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Abstract Purpose Soil microbial communities are critically important to agricultural ecosystems. The present study aimed to evaluate the changes in soil microbial community composition and functional groups after planting Phallus rubrovolvatus. Methods Illumina platform were adopted to characterize the bacterial and fungal diversity in the soil cropped with P. rubrovolvatus for 0 and 1 year. Results The results showed that planting P. rubrovolvatus reduced the bacterial and fungal diversity in the soil, and the dynamics of the soil bacterial diversity changed more drastically. This study also indicated that, as keystone taxa, the dominant bacteria (Actinobacteria, Sphingomonas, Xanthobacteraceae, and Gemmatimonadaceae) and dominant fungi (Mortierellales and Eurotiales) served as a key component in the network of soil microbial communities. Moreover, the bacterial and fungal communities in the soil planted with P. rubrovolvatus formed more similar and weak networks. Conclusion Planting P. rubrovolvatus significantly influenced the structure and composition of microbial communities. In the future, we will focus on ways to improve the soil environment after planting P. rubrovolvatus.

Based on the unique insulator-metal phase transition property of vanadium dioxide (VO2), we propose an integrated metasurface with a switchable mechanism between ultra-broadband absorption and polarization conversion, operating in the terahertz (THz) frequency range. The designed metasurface device is constructed using a stacked structure composed of VO2 quadruple rings, a dielectric layer, copper stripes, VO2 film, a dielectric layer, and a copper reflection layer. Our numerical simulations demonstrate that our proposed design, at high temperatures (above 358 K), exhibits an ultra-broadband absorption ranging from 4.95 to 18.39 THz, maintaining an absorptivity greater than 90%, and achieves a relative absorption bandwidth of up to 115%, significantly exceeding previous research records. At room temperature (298 K), leveraging VO2’s insulating state, our proposed structure transitions into an effective polarization converter, without any alteration to its geometry. It enables efficient conversion between orthogonal linear polarizations across 3.51 to 10.26 THz, with cross-polarized reflection exceeding 90% and a polarization conversion ratio over 97%. More importantly, its relative bandwidth reaches up to 98%. These features highlight its wide-angle, extensive bandwidth, and high-efficiency advantages for both switching functionalities. Such an ultra-broadband convertible design offers potential applications in optical switching, temperature dependent optical sensors, and other tunable THz devices in various fields.

In this work, we introduce a novel coherent perfect absorber, accentuating its novelty by emphasizing the broad bandwidth, reduced thickness, tunable property, and straightforward design achieved through the use of an asymmetric graphene metasurface. This design incorporates both square and circular graphene patches arranged on either side of a silicon substrate. With an optimized structural design, this absorber consistently captures over 90% of incoming waves across the frequency range of 1.65 to 4.49 THz, with a graphene Fermi level of 0.8 eV, and the whole device measures just 1.5 um thick. This makes our absorber significantly more effective and compact than previous designs. The absorber’s effectiveness can be significantly enhanced by combining the metasurface’s geometric design with the graphene Fermi level. It is anticipated that this ultrathin, wideband coherent perfect absorption device will play a crucial role in emerging on-chip THz communication technologies, including light modulators, photodetectors, and so on.

Magnetic reconnection is well known as an efficient mechanism for transferring magnetic energy into plasma energy. However, how the energy conversion and partition between different species is influenced by the shear angle of the reconnecting magnetic component (i.e., the guide field strength) is not well understood. Using 2.5-dimensional particle-in-cell simulations, we investigated the energy conversion in reconnection with different guide fields. We found that the overall energy conversion first decreases steeply and then increases slowly when the guide field increases from \begin{document}$ {B}_{g} $\end{document} = 0 to \begin{document}$ {B}_{g} $\end{document} = 4. The increase in energy conversion in the large guide field regime is due to the electron energy gain through the perpendicular channel \begin{document}${\boldsymbol{J}}_{\perp }\cdot {\boldsymbol{E}}_{\perp }$\end{document}. The overall energy conversion is predominantly contributed by \begin{document}${\boldsymbol{J}}_{\perp }\cdot{ \boldsymbol{E}}_{\perp }$\end{document} rather than \begin{document}$ {J}_{\parallel }{E}_{\parallel } $\end{document}. We further find that energy conversion mainly occurs within the reconnection front and the flux pileup region. However, the contribution from the fore reconnection front becomes important in large guide field regimes (\begin{document}$ 3 < {B}_{g}\le 4 $\end{document}) because of the enhanced electron energy gain.

Promoting rice straw in situ return is an important strategy for improving soil quality. From 2018 to 2021, we investigated the effects of rice straw return with microbial agents and film covering technology on soil physical and chemical properties at different layer depths, as well as the soil microbial community structure, in Hunan, southern China. This study was designed to evaluate the effects of microbial agents (T1), film mulch covering (T2), and the application of microbial agents combined with film mulch (T3) on the soil physicochemical properties and microbial community after rice straw in situ return. The results show that, after three years of continuous treatment, T3 significantly increased the soil temperature by 17.76–22.97%, T2 significantly increased the water content by 34.27–46.23%, and T1 and T3 significantly increased the soil pH. The addition of microbial agents combined with film mulch resulted in a notable increase in both the number of OTUs and the Chao1 index of soil microorganisms. Additionally, the model of promoting rice straw in situ return (the application of a microbial agent combined with film mulch) was shown to promote the growth of beneficial soil microorganisms. RDA was used for the investigation, and the findings showed that soil microorganisms were significantly influenced by the TOC content, pH, and water content. These findings provide evidence of an effective method for accelerating the decomposition of late rice straw and guiding soil improvement in tobacco–rice rotation regions.

