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With specific and inherent mRNA cleaving activity, small interfering RNA (siRNA) has been deemed promising therapeutics to reduce the exacerbation rate of asthma by inhibiting the expression and release of proinflammatory cytokines from airway epithelial cells (AECs). To exert the therapeutic effects of siRNA drugs, nano-formulations with high efficiency and safety are required to deliver these nucleic acids to the target cells. Herein, we exploited novel inhaled lipid nanoparticles (LNPs) targeting intercellular adhesion molecule-1 (ICAM-1) receptors on the apical side of AECs. This delivery system is meant to enhance the specific delivery efficiency of siRNA in AECs to prevent the expression of proinflammatory cytokines in AECs and the concomitant symptoms in parallel. A cyclic peptide that resembles part of the capsid protein of rhinovirus and binds to ICAM-1 receptors was initially conjugated with cholesterol and subsequently assembled with ionizable cationic lipids to form the LNPs (Pep-LNPs) loaded with siRNA against thymic stromal lymphopoietin (TSLP siRNA). The obtained Pep-LNPs were subjected to thorough characterization and evaluations in vitro and in vivo. Pep-LNPs significantly enhanced cellular uptake and gene silencing efficiency in human epithelial cells expressing ICAM-1 in vitro, exhibited AEC-specific delivery and improved the gene silencing effect in ovalbumin-challenged asthmatic mice after pulmonary administration. More importantly, Pep-LNPs remarkably downregulated the expression of TSLP in AECs, effectively alleviated inflammatory cell infiltration, and reduced the secretion of other proinflammatory cytokines, including IL-4 and IL-13, as well as mucus production in asthmatic mice. This study demonstrates that Pep-LNPs are safe and efficient to deliver siRNA drugs to asthmatic AECs and could potentially alleviate allergic asthma by inhibiting the overexpression of proinflammatory cytokines in the airway.

Given the extremely preeminent role of students’ learning engagement (LE) in their academic success, investigating the predictors of LE for EFL learners seems critical. Prior research has demonstrated that the external environmental factors (e.g., teacher support) and the internal motivational factors (e.g., self-efficacy, achievement goal orientation) were related to LE, yet the internal mechanism is still under-explored. Therefore, this study attempted to explore the associations between teacher support and LE and the possible underlying mechanism through which teacher support influences LE with individual motivational variables of self-efficacy and achievement goal orientation the mediators for EFL learners in China. A sample of 466 Chinese college EFL learners participated in the study. Results indicated that (1) both academic support and emotional support significantly predicted LE; (2) academic support predicted LE through the separate mediation of self-efficacy, mastery goals and performance-approach goals; whereas emotional support only predicted LE through mastery goals; (3) academic support, but not emotional support, predicted LE through the chain mediation of self-efficacy and mastery goals, self-efficacy and performance-approach goals. These results elucidated the mechanism of different teacher support on LE and provided some implications for promoting EFL learners’ engagement.

Using magnetic field data collected by Mars Atmosphere and Volatile EvolutioN (MAVEN), we investigated the external magnetic field distribution over low crustal field regions in the Martian ionosphere. Both draping and looping magnetic field are observed in the Martian dayside and nightside ionosphere at attitude range 150-600 altitude. Draping magnetic field is formed by the draped interplanetary magnetic field around the ionosphere obstacle, which is formed by the well-known induced magnetosphere current system. Looping magnetic field, observed in both ionosphere and magnetosphere, indicates a new current system coupling the ionosphere and magnetosphere. This new current system, different with the induced magnetosphere current system, has sunward component in the magnetosphere, and tailward component in the low altitude ionosphere. This current system is validated by both MAVEN observation and a global multi-fluid magnetohydrodynamic (MHD) simulation, which is most likely a universal phenomenon for a non-magnetized planetary with ionospheres interacted with high-speed solar wind.

The plasma transport process is important for the ionosphere of Mars, which controls the structure of the ionosphere above an altitude of 200 km. Plasma transport from the dayside ionosphere is crucial for producing the nightside ionosphere on Mars. The alteration in dayside plasma transport in the presence of crustal fields may influence the distribution of Martian ionospheric plasma and plasma escape in the magnetotail. This study employed a three-dimensional multispecies magnetohydrodynamic (MHD) model to simulate Mars-solar wind interactions. We show the magnetic field distribution and plasma velocity variation on the Martian day-side. The results indicate that the ion transport from low- to high-solar-zenith-angle areas in the south is inhibited by crustal fields, leading to a reduction in the ion number density and a thinner ionosphere near the southern terminator. Many heavy ions remain in the southern dayside ionosphere rather than moving to the nightside. In addition, the maximum reduction in the tailward flux of the planetary ions calculated by the MHD simulation is more than 50% at the southern terminator, indicating an inhibitory effect of the crustal fields on day-to-night transport. These effects may lead to a reduction in ion number density in the southern nightside ionosphere. Finally, we demonstrate a decrease in the global heavy-ion loss rate.

In recent years, the joint training of speech enhancement front-end and automatic speech recognition (ASR) back-end has been widely used to improve the robustness of ASR systems. Traditional joint training methods only use enhanced speech as input for the backend. However, it is difficult for speech enhancement systems to directly separate speech from input due to the diverse types of noise with different intensities. Furthermore, speech distortion and residual noise are often observed in enhanced speech, and the distortion of speech and noise is different. Most existing methods focus on fusing enhanced and noisy features to address this issue. In this paper, we propose a dual-stream spectrogram refine network to simultaneously refine the speech and noise and decouple the noise from the noisy input. Our proposed method can achieve better performance with a relative 8.6% CER reduction.

