86 studies using meta-analysis to statistically assess the responses of heavy metal-stressed plants to NO supply across several metal stresses and plant families. The results showed that plant biomass was consistently improved following NO supply to metal-stressed plants. NO played an important role in mitigating oxidative damage caused by heavy metal stress by significantly stimulating the activities of antioxidant enzymes. Moreover, NO supply consistently increased the Ca, Fe, and Mg contents in both leaves and roots. Plant tissues accumulated less heavy metals when exposed to heavy metal stress after NO addition. Additionally, the best concentration of SNP (an NO donor) for hydroponic culture is in the range of 75-150 μM. We further confirmed that NO application can generally alleviate plant heavy metal stress and its action pathway. The results presented here can help guide future applications of NO as a plant growth regulator in agriculture and breeding plants for heavy metal stress tolerance.

CO 2 , an acidic gas, is usually emitted from the combustion of fossil fuels and leads to the formation of acid rain and greenhouse effects. CO 2 can be used to produce kinds of value-added chemicals from a viewpoint based on carbon capture, utilization, and storage (CCUS). With the combination of unique structures and properties of ionic liquids (ILs) and covalent organic frameworks (COFs), covalent organic frameworks with ionic liquid-moieties (ILCOFs) have been developed as a kind of novel and efficient sorbent, catalyst, and electrolyte since 2016. In this critical review, we first focus on the structures and synthesis of different kinds of ILCOFs materials, including ILCOFs with IL moieties located on the main linkers, on the nodes, and on the side chains. We then discuss the ILCOFs for CO 2 capture and conversion, including the reduction and cycloaddition of CO 2 . Finally, future directions and prospects for ILCOFs are outlined. This review is beneficial for academic researchers in obtaining an overall understanding of ILCOFs and their application of CO 2 conversion. This work will open a door to develop novel ILCOFs materials for the capture, separation, and utilization of other typical acid, basic, or neutral gases such as SO 2 , H 2 S, NOx, NH 3 , and so on.

As the initial antibody technology, the preparation of hybridoma cells has been widely used in discovering antibody drugs and is still in use. Various antibody drugs obtained through this technology have been approved for treating human diseases. However, the key to producing hybridoma cells is efficient cell fusion. High-voltage microsecond pulsed electric fields (μsHVPEFs) are currently one of the most common methods used for cell electrofusion. Nevertheless, the membrane potential induced by the external microsecond pulse is proportional to the diameter of the cell, making it difficult to fuse cells of different sizes. Although nanosecond pulsed electric fields (nsPEFs) can achieve the fusion of cells of different sizes, due to the limitation of pore size, deoxyribonucleic acid (DNA) cannot efficiently pass through the cell pores produced by nsPEFs. This directly causes the significant loss of the target gene and reduces the proportion of positive cells after fusion. To achieve an electric field environment independent of cell size and enable efficient cell fusion, we propose a combination of nanosecond pulsed electric fields and low-voltage microsecond pulsed electric fields (ns/μsLVPEFs) to balance the advantages and disadvantages of the two techniques. The results of fluorescence experiments and hybridoma culture experiments showed that after lymphocytes and myeloma cells were stimulated by a pulse (ns/μsLVPEF, μsHVPEF, and control), compared with μsHVPEF, applying ns/μsLVPEF at the same energy could increase the cell fusion efficiency by 1.5-3.0 times. Thus far, we have combined nanosecond and microsecond pulses and provided a practical solution that can significantly increase cell fusion efficiency. This efficient cell fusion method may contribute to the further development of hybridoma technology in electrofusion.