Straw incorporation into soil contributes significantly to the sustainable development of agriculture. To investigate the impact of tobacco straw returns on a tobacco–rice replanting system, we designed an experiment with two straw return levels and a control group: T1 (full return), T2 (root return), and CK (no straw return). Over a three-year field experiment in rice fields in South China, we assessed the effects of tobacco straw return on soil quality, microbial diversity, dry matter accumulation, and yield composition of rice. The results demonstrated that returning tobacco straw to the field effectively enhanced rice yield by positively influencing various soil physical, chemical, and biological properties. Compared to those in the CK treatment, as the soil porosity increased from 9.0% to 12.4%, the mean weight diameter of the soil aggregates substantially increased, ranging from 28.7% to 45.2%. There were significant increases in soil organic matter, total nitrogen, and alkaline dissolved nitrogen. Soil sucrase activity increased between 29.8% and 44.9%, and urease activity increased between 4.3% and 62.2% over the three consecutive years of straw return. The diversity index of soil fungi significantly increased. Additionally, rice yield increased markedly, ranging from 1.8% to 5.1%. Overall, the enhancement effect of T1 surpassed that of T2. According to our comprehensive analysis, the incorporation of tobacco straw into the field was found to enhance the physical properties of the soil, elevate soil enzyme activity, and increase the abundance of soil microorganisms. Consequently, this practice led to improved rice yield and a reduction in agricultural waste output. Overall, the return of tobacco straw to the field represents a clean and dependable approach in rice-cultivated tobacco areas to improve soil health and rice productivity.

Communication blackouts have been a main threat to hypersonic vehicles for decades. The low frequency communication was considered a potential approach to mitigate the “blackout.” Nowadays, low frequency transmitters serving underwater communication have transmission power up to several megawatts. In other words, if low frequency communication signals could penetrate the plasma sheath, it would be a meaningful solution that using modern low frequency transmitters to give service to hypersonic vehicle communication, and the service area could be very large. Although the studies on blackouts using low frequency waves have lasted for many years, it still remains many unclear problems. The present study analyzes the characteristics of different frequency waves passing through a plasma sheath. The analysis revealed that the low frequency signals with high power could penetrate the plasma sheath and mitigate the blackout effectively. According to our simulation results, the transmission coefficient decreased with the flight speed and also increased with magnetic field intensity and the axial distance from the onboard antenna to the nose of the vehicle. Moreover, it is not sensitive to the frequency of signals. At last, two example models of using a ground low frequency station to communicate with the hypersonic vehicle were analyzed, which means that the low frequency communication can significantly be considered in the application of hypersonic vehicles in the near future.

Land use recognition from multispectral satellite images is fundamentally critical for geological applications, but the results are not satisfied. The scale dimension of current multiscale learning is too coarse to account for rich scales in multispectral images, and pixel-wise classification tends to produce “salt-and-pepper” labels due to possible misclassification in heterogeneous regions. In this article, these issues are addressed by proposing a new pixel-wise classification model with finer scales for convolutional neural networks. The model is designed to extract multiscale contextual information using multiscale networks at a fine-grained level, addressing the issue of insufficient multiscale learning for classification. Furthermore, a small-scale segmentation-combination method is introduced as a postprocessing solution to smooth fragmented classification results. The proposed method is tested on GF-1, GF-2, DEIMOS-2, GeoEye-1, and Sentinel-2 satellite images, and compared with six neural-network-based algorithms. The results demonstrate the effectiveness of the proposed model in finding objects of large scale difference, improving classification accuracy, and reducing classified fragments. The discussion also illustrates that convolutional neural networks and pixel-wise inference are more practical than transformer and patch-wise recognition.

Abstract Purpose Based on the recycling principle, returning of tobacco crop residues into the field is a common agronomic practice. However, comprehensive knowledge about the effects of tobacco plant residue return on the rhizosphere soil microbial community is very limited. Methods After tobacco crop residue returning into the potted soil, 16S ribosomal RNA (rRNA) and internal transcribed spacer (ITS) amplicon sequencing were employed to investigate the bacterial and fungal communities, respectively, from the tobacco rhizosphere soils. Results The results showed that tobacco residue returning increased the diversity of microbial communities (bacteria and fungi) and changed the species composition. It further increased the relative abundance of beneficial microorganisms. After tobacco residue returning, the structure of the rhizosphere soil microbial community network was found more complex with strong interactions among microbial species. In addition, the keystone species of bacterial and fungal communities associated with tobacco rhizosphere soil were altered. This had exerted a driving force to the beneficial bacteria such as Sphiningomonas and Psathyrella to the keystone microorganisms which played important roles in microbial species interaction. Conclusions Tobacco residue return into soil showed significant effects on the microbial diversity, community composition, network structure, keystone microorganisms, and ecosystem functions of tobacco rhizosphere soils. This study provides a scientific basis for the improvement of tobacco field ecosystem functioning and ensuring soil health.

Objective: The amylase-producing strain screened on the surface of Yunnan Malong C3F-2016 tobacco leaves were used as the starting strain to mutagenically select high amylase-producing strain and to study the enzymatic properties before and after mutagenesis. Methods: The amylase-producing strain were selected by ARTP technique and the amylase activity was determined by the 3,5-dinitrosalicylic acid (DNS) method before and after mutagenesis, and the effects of different temperatures, pH, metal ions and UV light on the amylase activity were investigated. Results: A mutant strain Bacillus koreensis FS-103 was selected by mutagenesis with improved enzyme activity and stable transmission, and its amylase activity reached 9050 U/mL, which was 90% higher than that of the starting strain. The optimum action temperature of amylase produced by the high-yielding mutant strain FS-103 was 60 ℃ and the optimum action pH5.5, with good stability between 40 and 50 ℃ and pH5~6, Ca2+ and Mg2+ had a promoting effect on amylase activity, and the effect of UV irradiation on amylase activity was weakened. Conclusion: This method of mutagenic selection of amylase-producing strain was feasible and lays the theoretical foundation for the research and development of enzyme preparations by this type of strain.