Background. Diabetes mellitus (DM) and dyslipidemia are the main risk factors for atherosclerosis. Elevated glycosylated hemoglobin A1c (HbA1c) and reduced high-density lipoprotein cholesterol (HDL-C) are associated with the progression of atherosclerosis. The aim of this study is at exploring the relationship between the HbA1c/HDL-C ratio and atherosclerosis evaluated using carotid artery intima-media thickness (cIMT) and carotid artery plaque. Methods. In this retrospective study, we enrolled 1304 patients who had multiple cardiovascular risk factors or symptoms of suspected coronary artery disease. cIMT and carotid artery plaque were measured using ultrasonography. Logistic regression was used to explore the correlation between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque. We used restricted cubic spline curves to assess nonlinear relationships between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque. Results. With increased quartiles of HbA1c/HDL-C, patients had higher cIMT and a greater carotid plaque burden. After adjusting for other relevant clinical covariates, patients with the highest HbA1c/HDL-C ratio (quartile 4 (Q4)) had a 2.88 times (95% confidence interval (CI): 2.02–4.10, P < 0.001 ) more abnormal mean cIMT, 3.72 times (95% CI: 2.55–5.44, P < 0.001 ) more abnormal maximum cIMT, and 2.58 times (95% CI: 1.70–3.91, P < 0.001 ) greater carotid artery plaque burden compared with patients who had the lowest HbA1c/HDL-C ratio (Q1). Moreover, the association of HbA1c/HDL-C with atherosclerosis remained significant in a subsample of patients with and without DM. Conclusion. As a novel compound indicator for evaluating blood glucose homeostasis and dyslipidemia, the HbA1c/HDL-C ratio was positively correlated with carotid atherosclerosis evaluated using the mean and maximum cIMT as well as the carotid artery plaque burden.

It has been confirmed that dipolarization fronts (DFs) are the result of the interchange instability in the Earth’s magnetotail. In this paper, we use a Hall MHD model to simulate the evolution of the interchange instability that produces DFs along the leading edge. A test particle simulation is performed to study the physical phenomenon of ion acceleration at the DF. The numerical simulation indicates that almost all particles move earthward and dawnward and then drift to the tail. The DF-reflected ion population at the duskside appears earlier as a consequence of the asymmetric Hall electric field. Ions that are distributed in a dawn-dusk asymmetric semicircle behind the DF tend to be accelerated to higher energies (>13.5 keV). These high-energy particles eventually concentrate in the dawnside. Ions experience effective acceleration by the dawnward electric field, while they drift through the dawn flank at the front, toward the tail.

Predicting the binding of peptide and major histocompatibility complex (MHC) plays a vital role in immunotherapy for cancer. The success of Alphafold of applying natural language processing (NLP) algorithms in protein secondary struction prediction has inspired us to explore the possibility of NLP methods in predicting peptide–MHC class I binding. Based on the above motivations, we propose the MHCRoBERTa method, RoBERTa pre-training approach, for predicting the binding affinity between type I MHC and peptides. Analysis of the results on benchmark dataset demonstrates that MHCRoBERTa can outperform other state-of-art prediction methods with an increase of the Spearman rank correlation coefficient (SRCC) value. Notably, our model gave a significant improvement on IC50 value. Our method has achieved SRCC value and AUC value as 0.785 and 0.817, respectively. Our SRCC value is 14.3% higher than NetMHCpan3.0 (the second highest SRCC value on pan-specific) and is 3% higher than MHCflurry (the second highest SRCC value on all methods). The AUC value is also better than any other pan-specific methods. Moreover, we visualize the multi-head self-attention for the token representation across the layers and heads by this method. Through the analysis of the representation of each layer and head, we can show whether the model has learned the syntax and semantics necessary to perform the prediction task well. All these results demonstrate that our model can accurately predict the peptide–MHC class I binding affinity and that MHCRoBERTa is a powerful tool for screening potential neoantigens for cancer immunotherapy. MHCRoBERTa is available as an open source software at github (https://github.com/FuxuWang/MHCRoBERTa).

Context. The draping of the interplanetary magnetic field (IMF) around unmagnetized planets induces a magnetotail with a two-lobe plasma structure. On Mars, due to the impact of the IMF Parker spiral angle, the structure of its induced magnetotail is dawn-dusk asymmetric. Observational and numerical studies have shown the dawn-dusk asymmetric size of magnetic lobes and the shift of the polarity reversal layer and the inverse polarity reversal layer under different Parker spiral angles. Variation in the tail-region induced magnetic field with the Parker spiral angle is important in the evolution of the magnetotail. Further studies should investigate the influence of the magnetic pressure and field direction on the magnetic lobe structure and plasma boundary locations, as well as the relationship between the polarity reverse of the IMF and the Parker spiral angle. Aims. This study aims to investigate the dawn-dusk asymmetric structure of the Martian magnetotail under different Parker-spiral IMF orientations. In this study, we used a multispecies magnetohydro-dynamic (MHD) model, which has been shown to self-consistently calculate the Mars-solar wind interaction, to investigate the effects of the Parker spiral angle on the structure of the Martian magnetotail. By comparing the magnetic field, large-scale configurations, and plasma boundary locations across various cases, we aim to clarify how variations in the IMF Parker spiral angle affect the magnetic pressure and field direction in the magnetotail and the locations and shapes of the magnetic lobes, polarity reversal layer, and inverse polarity reversal layer. Methods. A three-dimensional and parallelized multispecies MHD model was constructed to simulate the global solar wind interaction with Mars. Four ion species, H+, O2+, O+, and CO2+, as well as the chemical reactions between them, such as photoionization, charge exchange, and recombination, were considered in the model to accurately calculate the ion distributions in the magnetosphere and ionosphere of Mars. Three cases with Parker spiral angles of 90, 56, and 30 degrees were examined, representing the perpendicular, standard, and quasi-parallel IMF relative to the solar wind flow, respectively. Results. A symmetric magnetotail was reproduced in the case with a Parker spiral angle of 90° degrees. When the Parker spiral angle decreases, the magnetic pressure in the magnetic lobes reduces, and the flaring angle of the magnetic field becomes larger on the dawn side than on the dusk side. These two factors result in the shrinkage and extension of the magnetic lobes. Furthermore, the variation in magnetic pressure results in a polarity reversal layer bent toward the dawn side. Finally, we found that the inverse polarity reversal layer shrinks toward Mars with a decrease in the Parker spiral angle.

Worries about the increasing number of Sybils in online social networks (OSNs) are amplified by a range of security issues; thus, Sybil detection has become an urgent real-world problem. Lightweight and limited data-friendly, LBP (Loopy Belief Propagation)-based Sybil-detection methods on the social graph are extensively adopted. However, existing LBP-based methods that do not utilize node attributes often assume a global or predefined homophily strength of edges in the social graph, while different user’s discrimination and preferences may vary, resulting in local homogeneity differences. Another issue is that the existing message-passing paradigm uses the same edge potential when propagating belief to both sides of a directed edge, which does not agree with the trust interaction in one-way social relationships. To bridge these gaps, we present SybilHP, a Sybil-detection method optimized for directed social networks with adaptive homophily prediction. Specifically, we incorporate an iteratively updated edge homophily estimation into the belief propagation to better adapt to the personal preferences of real-world social network users. Moreover, we endow message passing on edges with directionality by a direction-sensitive potential function design. As a result, SybilHP can better capture the local homophily and direction pattern in real-world social networks. Experiments show that SybilHP works with high detection accuracy on synthesized and real-world social graphs. Compared with various state-of-the-art graph-based methods on a large-scale Twitter dataset, SybilHP substantially outperforms existing methods.

Ionospheric chemistry plays an unexpectedly important role in the evolution of planetary habitability. This study is dedicated to a detailed modeling of the nightside Martian ionospheric structure and composition, a topic that has been poorly explored due to the absence of relevant measurements, but now becomes tractable owing to the unprecedented measurements made by the Mars Atmosphere and Volatile Evolution. Two-stream kinetic calculations and time-dependent fluid calculations are coupled to derive the nightside density profiles at 100–300 km for a large number of ion species, assuming solar wind electron precipitation as the only viable ionizing source in the ideal nonmagnetized atmosphere. Our calculations indicate the presence of a well-defined ionospheric peak at 146 km with a peak density of 8500 cm−3, as driven by the strong atmospheric “absorption” of precipitating electrons at low altitudes. The distribution of nonterminal species is roughly under chemical equilibrium below 170 km, whereas for terminal species such as NO+ and HCO+, diffusion is effective at essentially all altitudes, in direct contrast to the dayside behavior. In the more realistic magnetized atmosphere, the ionospheric peak seldom exists due to the patchiness of electron precipitation. In particular, our model results agree fairly well with the MAVEN measurements, especially in view of the coincidence between electron depletion and thermal plasma void seen along many MAVEN orbits. Compared to the dayside, the nightside ionospheric composition has a much higher proportion of NO+ and lower proportion of CO2 +, likely indicative of nightside enhancement of atmospheric O and N.

Significant genetic association exists between rheumatoid arthritis (RA) and cardiovascular disease. The associated mechanisms include common inflammatory mediators, changes in lipoprotein composition and function, immune responses, etc. However, the causality of RA and vascular/heart problems remains unknown. Herein, we performed Mendelian randomization (MR) analysis using a large-scale RA genome-wide association study (GWAS) dataset (462,933 cases and 457,732 controls) and six cardio-cerebrovascular disease GWAS datasets, including age angina (461,880 cases and 447,052 controls), hypertension (461,880 cases and 337,653 controls), age heart attack (10,693 cases and 451,187 controls), abnormalities of heartbeat (461,880 cases and 361,194 controls), stroke (7,055 cases and 454,825 controls), and coronary heart disease (361,194 cases and 351,037 controls) from United Kingdom biobank. We further carried out heterogeneity and sensitivity analyses. We confirmed the causality of RA with age angina (OR = 1.17, 95% CI: 1.04–1.33, p = 1.07E−02), hypertension (OR = 1.45, 95% CI: 1.20–1.75, p = 9.64E−05), age heart attack (OR = 1.15, 95% CI: 1.05–1.26, p = 3.56E−03), abnormalities of heartbeat (OR = 1.07, 95% CI: 1.01–1.12, p = 1.49E−02), stroke (OR = 1.06, 95% CI: 1.01–1.12, p = 2.79E−02), and coronary heart disease (OR = 1.19, 95% CI: 1.01–1.39, p = 3.33E−02), contributing to the understanding of the overlapping genetic mechanisms and therapeutic approaches between RA and cardiovascular disease.

A three-dimensional four species multi-fluid magnetohydrodynamic (MHD) model was constructed to simulate the solar wind global interaction with Mars. The model was augmented to consider production and loss of the significant ion species in the Martian ionosphere, i.e., H+, O2+, O+, CO2+, associated with chemical reactions among all species. An ideal dipole-like local crustal field model was used to simplify the empirically measured Martian crustal field. Results of this simulation suggest that the magnetic pile-up region (MPR) and the velocity profile in the meridian plane are asymmetric, which is due to the nature of the multi-fluid model to decouple individual ion velocity resulting in occurrence of plume flow in the northern Martian magnetotail. In the presence of dipole magnetic field model, boundary layers, such as bow shock (BS) and magnetic pile-up boundary (MPB), become protuberant. Moreover, the crustal field has an inhibiting effect on the flux of ions escaping from Mars, an effect that occurs primarily in the region between the terminator (SZA 90°) and the Sun–Mars line of the magnetotail (SZA 180°), partially around the terminator region. In contrast, near the tailward central line the crustal field has no significant impact on the escaping flux.