Magnetic reconnection is one of the important physical mechanisms for the conversion of magnetic energy into plasma energy, which is closely related to many explosive phenomena in space. Magnetic reconnection is a cross-scale physical process, in which the physical process at the electron-scale plays key roles in triggering reconnection and facilitating reconnection fast, hence it has attracted much attention. After the launch of the magnetospheric multiscale (MMS) satellite in 2015, the unprecedented high-resolution data provided by MMS enable us to have a new understanding of the electron-scale physics. This paper briefly summarizes the recent research progresses of electron-scale physics in magnetic reconnection based on the observational results of MMS. We divided the reconnection region into the electron diffusion region, ion diffusion region and reconnection exhaust, and summarized the electron scale physical processes from many aspects. The main contents are as follows: The electron diffusion region can form a multiple structure in the inflow or outflow direction, and its formation process may involve a variety of instabilities; The crescent distribution in the electron diffusion region is affected by many factors, such as Hall electric field and electron meandering motion, so that the electron distribution function in this region no longer presents a crescent distribution in some cases; Plasma waves in the electron diffusion region can effectively heat electrons and provide anomalous resistance to break the frozen-in conditions, which plays a key role in reconnection; The non-ideal electric field in the electron diffusion region can be balanced by the electron pressure tensor term, but the anomalous resistance term may dominate in some events; The formation and evolution of electron scale coherent structures in the ion diffusion region are very important for energy conversion and dissipation, including the turbulence driven by the merging of magnetic islands, the secondary reconnection triggered by Kelvin-Helmholtz instability and the formation of kinetics scale magnetic holes; The coalescence of magnetic flux ropes and the magnetic reconnection between the magnetic flux ropes and the geomagnetic field in the reconnection exhaust can release the magnetic energy through multi-scale coupling, and the generation of high-energy electrons can be excited in the magnetic flux ropes through a variety of acceleration mechanisms; Near the reconnection front, there are often various plasma instabilities and strong current structures, which play an important role in the release of magnetic energy. In addition, we briefly discuss the triggering mechanism of magnetic reconnection at the electron-scale, such as the electron-only reconnection in turbulence and reconnection driven by electron kinetics in the magnetotail. Finally, we discuss the importance of multi-scale coupling in magnetic reconnection and some key open questions.

Starch is an essential factor affecting the quality of flue-cured tobacco, and high starch content can affect the sensory quality and safety. Recently, the degradation of macromolecules in tobacco raw materials by using additional microorganisms to improve their intrinsic quality and safety has become a new research hotspot in the tobacco industry. However, the technical maturity and application scale are limited. Our study analyzed the correlation between microbial community composition and volatile components on the surface of tobacco leaves from 14 different grades in Fujian tobacco-producing areas. The PICRUSt software was utilized to predict the function of the microbial community present in tobacco leaves. Furthermore, dominant strains that produced amylase were screened out, and an enzyme solution was prepared to enhance the flue-cured tobacco flavor. Changes in the content of macromolecules and volatile components were determined, and sensory evaluations were conducted to assess the overall quality of the tobacco leaves. The results showed that the dominant bacterial genera on the surface of Fujian tobacco leaves were Variovorax, Sphingomonas, Bacillus, etc. Bacillus was positively correlated with various volatile components, which contributed to the sweet and aromatic flavors of Fujian flue-cured tobacco. The main genetic functions of Fujian flue-cured tobacco surface bacteria were carbohydrate metabolism and amino acid metabolism. After treating flue-cured tobacco with an enzyme preparation prepared by the fermentation of Paenibacillus amylolyticus A17 #, the content of starch, pectin, and cellulose in flue-cured tobacco decreased significantly compared with the control group. Meanwhile, the content of total soluble sugar and reducing sugar was significantly increased, and the volatile aroma components, such as 3-hydroxy--damascone, 2,3-dihydro-3,5-dihydroxy-6-methyl-4 H-Pyran-4-one, ethyl palmitate, ethyl linolenic acid, etc., were significantly increased. The aroma quality and quantity of flue-cured tobacco were enhanced, while impurities were reduced. The smoke characteristics were improved, with increased fineness, concentration, and moderate strength. The taste characteristics were also improved, with reduced irritation and a better aftertaste. In conclusion, Bacillus, as the dominant genus in the abundance of bacterial communities on tobacco surfaces in Fujian, had an essential impact on the flavor of tobacco leaves by participating in carbohydrate metabolism and finally forming the unique flavor style of flue-cured tobacco in Fujian tobacco-producing areas. Paenibacillus amylolyticus A17 #, a target strain with amylase-producing ability, was screened from the surface of Fujian flue-cured tobacco. The enzyme preparation, produced by the fermentation of Paenibacillus amylolyticus A17 #, was utilized to reduce the content of macromolecules, increase the content of water-soluble total sugar and reducing sugar, and produce a variety of crucial volatile aroma components, which had a significant improvement on the quality of tobacco leaves.

Magnetic reconnection and turbulence are two of the most significant mechanisms for energy dissipation in collisionless plasma. The role of turbulence in magnetic reconnection poses an outstanding problem in astrophysics and plasma physics. It is still unclear whether turbulence can modify the reconnection process by enhancing the reconnection rate or energy conversion rate. In this study, utilizing unprecedented high-resolution data obtained from the Magnetospheric Multiscale spacecraft, we provide direct evidence that turbulence plays a vital role in promoting energy conversion during reconnection. We reached this conclusion by comparing magnetotail reconnection events with similar inflow Alfvén speed and plasma β but varying amplitudes of turbulence. The disparity in energy conversion was attributed to the strength of turbulence. Stronger turbulence generates more coherent structures with smaller spatial scales, which are pivotal contributors to energy conversion during reconnection. However, we find that turbulence has negligible impact on particle heating, but it does affect the ion bulk kinetic energy in these two events. These findings significantly advance our understanding of the relationship between turbulence and reconnection in astrophysical plasmas.