The intrinsic magnetic topological insulator MnBi2Te4 has drawn great attention due to its novel quantum states, among which the most promising one is the quantum anomalous Hall effect. However, MnBi2Te4 is a metastable phase with a narrow temperature range for synthesis, which remains a challenge to grow uniform and high quality MnBi2Te4 sample. Large-area MnBi2Te4 thin films are mainly prepared by molecular beam epitaxy so far. Here, we report a highly versatile method for growing crystallized MnBi2Te4 films on amorphous SiO2/Si substrates by magnetron sputtering at room temperature and post-annealing. High-quality MnBi2Te4 films with a c-axis perpendicular to the substrate and low surface roughness are realized. MnBi2Te4 films have an antiferromagnetic Néel temperature of 21 K, with low carrier concentration (2.5 × 1019 cm−3) and decent mobility (34 cm2 V−1s−1). The films reveal ferromagnetic at ground state and a typical spin-flop transition at 2–3 T. This work provides a pathway toward the fabrication of sputtered-MnBi2Te4 devices for electronic and spintronic applications.

This paper proposes a novel pretext task for self-supervised video representation learning by exploiting spatiotemporal continuity in videos. It is motivated by the fact that videos are spatiotemporal by nature and a representation learned to detect spatiotemporal continuity/discontinuity is thus beneficial for downstream video content analysis tasks. A natural choice of such a pretext task is to construct spatiotemporal (3D) jigsaw puzzles and learn to solve them. However, this task turns out to be intractable. We thus propose Constrained Spatiotemporal Jigsaw (CSJ) whereby the 3D jigsaws are formed in a constrained manner to ensure that large continuous spatiotemporal cuboids exist in a shuffled clip to provide sufficient cues for the model to reason about the continuity. With the constrained jigsaw puzzles, instead of solving them directly, which could still be extremely hard, we carefully design four surrogate tasks that are more solvable but meanwhile still ensure that the learned representation is sensitive to spatiotemporal continuity at both the local and global levels. Extensive experiments show that our CSJ achieves state-of-the-art on two downstream tasks across various benchmarks.

Background: Diabetes mellitus (DM) and dyslipidemia are the main risk factors for atherosclerosis. Elevated glycosylated hemoglobin A1c (HbA1c) and reduced high-density lipoprotein cholesterol (HDL-C) are associated with the progression of atherosclerosis. The aim of this study is to explore the relationship between the HbA1c/HDL-C ratio and atherosclerosis evaluated using carotid artery intima-media thickness (cIMT) and carotid artery plaque.Methods: In this retrospective study, we enrolled 1304 patients who had multiple cardiovascular risk factors or symptoms of suspected coronary artery disease. cIMT and carotid artery plaque were measured using ultrasonography. Logistic regression was used to explore the correlation between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque. We used restricted cubic spline curves to assess nonlinear relationships between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque.Results: With increased quartiles of HbA1c/HDL-C, patients had higher cIMT and a greater carotid plaque burden. After adjusting for other relevant clinical covariates, patients with the highest HbA1c/HDL-C ratio (Quartile 4 [Q4]) had a 2.88-times (95% confidence interval [CI]: 2.02–4.10, PConclusions: As a novel compound indicator for evaluating blood glucose homeostasis and dyslipidemia, the HbA1c/HDL-C ratio was positively correlated with carotid atherosclerosis evaluated using the mean and maximum cIMT as well as the carotid artery plaque burden.

As is universally acknowledged, the United States has often been called “a nation of immigrants”. Under the great influence of immigration, there have been many great changes based on racial integration in all aspects of the United States, especially the aspect of culture. This article mainly focuses on five ethnic groups which take the largest percentage of the total number of population in America, analyzing their contribution to the American culture. In the end, the paper will give a further conclusion, summarizing the contributions and ways about ethnic groups to the American culture.

The etiology of non-alcoholic fatty liver disease (NAFLD) involves complex interaction of genetic and environmental factors. A large number of observational studies have shown that hypothyroidism contributes to a high risk of NAFLD. However, the exact causality is still unknown. Due to the progress of genome-wide association study (GWAS) and the discovery of Mendelian randomization (MR), it is possible to explore the causality between the two diseases. In this study, in order to research into the influence of intermediate phenotypes on outcome, nine independent genetic variants of hypothyroidism obtained from the GWAS were used as instrumental variables (IVs) to perform MR analysis on NAFLD. Since there was no heterogeneity between IVs (P= 0.70), a fixed-effects model was used. The correlation between hypothyroidism and NAFLD was evaluated by using inverse-variance weighted (IVW) method and weighted median method. Then the sensitivity test was analyzed. The results showed that there was a high OR (1.7578; 95%CI 1.1897–2.5970;P= 0.0046) and a low intercept (−0.095;P= 0.431). None of the genetic variants drove the overall result (P< 0.01). Simply, we proved for the first time that the risk of NAFLD increases significantly on patients with hypothyroidism. Furthermore, we explained possible causes of NAFLD caused by hypothyroidism.

Protein stability is related to its functional activities, and effect on stability or misfolding could be one of the major disease-causing mechanisms of missense mutations. Here we developed a novel machine learning computational method PremPS, which predicts the effects of single mutations on protein stability by calculating the changes in unfolding Gibbs free energy. PremPS uses only ten evolutionary- and structure-based features and is parameterized on five thousand mutations. Our approach outperforms previous methods and shows a considerable improvement in estimating the effects of mutations increasing protein stability. In addition, PremPS presents an outstanding performance in predicting the pathogenicity of missense mutations using an experimental dataset composed of two thousand non-neutral and neutral mutations. PremPS can be applied to many tasks, including finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. It is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/.Key PointsConsiderable improvement in estimating the effects of mutations increasing protein stability;Comprehensive comparison with other 25 computational methods on different test sets;An outstanding performance in predicting the pathogenicity of missense mutations;PremPS employs only ten distinct features belonging to six categories, and the most important feature describes evolutionary conservation of the site;The webserver allows to do large-scale mutational scanning and takes about ten minutes to perform calculations for one thousand mutations from a normal size protein.

Energetic electron depletions are a notable feature of the nightside Martian upper atmosphere. In this study, we investigate systematically the variations of the occurrence of depletions with both ...

Ion escape from the atmosphere to space is one of the most likely reasons to account for the evolution of the Martian climate. Based on three-dimensional multifluid magnetohydrodynamic simulations, we investigated the impact of the magnetic inclination angle on O+ escape at low altitudes of 275–1000 km under the typical solar wind conditions. Numerical results showed that an outward ion velocity in the direction opposite to the electromagnetic (EM) force results in weak outward flux and leads to ions becoming trapped by the horizontal magnetic field lines at the local horizontal magnetic equator. Much of the EM force can be attributed to the Hall electric force. In the region of high absolute magnetic inclination angle, the outward ion velocity has the same direction as the EM force, which increases the outward flux and causes ions to diffuse upward along open magnetic field lines to higher altitude. In addition, the EM force is mainly provided by the electron pressure gradient force and the motional electric force. Global results for the magnetic inclination angle indicate that the strong crustal field regions in the southern hemisphere are mainly occupied by magnetic field lines with high absolute magnetic inclination angle, while horizontal field lines are dominant in the northern hemisphere, which leads to a higher O+ escape rate in the Martian southern hemisphere than in the northern, from altitudes of 275 to 1000 km. This is a significant advance in understanding the impact and mechanism of the Martian magnetic field directions on ion escape.

Watermarking algorithms that resist geometric combination attacks is currently a trend of research in this field. This paper proposed a geometrically invariant watermarking scheme based on the feature points of resistance to affine transformation. The scheme used Affine Scale Invariant Feature Transform (ASIFT) to detect the feature points of the carrier image and filtrated the established feature points group depending on anti-affine properties. The obtained feature points set obtained better robustness against multiple attacks. As for robustness, we utilized the feature points set to construct the Delaunay tessellation and embedded the watermark information in the histogram of each triangle. Because of the stability of Delaunay tessellation and the basic characteristics of affine transformation, the geometric robustness of the proposed scheme achieved a good effect as was verified in experiments.

Flapping motion of the current sheet (CS) is an important physical process in the Earths magnetotail. The magnetic double-gradient model, which includes both the instability and wave modes, offers a reasonable explanation for the exciting and propagation of the flapping wave. In this paper, we apply an advanced numerical magnetohydrodynamic (MHD) scheme (conservation element and solution element (CESE)-MHD) to simulate the magnetic double-gradient instability in an idealized current sheet that mimics the magnetotail configuration. We initialize the simulations with a numerically relaxed magnetotail equilibrium, in which the normal component of the magnetic field has a tailward gradient. It is confirmed in our simulation that the instability develops in the current layer. The growth rate of the instability yielded from the simulation is very close to the prediction of theory, with a relative deviation of only ten percent. The results demonstrate that the CESE-MHD scheme is very powerful in numerical study of the double-gradient mechanism of the CS flapping mode, and can be used for further investigations of the flapping motion in more realistic CS configurations.

Cadmium (Cd)-contaminated rice (Oryza sativa) in Southern China is a great threat to food security, and the paddy soil remediation is urgently needed to reduce Cd accumulation in rice. Application of biochar could effectively immobilize soil Cd and reduce Cd uptake by rice. Fields that were applied with soil treatments including control and 15 and 30 t ha−1 each hickory nut shell-derived biochar (KC) or maize straw-derived biochar (MC), and grown with two rice varieties (hybrid rice and late japonica rice) were selected for this study. The long-term effect of biochars on decreasing Cd bioavailability in paddy soils was evaluated. The results showed when MC was applied at 15 t ha−1, DTPA-Cd (soil cadmium extracted by diethylenetriamine pentaacetic acid) was reduced by 20.0 and 34.5% in Field A (slightly Cd pollution) and B (moderately Cd pollution), respectively. In Field B, soil DTPA-Cd concentrations with application of 30 t ha−1 biochars were all lower than that of 15 t ha−1 biochar, but there were no significant differences between the two types of biochars. Cd concentration in rice grains and straws of hybrid rice are two times more than those of late japonica rice. Cd bio-concentration factor both of grains and straw was significantly increased by biochar application, which in Field A was higher than that in Field B. Our results suggest that biochars reduce Cd accumulation in rice grains by immobilizing soil Cd. KC has a higher potential in lowering Cd bioavailability than MC. Hybrid rice should be prohibited to cultivate in these areas.

Without the intrinsic magnetic field, the solar wind interaction with Mars can be significantly different from the interaction with Earth and other magnetized planets. In this paper, we investigate how a global configuration of the magnetic structures, consisting of the bow shock, the induced magnetosphere, and the magnetotail, is modulated by the interplanetary magnetic field (IMF) orientation. A 3D multispecies numerical model is established to simulate the interaction of solar wind with Mars under different IMF directions. The results show that the shock size including the subsolar distance and the terminator radius increases with Parker spiral angle, as is the same case with the magnetotail radius. The location and shape of the polarity reversal layer and inverse polarity reversal layer in the induced magnetotail are displaced to the y < 0 sector for a nonzero flow-aligned IMF component, consistent with previous analytical solutions and observations. The responses of the Martian global magnetic configuration to the different IMF directions suggest that the external magnetic field plays an important role in the solar wind interaction with unmagnetized planets.