A bound state in the continuum (BIC) is a wave that coexists with a continuous wave but remains localized. In the terahertz band, BIC can design devices with an ultra-high mass factor (Q factor), which is of great value for terahertz science and technology, so we designed a terahertz BIC metasurface structure composed of metal split ring resonators (SRRs). According to the symmetric protection principle of superlattice mode, the leakage process of BIC states to the far field is studied by changing the gap width of SRR. By introducing multiple SRRs and changing their arrangement, we obtain three superlattice modes and BIC states. The leakage of BIC states into the far field is observed experimentally, which means that observable quasi-BIC patterns are formed. We verify a feasible method that allows for flexible design and implementation of BIC.

IntroductionPrevious studies reported that fucose plays a protective role in inhibiting pathogens. Fusobacterium nucleatum (Fn) was recently found to promote the progression of colitis. However, the effects of fucose on Fn are poorly understood. This study aimed to explore whether fucose could ameliorate the proinflammatory property of Fn in colitis and the underlying mechanisms.MethodsTo validate our hypothesis, mice were administrated with Fn and fucose-treated Fn (Fnf) before dextran sulfate sodium (DSS) treatment to establish Fn related colitis model. The metabolism variation of Fn was detected by metabolomic analysis. To verify the effects of bacterial metabolites on intestinal epithelial cells (IECs), Caco-2 cells were treated with bacterial supernatant.ResultsMore severe inflammation, intestinal barrier damage, autophagy block, and apoptosis in the colon were noted in DSS mice that were administrated with Fn or Fnf. However, the severity degree in Fnf+DSS group was less compared to Fn+DSS group. Metabolic pathways of Fn were altered after fucose treatment and proinflammatory metabolites were decreased. The supernatant of Fnf induced a lower level of inflammation than Fn in Caco-2 cells. One of the decreased metabolites, homocysteine thiolactone (HT), was proven to induce inflammatory effects in Caco-2 cells.DiscussionIn conclusion, fucose ameliorates the proinflammatory property of Fn via altering its metabolism and these findings provide evidence for the application of fucose as functional food or prebiotic in the treatment of Fn related colitis.

Abstract The exohiss waves are hiss‐like whistler mode waves that occur outside plasmapause. Although these waves can cause the loss of radiation belt electrons ∼

In metasurface design, massive meta-atoms have to be optimized to produce the desired properties, which are time-consuming and sometimes prohibitive. In this paper, neural network model composed forward modeling and inverse design network is proposed to realize rapid, efficient, and automatic metasurface design of THz unidirectional transmission. Specifically, massive metasurface samples are generated by Python-CST co-simulation to train the neural network model and make it robust to predict the THz responses and vice versa. The consistency of simulation and prediction results imply that the model can accurately capture the nonintuitive complex relationship between structural parameters and electromagnetic spectra. To further verify the model, retrieved structural parameters for unidirectional transmission are deduced due to inverse design network and double L-shape arrays metasurface is experimental fabricated. It is shown that the experimental asymmetric transmission responses by retrieved structural parameters are identical with the simulations by design parameter. Such results effectively verify the design and model, providing a paradigm for functional metasurface design and the development of applications in optoelectrical fields.

Abstract How particles are being energized by turbulent electromagnetic fields is an outstanding question in plasma physics and astrophysics. This paper investigates the electron acceleration mechanism in strong turbulence (δB/B0 ∼ 1) in the Earth's magnetosheath based on the novel observations of the Magnetospheric Multiscale mission. We find that electrons are magnetized in turbulent fields for the majority of the time. By directly calculating the electron acceleration rate from Fermi, betatron mechanism, and parallel electric field, it is found that electrons are primarily accelerated by the parallel electric field within coherent structures. Moreover, the acceleration rate by parallel electric fields increases as the spatial scale reduces, with the most intense acceleration occurring over about one ion inertial length. This study is an important step toward fully understanding the turbulent energy dissipation in weakly collisional plasmas.

In the era of big data, all‐optical control of the magnetization is recognized as an alternative scheme that boosts the accelerating advance of multifunctional integrated opto‐magnetization devices with high‐density capacity. The light‐induced magnetizations demonstrated so far are devoted to steering their spatial orientations and structures by engineering the complicated phase, amplitude, and polarization modulations of incident wavefronts, which, however, confront low efficiency, weak flexibility, and limited dimension. To tackle these issues efficaciously, a novel strategy is proposed to first achieve 5D opto‐magnetization composed of 3D spatial location, vectorial orientation as well as magnitude. This relies on physics‐enhanced deep learning incorporating multilayer perceptron (MLP) artificial neural network and opto‐magnetization principles. The preeminent magnetization morphology largely expedites the improvement in multi‐dimensional storage. The proposed facile approach is time‐efficient, flexible, and accurate to attain the prescribed magnetization. Moreover, the presenting findings and proposed route are not only applied for magnetization manipulation, but also applicable to the control of the structured light field.

Abstract Magnetosonic waves (MSWs) can be discrete or continuous in a time‐frequency spectrogram. For discrete MSWs that satisfy the Chirikov resonance overlap criterion (CROC), the spectrum can be regarded as continuous and hence the quasi‐linear theory can be employed to calculate the corresponding electron diffusion coefficient; otherwise, the contribution of each harmonic emission to the diffusion coefficient should be calculated separately. From the Van Allen Probe‐A (RBSP‐A) burst mode observations taken between January 2014 to December 2017, a total of 21,766 discrete MSW events were selected for statistical analysis, among which 314 events (1.44%) are found to not satisfy the CROC. The MSW events not satisfying the CROC are mainly distributed in the range between L ∼ 4 and 6 outside the plasmapause, they all have a frequency gap (e.g., a frequency difference ≥2 fcH between two discrete bands).