Using a global magnetospheric MHD model coupled with a kinetic ring current model, we investigate the effects of magnetotail dynamics, particularly the earthward bursty bulk flows (BBFs) produced by the tail reconnection, on the global-scale current systems. The simulation results indicate that after BBFs brake around X = −10 RE due to the dipolar “magnetic wall,” vortices are generated on the edge of the braking region and inside the inner magnetosphere. Each pair of vortex in the inner magnetosphere disturbs the westward ring current to arc radially inward as well as toward high latitudes. The resultant pressure gradient on the azimuthal direction induces region-1 sense field-aligned component from the ring current, which eventually is diverted into the ionosphere at high latitudes, giving rise to a pair of field-aligned current (FAC) eddies in the ionosphere. On the edge of the flow braking region where vortices also emerge, a pair of region-1 sense FACs arises, diverted from the cross-tail duskward current, generating a substorm current wedge. This is again attributed to the increase of thermal pressure ahead of the bursty flows turning azimuthally. It is further found that when multiple BBFs, despite their localization, continually and rapidly impinge on the “wall,” carrying sufficient tail plasma sheet population toward the Earth, they can lead to the formation of a new ring current. These results indicate the important role that BBFs play in bridging the tail and the inner magnetosphere ring current and bring new insight into the storm-substorm relation.

YOLOv3, a target detection algorithm based on deep learning, is widely applied in object recognition, especially in guiding the blind. The existing products of assisting the blind based on YOLOv3 can already achieve high-precision, high-real-time object recognition. But YOLOv3 also has many limitations, such as the inability to measure distances or it’s hard to recognize objects correctly in fog or haze. For these deficiencies, this paper proposes a road barrier monitoring method based on improved YOLOv3, using an image downsampling algorithm based on the dark channel to defog the image, and then with the binocular distance measurement algorithm to calculate the obstacles from the distance of the camera according to the width and height of the obstacles. The experimental results show that the improved product retains the advantages of high accuracy and fast recognition speed of YOLOv3. At the same time, it also owns the new functions of obstacle ranging and bad weather identification. The improved algorithm can meet the requirements of portability, real-time, and practicality of guide products.

Computational methods that predict protein stability changes induced by missense mutations have made a lot of progress over the past decades. Most of the available methods however have very limited accuracy in predicting stabilizing mutations because existing experimental sets are dominated by mutations reducing protein stability. Moreover, few approaches could consistently perform well across different test cases. To address these issues, we developed a new computational method PremPS to more accurately evaluate the effects of missense mutations on protein stability. The PremPS method is composed of only ten evolutionary- and structure-based features and parameterized on a balanced dataset with an equal number of stabilizing and destabilizing mutations. A comprehensive comparison of the predictive performance of PremPS with other available methods on nine benchmark datasets confirms that our approach consistently outperforms other methods and shows considerable improvement in estimating the impacts of stabilizing mutations. A protein could have multiple structures available, and if another structure of the same protein is used, the predicted change in stability for structure-based methods might be different. Thus, we further estimated the impact of using different structures on prediction accuracy, and demonstrate that our method performs well across different types of structures except for low-resolution structures and models built based on templates with low sequence identity. PremPS can be used for finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. PremPS is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/, which allows to do large-scale mutational scanning and takes about four minutes to perform calculations for a single mutation per protein with ~ 300 residues and requires ~ 0.4 seconds for each additional mutation., Author summary The development of computational methods to accurately predict the impacts of amino acid substitutions on protein stability is of paramount importance for the field of protein design and understanding the roles of missense mutations in disease. However, most of the available methods have very limited predictive accuracy for mutations increasing stability and few could consistently perform well across different test cases. Here we present a new computational approach PremPS, which is capable of predicting the effects of single point mutations on protein stability. PremPS employs only ten evolutionary- and structure-based features and is trained on a symmetrical dataset consisting of the same number of cases of stabilizing and destabilizing mutations. Our method was tested against numerous blind datasets and shows a considerable improvement especially in evaluating the effects of stabilizing mutations, outperforming previously developed methods. PremPS is freely available as a user-friendly web server at http://lilab.jysw.suda.edu.cn/research/PremPS/, which is fast enough to handle the large number of cases.

It has been confirmed that dipolarization fronts (DFs) can be a result from the existence of interchange instability in the magnetotail. In this paper, we used a Hall MHD model to simulate the evolution of the interchange instability, which produces DFs on the leading edge. A test particle simulation was performed to study the physical phenomenon of ion acceleration on DF. Numerical simulation indicates that almost all particles move towards the earthward and dawnward and then drift to the tail. The DF-reflected ion population on the duskside appears earlier as a consequence of the asymmetric Hall electric field. Ions, with dawn-dusk asymmetric semicircle behind the DF, may tend to be accelerated to a higher energy (> 13.5 keV). These high-energy particles are eventually concentrated in the dawnside. Ions experience effective acceleration by the dawnward electric field Ey while they drift through the dawn flank of the front towards the tail.

A magnetic reconnection event detected by Cluster is analyzed using three methods: Single-spacecraft Inference based on Flow-reversal Sequence (SIFS), Multispacecraft Inference based on Timing a Structure (MITS), and the First-Order Taylor Expansion (FOTE). Using the SIFS method, we find that the reconnection structure is an X line; while using the MITS and FOTE methods, we find it is a magnetic island (O line). We compare the efficiency and accuracy of these three methods and find that the most efficient and accurate approach to identify a reconnection event is FOTE. In both the guide and nonguide field reconnection regimes, the FOTE method is equally applicable. This study for the first time demonstrates the capability of FOTE in identifying magnetic reconnection events; it would be useful to the forthcoming Magnetospheric Multiscale (MMS) mission.