Abstract In the recent couple of decades, some multifunctional spaceborne active radars had been launched. Those radars used to be broadband radars using dipole transmitting antennas. The odd‐order resonant frequency of the antenna does not completely cover the operating frequency of the entire radar, so this may cause the antenna's radiation efficiency to deteriorate. The typical method to solve this problem was to design an impedance matching network system for broadband antennas to achieve a good voltage standing wave ratio and transmit power gain. In this paper, a new optimized real‐frequency method was designed, and a 0.4‐meter dipole antenna was tested before and after impedance matching. The measured results showed that the impedance matching network obtained by the optimized real‐frequency method proposed in this paper can improve the antenna radiation efficiency, and can effectively reduce the standing wave ratio to avoid damage to the transmitter caused by high echo power.

Abstract Background During the biomass-to-bio-oil conversion process, many studies focus on studying the association between biomass and bio-products using near-infrared spectra (NIR) and chemical analysis methods. However, the characterization of biomass pyrolysis behaviors using thermogravimetric analysis (TGA) with support vector machine (SVM) algorithm has not been reported. In this study, tobacco was chosen as the object for biomass, because the cigarette smoke (including water, tar, and gases) released by tobacco pyrolysis reactions decides the sensory quality, which is similar to biomass as a renewable resource through the pyrolysis process. Results SVM algorithm has been employed to automatically classify the planting area and growing position of tobacco leaves using thermogravimetric analysis data as the information source for the first time. Eighty-eight single-grade tobacco samples belonging to four grades and eight categories were split into the training, validation, and blind testing sets. Our model showed excellent performances in both the training and validation set as well as in the blind test, with accuracy over 91.67%. Throughout the whole dataset of 88 samples, our model not only provides precise results on the planting area of tobacco leave, but also accurately distinguishes the major grades among the upper, lower, and middle positions. The error only occurs in the classification of subgrades of the middle position. Conclusions From the case study of tobacco, our results validated the feasibility of using TGA with SVM algorithm as an objective and fast method for auto-classification of tobacco planting area and growing position. In view of the high similarity between tobacco and other biomasses in the compositions and pyrolysis behaviors, this new protocol, which couples the TGA data with SVM algorithm, can potentially be extrapolated to the auto-classification of other biomass types.

Electron density (or electron concentration) is a critical metric for characterizing the ionosphere’s mobility. Shortwave technologies, remote sensing systems, and satellite communications—all rely on precise estimations of electron density in the ionosphere. Using electron density profiles from FORMOSAT-3/COSMIC (Constellation Observation System for Meteorology, Ionosphere, and Climate) from 2006 to 2013, a four-dimensional physical grid model of ionospheric electron density was created in this study. The model, known as EDG-DNN, utilizes a DNN (deep neural network), and its output is the electron density displayed as a physical grid. The preprocessed electron density data are used to construct training, validation, and test sets. The International Reference Ionosphere model (IRI) was chosen as the reference model for the validation procedure since it predicts electron density well. This work used the IRI-2016 version. IRI-2016 produced more precise results of electron density when time and location parameters were input. This study compares the electron density provided by IRI-2016 to the EDG-DNN to assess the merits of the latter. The final results reveal that EDG-DNN has low-error and strong stability, can represent the global distribution structure of electron density, has some distinctive features of ionospheric electron density distribution, and predicts electron density well during quiet periods.

The process and mechanism of gold mineralization are frontier issues. The Dunbasitao deposit is the most important gold deposit discovered along the Armantai suture zone, East Junggar, NW China, which indicates the potential for future ore exploration in this area. Orebodies are mainly hosted in Lower Carboniferous Jiangbasitao Formation volcano-sedimentary rocks, and the ores are characterized by multistage pyrites. Based on microscopy and backscattered electron imaging studies, pyrites are classified into five types: the pre-ore framboidal/colloidal Py0; the early-stage coarse-grained, cubic, and homogeneous Py1; and the middle-stage fine-grained, cubic/pyritohedron Py2 that includes Py2a (core), Py2b (mantle), and Py2c (rim). The results of the EPMA and in situ LA-ICP-MS analyses show that trace elements of pyrite mainly occur in two forms: solid solutions and invisible or visible inclusions. Mn, Co, Ni, and As enter the pyrite lattice, whereas Ti occurs as mineral inclusions, and Au, Cu, Zn, Sb, and Pb can occur in both forms. Au and As show a positive linear relationship with r = 0.850. Py2b has much higher Au contents (20.1 to 201 ppm) than other pyrite types (Py0: 0.01 to 0.36 ppm; Py1: 0.01 to 0.02 ppm; Py2a: 0.31 to 2.48 ppm; and Py2c: 0.18 to 18.0 ppm). The Dunbasitao deposit is classified as an orogenic gold deposit using the two latest machine learning classifiers based on pyrite trace element data. Fluid immiscibility, sudden cooling, and the substitution of S1− with As1− might be crucial mechanisms leading to Au precipitation. Initial ore-forming fluids brought major amounts of As, Au, Co, Ni, Se, Zn, Ag, Cd, Sn, and other elements, and the Jiangbasitao Formation host rocks contributed a certain amount of As, Ni, Cu, Sb, Pb, and Bi, at least.

The Larmor electric field (LEF) was previously suggested as a signature to identify the diffusion region in asymmetry reconnection. Using 2.5D particle-in-cell simulations, we show that the LEF also exists in symmetric reconnection, manifested as a transient structure upstream of the Hall electric field. The LEF emerges during the rapid growth phase of the reconnection rate and has opposite polarity to the Hall field. The half-width of the current sheet spontaneously decreases to the electron scale as the evolution of reconnection, which gives rise to the LEF. The current sheet later thickens to maintain the fast reconnection rate, which causes the disappearance of the LEF. We further find that the magnitude of LEF is sensitive to the initial half-width current sheet, the background plasma temperature and density, the guide-field strength, and the ion–electron mass ratio. Our results provide new insight into the dynamics around the diffusion region. The LEF can help satellites not only locate the diffusion region but also identify the onset phase of reconnection in the magnetotail.