This paper studies the effective polytropic index in the central plasma sheet (CPS) by using the method of Kartalev et al. (2006), which adopts the denoising technique of Haar wavelet to identify the homogeneous MHD Bernoulli integral (MBI) and has been frequently used to study the polytropic relation in the solar wind. We chose the quiet CPS crossing by Cluster C1 during the interval 08:51:00–09:19:00 UT on 03 August 2001. In the central plasma sheet, thermal pressure energy per unit mass is the most important part in MBI, and kinetic energy of fluid motion and electromagnetic energy per unit mass are less important. In the MBI, there are many peaks, which correspond to isothermal or near isothermal processes. The interval lengths of homogenous MBI regions are generally less than 1 min. The polytropic indexes are calculated by linearly fitting the data of lnp and lnn within a 16 s window, which is shifted forward by 8 s step length. Those polytropic indexes with |R|⩾0.8 (R is the correlation coefficient between lnp and lnn) and p-value⩽0.1 in the homogeneous regions are almost all in the range of [0, 1]. The mean and median effective polytropic indexes with high R and low p-value in homogeneous regions are 0.34 and 0.32 respectively, which are much different from the polytropic index obtained by traditional method ( α trad=−0.15). This result indicates that the CPS is not uniform even during quiet time and the blanket applications of polytropic law to plasma sheet may return misleading value of polytropic index. The polytropic indexes in homogeneous regions with a high correlation coefficient basically have good regression significance and are thus credible. These results are very important to understand the energy transport in magnetotail in the MHD frame.

This paper uses the data of Cluster from 2001 to 2009 to study the polytropic processes of central plasma sheet (CPS) ions. We first adopt the approach of MHD Bernoulli integral (MBI) to identify homogeneous streamflow tubes (quasi-invariant MBI regions) and then calculate the polytropic index of ions for those streamflow tubes whose outward electromagnetic energy ratios δ

Summary Missense mutations may affect proteostasis by destabilizing or over-stabilizing protein complexes and changing the pathway flux. Predicting the effects of stabilizing mutations on protein-protein interactions is notoriously difficult because existing experimental sets are skewed toward mutations reducing protein-protein binding affinity and many computational methods fail to correctly evaluate their effects. To address this issue, we developed a method MutaBind2, which estimates the impacts of single as well as multiple mutations on protein-protein interactions. MutaBind2 employs only seven features, and the most important of them describe interactions of proteins with the solvent, evolutionary conservation of the site, and thermodynamic stability of the complex and each monomer. This approach shows a distinct improvement especially in evaluating the effects of mutations increasing binding affinity. MutaBind2 can be used for finding disease driver mutations, designing stable protein complexes, and discovering new protein-protein interaction inhibitors., Graphical Abstract, Highlights • A new method to predict binding affinity changes upon single and multiple mutations • Improved performance in evaluating the effects of mutations increasing binding affinity • Generation of the structural model of a mutant complex, Protein Folding; Bioinformatics; 3D Reconstruction of Protein

During reconnection, a flux pileup region (FPR) is formed behind a dipolarization front in an outflow jet. Inside the FPR, the magnetic field magnitude and Bz component increase and the whistler-mode waves are observed frequently. As the FPR convects toward the Earth during substorms, it is obstructed by the dipolar geomagnetic field to form a near-Earth FPR. Unlike the structureless emissions inside the tail FPR, we find that the whistler-mode waves inside the near-Earth FPR can exhibit a discrete structure similar to chorus. Both upper band and lower band chorus are observed, with the upper band having a larger propagation angle (and smaller wave amplitude) than the lower band. Most chorus elements we observed are “rising-tone” type, but some are “falling-tone” type. We notice that the rising-tone chorus can evolve into falling-tone chorus within

Mycotaxon is pleased to add a new annotated species distribution list to our 133 previously posted free-access fungae. The 9-page "Diversity of macrofungi in Yushan, Jiangsu, China" by Bing Xu, Haoyu Lu, Donglei Zhao, Wei Wang, and Hong Ji may be downloaded from our website via http://www.mycotaxon.com/mycobiota/index.html

It has been demonstrated that Kelvin–Helmholtz (KH) instability is an essential large-scale mechanism to generate plasma waves along the boundary layers of Venus. In this paper, evolution of KH instability on the Venusian ionopause with the influence of the Hall effect was investigated under Hall magnetohydrodynamic (MHD) simulations. Linear and nonlinear physical behaviors of KH instability with different wavelengths of perturbation, magnetic field configurations, and ion inertial lengths were studied. Numerical results indicate that, for perturbation with short wavelength, the circulation area of matter becomes small and the driving force is weakened. The combined effect of short wavelength and the antiparallel magnetic field leads to longer linear growth time, while the antiparallel magnetic field tends to enlarge the pressure gradient. As for the moderate wavelength of perturbation, the growth rate reaches its peak value, whereas the maximal y component of total kinetic energy increases significantly with the wavelength. Hall MHD simulations indicate that the Hall effect does not change the growth rates for different ion inertial lengths at all. However, the Hall effect has a depression effect on small structures at the nonlinear stage of KH instability.

Ultra high-voltage direct current (UHVDC) transmission projects of ±1100kV have been in design and construction in China, recently. The electromagnetic environment with corona discharge phenomenon of UHVDC transmission lines has been of interest for engineers. It is necessary to control the electric field strength of the sub-conductors of the power lines because the field on the lines has significant impacts on radio interference (RI), audible noise (AN) and ionized electric field on the ground. In this paper, the electric field on the sub-conductor surfaces are analyzed by the charge simulation method (CSM). The configuration of ±1100kV UHVDC power lines are suggested in order to limit the electromagnetic environment nearby, which may provide useful reference for the design of ±1100kV UHVDC transmission lines.

A deep neural network-based image copyright protection scheme is presented. Instead of modifying the images like traditional watermarking methods, the proposed scheme trains a neural network to extract the robust features from image blocks and then classify them to represent the copyright message. First, the original image and its multiple attacked images are divided into nonoverlapping blocks, a part of which will be selected as candidate blocks. Then, the copyright message bits, together with candidate blocks, constitute the training dataset for the network, enabling the trained network to serve as a copyright message extractor. With the proposed scheme, no quality loss will be caused, and moreover, superior robustness can be achieved due to the adaptive robust feature extraction. Our study also offers further insight into the rationalities and considerations in design. Extensive experiments on a wide range of images show that the proposed scheme possesses strong robustness to many attacks, including additive noise corruption, JPEG compression, filtering, and resizing.

In this research effort, numerical simulation of two-dimensional magnetohydrodynamic (MHD) channel is performed and Hall effect is studied. The computational model consists of the Navier-Stokes (N-S) equations coupled with electrical-magnetic source terms, Maxwell equations and the generalized Ohm's law. Boundary conditions for the electrical potential equation considering Hall effect are derived. To start with, the MHD channel with single-pair electrodes is studied and flow of the electric current is in accordance with physical principle. Then the MHD channel with five-pair electrodes is numerically simulated. The results show that the electrical current concentrates on the downstream of the anode and the upstream of the cathode due to Hall effect, and the flow field becomes asymmetrical. At the current value of the magnetic interaction parameter, the electrical-magnetic force affects the flow remarkably, decreasing the outlet Mach number and increasing the outlet pressure; what's more, the flow structure in the channel becomes extremely complex. Performances of MHD channels with continual electrodes and segmented electrodes are compared. The results show that performance of the MHD channel with segmented electrodes is better than that with continual electrodes with the increase of Hall parameter.

A numerical procedure based on a five-wave model associated with non-ideal, low magnetic Reynolds number magnetohydrodynamic (MHD) flows was developed. It is composed of an entropy conditioned scheme for solving the non-homogeneous Navier-Stokes equations, in conjunction with an SOR method for solving the elliptic equation governing the electrical potential of flow field. To validate the developed procedure, two different test cases were used which included MHD Rayleigh problem and MHD Hartmann problem. The simulations were performed under the assumption of low magnetic Reynolds number. The simulated results were found to be in good agreement with the closed form analytical solutions deduced in the present study, showing that the present algorithm could simulate engineering MHD flow at low magnetic Reynolds number effectively. In the end, a flow field between a pair of segmented electrodes in a three dimensional MHD channel was simulated using the present algorithm with and without including Hall effects. Without the introduction of Hall effects, no distortion was observed in the current and potential lines. By taking the Hall effects into account, the potential lines distorted and clustered at the upstream and downstream edges of the cathode and anode, respectively.

A numerical procedure based on a five-wave MHD model associated with non-ideal, low magnetic Reynolds number MHD flows was developed in the present study for analyzing the flow fields in the MHD generator of a MHD bypass scramjet. The numerical procedure is composed of an entropy conditioned scheme for solving the non-homogeneous Navier-Stokes equations, in conjunction with an SOR method for solving the elliptic equation governing the electrical potential. It was found that a separation would take place near the downstream edge of the second electrode, where the local adverse pressure gradient is large, and the core of the flow field is characterized as a 2-D flow due to the Hartmann effects along the direction of the magnetic field. The electric current lines would be increasingly distorted as the magnetic interactive parameter increases, and even induce an eddy current. Induced eddy current was also found in the different cross-sections along the axial direction, all of these would definitely deteriorate the performance of the MHD generator. The cross-sectional M-shape velocity profile found along the axial direction between the insulating walls is responsible for the formation of the vortex flow at the corner of the insulator cross-section, which, in turn, induces the corner eddy current at the corner. A numerical parametric study was also performed, and the computed performance parameters for the MHD generator suggest that, in order to enhance the performance of MHD generator, the magnetic interaction parameter should be elevated.

Using an extended MHD model including the Hall effect and finite Larmor radius effect, we reproduce multiple dipolarization fronts (DFs) associated with the interchange instability in the braking region of bursty bulk flow in the plasma sheet. Our simulations reveal that the multiple DFs produced by the interchange instability are “growing” type DFs because the maximum plasma flow speeds are behind the fronts. Both the earthward and tailward moving DFs can be produced by interchange instability in the near-Earth region. The Hall electric field is the dominant electric field component in the dip region and the DF layer. The convective and the electron pressure gradient electric field components are smaller. The sharp Bz changes in both the dip region and DF layer correspond to the oppositely directed currents that are primarily associated with electrons. The ion diamagnetic current due to the strong ion pressure gradient causes an intense downward current in the dip region, which can produce the dip ahead ...

By analyzing the types, causes and the fault feature of common fault of squirrel-cage asynchronous motor, and based on the study of the principles and methods of fault detection of electromotor, the multi-channel electric power data acquisition system is designed, which can realize the online fault detection of motor. Using AT89C52 microcontroller as the core components of the controller, and data collection use a special measurement chip CS5460. The data collected is transmitted to the upper computer by RS232 bus so as to realize the electric energy data. Sampling interpolation FFT algorithm make software compensation, and then the MCU high-speed interval of multi-channel data acquisition is realized.