The behavior of the Martian ionosphere during global dust storms has always been a popular topic. Based on many Mars Atmosphere and Volatile Evolution observations, a Martian ionospheric electron density model is constructed herein using a physical-grid deep neural network algorithm. The precision of the model is proved to be high, and the R ^2 value of the test set is 0.979. On this basis, the effects of global dust storms on the electron density and peak height of the Martian ionosphere are explored. The results show that the MY34 global dust storm significantly raised the peak height of the Martian electron layer, and its effects mainly ranged from 20°N to 55°N. The periodicity of the global daily average peak electron layer height following this dust storm was more regular than that before the dust storm.

Solar eruptions and the solar wind are sources of space weather disturbances, and extreme-ultraviolet (EUV) observations are widely used to research solar activity and space weather forecasts. Fengyun-3E is equipped with the Solar X-ray and Extreme Ultraviolet Imager, which can observe EUV imaging data. Limited by the lower resolution, however, we research super-resolution techniques to improve the data quality. Traditional image interpolation methods have limited expressive ability, while deep-learning methods can learn to reconstruct high-quality images through training on paired data sets. There is a wide variety of super-resolution models. We try these three representative models: Real-ESRGAN combined with generative adversarial networks, residual channel-attention networks (RCAN) based on channel attention, and SwinIR, based on self-attention. Instruments on different satellites differ in observation time, angle, and resolution, so we selected Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) 193 Å images with similar wavelengths as a reference and used a feature-based method for image registration to eliminate slight deformations to build training data sets. Finally, we compare the above methods in their evaluation metrics and visual quality. RCAN has the highest peak signal-to-noise ratio and structural similarity evaluation. Real-ESRGAN model is the best in the Learned Perceptual Image Patch Similarity index, and its results visually show that it has more highly detailed textures. The corrected super-resolution results can complement the SDO/AIA data to provide solar EUV images with a higher temporal resolution for space weather forecasting and solar physics research.

We study the energy conversion in the turbulent region (TR) downstream of the reconnection front (RF) via 2.5D particle-in-cell simulations. Our study shows that most magnetic energy is transferred into plasma in the exhaust region (ER) and the TR downstream of the RF; the latter is formed due to the electron Kelvin–Helmholtz instability (KHI). Unlike the energy conversion in the ER, the energy conversion in the TR is mainly balanced by its in-plane component ( E _x J _x + E _z J _z ). We further find that the time evolution of the integrated energy conversion in the TR is strongly correlated with the time evolution of the electron KHI and secondary reconnection. The KHI feeds on the electron kinetic energy to grow, and electron vortices are formed, correspondently. The energy is transferred to ions through a nonideal electric field associated with those electron vortices after the KHI is well developed. Finally, the electron vortices are collapsed due to the secondary reconnection among those vortices. The power law of the magnetic energy spectra also shows a slope near −5/3 at wavenumbers larger than the ion scale when the KHI is fully developed.

In order to obtain high cost-effective coating materials working in chlorine-containing environment at high temperature, a 904L super austenitic alloy modified by an AlFeNiMoNb alloy (904L:AlFeNiMoNb) was obtained by vacuum arc melting process. The 904L:AlFeNiMoNb high-entropy alloy has a similar phase component with the AlFeNiMoNb alloy, but a more homogenous microstructure than that of the AlFeNiMoNb alloy. High-temperature chloride corrosion tests for 904L, AlFeNiMoNb, and 904L:AlFeNiMoNb high-entropy alloy were carried out under N2–2.6 vol.% CO2–1.3 vol.% O2–2,700 vppm HCl gaseous environment at 700°C and 800°C for 55 h, respectively. Due to the volatilization of FeCl2, weight change curves of the 904L alloy at 700°C and 800°C showed obvious weight loss. Especially at 800°C, the weight loss of the corroded 904L sample was 10 times that of the corroded sample at 700°C. Different from the weight loss situation of the 904L sample, both AlFeNiMoNb and 904L:AlFeNiMoNb high-entropy alloy showed small weight gains under the corrosion temperature of 700°C, while the latter gained half as much weight as the former. When the corrosion temperature was raised to 800°C, the AlFeNiMoNb and 904L:AlFeNiMoNb high-entropy alloy showed flat weight change curves with little weight loss. Weight loss for the AlFeNiMoNb and 904L:AlFeNiMoNb high-entropy alloy were 1.35138 and 0.0118 mg/cm2, respectively. The high temperature chloride corrosion resistance of 904L:AlFeNiMoNb high-entropy alloy is higher than that of 904L and AlFeNiMoNb at both 700°C and 800°C. Meanwhile, on the basis of the morphology and composition results of the corroded samples, combined with thermodynamic calculation, the high-temperature chloride corrosion mechanics of the tested alloys were discussed.

Lung cancer is a leading fatal malignancy in humans. p53 mutants exhibit not only loss of tumor suppressor capability but also oncogenic gain-of-function, contributing to lung cancer initiation, progression and therapeutic resistance. Research shows that p53 mutants V157F and R158L occur with high frequency in lung squamous cell carcinomas. Revealing their conformational dynamics is critical for developing novel lung therapies. Here, we used all-atom molecular dynamics (MD) simulations to investigate the effect of V157F and R158L substitutions on the structural properties of the p53 core domain (p53C). Compared to wild-type (WT) p53C, both V157F and R158L mutants display slightly lesser β-sheet structure, larger radius of gyration, larger volume and larger exposed surface area, showing aggregation-prone structural characteristics. The aggregation-prone fragments (residues 249–267 and 268–282) of two mutants are more exposed to water solution than that of WT p53C. V157F and R158L mutation sites can affect the conformation switch of loop 1 through long-range associations. Simulations also reveal that the local structure and conformation around the V157F and R158L mutation sites are in a dynamic equilibrium between the misfolded and properly folded conformations. These results provide molecular mechanistic insights into allosteric mechanisms of the lung-enriched p53 mutants.

Previous studies suggest that dipolarization fronts (DFs) are 1 to 3RE (RE is the earth radius) wide in the dawn-dusk direction. Recent kinetic simulations have found that DFs may break up into small-scale structures after they are produced by reconnection. Motivated by this simulation, we revisited the scale size of DFs in the dawn-dusk direction by using Cluster observations during the years when the inter-distance among Cluster spacecraft was between 1000 and 2000 km. We selected the DFs that were detected by more than one spacecraft and estimated the radii of these DFs by a simple geometrical analysis, which is based on comparison of DF normals observed by different spacecraft. We found a few DFs that were only a few ion inertial lengths in the dawn-dusk direction. These results point out the importance of multi-scale coupling during the evolution of DFs.

Yunnan province harbours substantial genetic, cultural and linguistic diversity, with the largest number of Aborigines in China, but the relationship among these Aborigines remains enigmatic. This study genotyped 45 Y chromosomal single nucleotide polymorphisms (SNPs) of 500 males from two aboriginal cross-border populations, Jingpo and Dai, from Dehong, Yunnan. It is reported that Haplogroup O2a2b1a1-M117 is the dominant lineage in both Jingpo and Dai. The Jingpo people show affinity with Tibeto-Burman speaking populations with a relatively high frequency of Haplogroup D-M174, and the Dai people are generally genetically similar with Tai-Kadai speaking populations with high frequencies of Haplogroup O1a-M119 and O1b1a1a-M95, which is consistent with their language classification.

The Liushuping deposit, located on the northeast margin of the Bikou Block, is the middle-sized gold-zinc deposit (with ore reserves of 15.67 × 104 t Zn and 2.2 t Au) in the Mianxian–Lueyang–Yangpingguan area. The orebodies occur in the meta-dolomite of the Duantouya and Jiudaoguai formations controlled by the Jiudaoguai syncline. The ore-forming process has experienced hydrothermal period and epigenetic oxidation period, and the hydrothermal period can be divided into two stages. The hydrothermal sericite sample collected from stage 2 yielded a well-defined 40Ar/39Ar isotopic plateau age of 215.70 ± 0.37 Ma, and an 39Ar/36Ar-40Ar/36Ar normal isochron age of 215.35 ± 0.38 Ma, indicating that the metallogenic age of the Liushuping is the Late Triassic (ca. 215 Ma). The ISr(t) of sphalerite is higher than that of the Bikou Group but similar to the Duantouya Formation, indicating that the ore-forming fluids may mainly originate from the metamorphic dehydration of the Duantouya Formation. The Liushuping Au–Zn deposit is consistent with that of the Qinling Indosinian orogeny and mineralization, which are related to oceanic subduction during the Late Triassic.

A valley-Hall-like photonic insulator based on C3v Kagome split-ring is proposed. Theoretical analysis and numerical calculations illustrate that C3v symmetry can be broken not only by global rotation α but also individual rotation θ of the split rings, providing topological phase transitions. Furthermore, refraction of the edge state from the interface into the background space at Zigzag termination is explored. It is shown that positive/negative refraction of the outgoing beam depends on the type of valley (K or K′), from which the edge state is projected. These results provide a new way to manipulate terahertz wave propagation and facilitate the potential applications in directional collimation, beam splitting, negative refraction image, etc.

Communication blackout is always a serious threat to the flight tasks of modern hypersonic vehicles moving in near space. EHF communication is considered as a potential solution to the blackout problem. Nevertheless, EHF waves suffer from severe attenuation in hypersonic plasma sheaths. An external magnetic field could mitigate EHF wave attenuation in hypersonic plasma sheaths. Dipole magnetic fields, generated by coils, are feasible in realistic scenarios. In the present study, a model for EHF wave propagation in hypersonic plasma sheaths magnetized by dipole magnetic fields that are generated with coils is developed. The dissipation caused by the inhomogeneity of dipole magnetic fields and the magnetic field component of electromagnetic waves are compared with the dissipation yielded by the collision between electrons and neutral particles. The results show that collision is still the main dissipation mechanic for EHF waves. The study also found that, in the blunt-coned plasma sheath, the mitigation effect of a dipole magnetic field is weaker than that of a uniform magnetic field. The mechanics which yield the difference is analyzed. In addition, the relation between the characteristics of EHF waves and the coil parameters is investigated. Suggestions for the coil parameters and the operation frequencies of the EHF communication systems are made based on the investigation.

To investigate the characteristics of regions exhibiting multiple lightning initiations within a finite volume and a short time, the lightning location data obtained from the convective regions of 14 mesoscale convective systems were analyzed in combination with data from radar. In total, 415 out of 5996 radar grids (1 km × 1 km × 0.5 km) were found to initiate more than one flash within 6 min. Only 49 grids showed an initiation density of more than two flashes within 6 min. The grids with high flash initiation densities were found to have a similar distribution to those with one lightning initiation within 6 min, in terms of altitude and reflectivity relative to altitude. They also showed similar trends in their frequency evolution. The grids with higher initiation densities seemed to be more concentrated in the altitude range of 9–13 km. However, only one was found to form at a lower altitude near the melting level when lightning initiation clearly declined. Moreover, the spatial relationship of this lower higher-initiation density grid to the reflectivity core was different to that in the main altitude range. In this paper, the possible dynamic and electrical mechanisms of the formation of this lower higher-initiation density grid are discussed.

Abstract A microwave one-way waveguide of three-dimensional configuration is proposed and investigated theoretically. In this waveguide there exists a complete one-way propagation band, where the mode propagates only in one direction and can be immune to backscattering. By terminating the one-way waveguide with metal slab, one-way propagating waves in this waveguide system can be stopped at the terminal end without any backscattering. Meanwhile, a hotspot with extremely enhanced magnetic-field amplitude is generated in this 3D waveguide system. For an incident microwave pulse, the trapped wave packet can be compressed to deep subwavelength scale besides the magnetic field enhancement. Moreover, the magnetic field enhancement of trapped waves can be further largely increased by tapering laterally the waveguide system. The approach for trapping microwaves has promising applications in magnetic sensing and magnetic non-linearity.

We experimentally demonstrate that high-resolution terahertz focusing can be realized in planar metalenses, which consist of arrays of different V-shaped antenna units on a silicon substrate. Numerical results show that a larger numerical aperture of metalenses can provide smaller full width at half maximum of field distribution, leading to higher spatial resolution. The measurement of fabricated metalenses samples was performed by a terahertz near-field imaging system, and experimental results agree well with the numerical prediction. Especially for 1.1 THz incident light, when the numerical aperture increases from 0.79 to 0.95, the full width at half maximum correspondingly decreases from 343 μm to 206 μm, offering an improvement of spatial resolution.

Inter-annual variation of meteorological conditions and their effects on snow and ice thickness in an Arctic lake Unari (67.14° N, 25.73° E) were investigated for winters 1980/1981–2012/2013. The lake snow and ice thicknesses were modelled applying a thermodynamic model, and the results were compared with observations. Regression equations were derived for the relationships between meteorological parameters and modelled snow and ice properties. The composite differences of large-scale atmospheric circulation patterns between seasons of thin and thick ice were analysed. The air temperature had an increasing trend (statistical significance p

In an integrated radar-communication network, multiuser access techniques with minimal performance degradation and without range-Doppler ambiguities are required, especially in a dense user environment. In this paper, a multiuser access scheme with random subcarrier allocation mechanism is proposed for orthogonal frequency division multiplexing (OFDM) based integrated radar-communication networks. The expression of modulation Symbol-Domain method combined with sparse representation (SR) for range-Doppler estimation is introduced and a parallel reconstruction algorithm is employed. The radar target detection performance is improved with less spectrum occupation. Additionally, a Doppler frequency detector is exploited to decrease the computational complexity. Numerical simulations show that the proposed method outperforms the traditional modulation Symbol-Domain method under ideal and realistic nonideal scenarios.

Virtual-force algorithms (VFAs) have been widely studied for accurate node deployment in wireless-sensor-network (WSN) applications. Their main purpose is to achieve the maximum coverage area with the minimum number of sensor nodes in the target area. Recently, we reported a new VFA based on virtual spring force (VFA-SF) and discussed in detail the corresponding efficiency via statistical analysis. The optimized strategy by adding an external central force (VFA-SF-OPT) was presented, which effectively eliminates the coverage hole or twisted structure in the final network distribution. In this paper, the parameter effects on VFA-SF and the VFA-SF-OPT were further investigated: (1) Node velocity dramatically affects the convergence rate of the node-deployment process. (2) A suitable external central force improves equilibrium distance and reduces energy consumption. (3) The effects of VFA-SF and VFA-SF-OPT for different types of obstacles are discussed. Generally, by choosing suitable parameters, both VFA-SF and VFA-SF-OPT can effectively improve node deployment and energy consumption for the whole sensor network. The results give important insight in parameter selection and information fusion in the application of a large-scale WSN.

How to effectively deploy all wireless sensors and save a system’s energy consumption is a key issue in current wireless sensor network (WSN) applications. Theoretical analysis has proven that a hexagonal structure is the best topology in the two-dimensional network, which can provide the maximum coverage area with the minimum number of sensor nodes and minimum energy consumption. Recently, many scientists presented their self-deployment strategies based on different virtual forces and discussed the corresponding efficiency via several case studies. However, according to our statistical analysis, some virtual force algorithms, e.g., virtual spring force, can still cause holes or twisted structure in a small region of the final network distribution, which cannot achieve the ideal network topology and will waste the system energy in real applications. In this paper, we first statistically analyzed the convergence and deployment effect of the virtual spring force algorithm to derive our question. Then we presented an optimized strategy that sensor deployment begins from the center of the target region by adding an external central force. At the early stage, the external force will be added to the most peripheral nodes to promote the formation of hexagonal topology and avoid covering holes or unusual structure. Finally, a series of independent simulation experiments and corresponding statistical results proved that our optimized deployment solution is very stable and effective, which can improve the energy consumption of the whole sensor network and be used in the application of a large scale WSN.

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Mobile sensor networks are an important part of modern robotics systems and are widely used in robotics applications. Therefore, sensor deployment is a key issue in current robotics systems research. Since it is one of the most popular deployment methods, in recent years the virtual force algorithm has been studied in detail by many scientists. In this paper, we focus on the virtual force algorithm and present a corresponding parameter investigation for mobile sensor deployment. We introduce an optimized virtual force algorithm based on the exchange force, in which a new shielding rule grounded in Delaunay triangulation is adopted. The algorithm employs a new performance metric called ‘pair-correlation diversion', designed to evaluate the uniformity and topology of the sensor distribution. We also discuss the implementation of the algorithm's computation and analyse the influence of experimental parameters on the algorithm. Our results indicate that the area ratio, φ s , and the exchange force constant, G , influence the final performance of the sensor deployment in terms of the coverage rate, the convergence time and topology uniformity. Using simulations, we were able to verify the effectiveness of our algorithm and we obtained an optimal region for the (φ s , G )-parameter space which, in the future, could be utilized as an aid for experiments in robotic sensor deployment.

Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI) and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1) we propose a nonconvex low-rank approximation for reconstructing RSI; (2) we inject reference prior information to overcome over smoothed edges and texture detail losses; (3) on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT) simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR) and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.