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Background Diabetic nephropathy (DN) is a serious complicating factor in human type 2 diabetes (T2DM), and it commonly results in end-stage renal disease (ESRD) that requires kidney dialysis. Here, we report that the α7 nicotinic acetylcholine receptor (α7nAChR) agonist GTS-21 exerts a novel anti-inflammatory action to ameliorate DN, as studied using an inbred strain of Leprdb/db mice in which hyperglycemia and obesity co-exist owing to defective leptin receptor (Lepr) signaling. Methods For this analysis, GTS-21 was administered to 10–12 week-old male and female mice as a 4mg/kg intraperitoneal injection, twice-a-day, for 8 weeks. Kidney function and injury owing to DN were monitored by determination of plasma levels of BUN, creatinine, KIM-1 and NGAL. Histologic analysis of glomerular hypertrophy and mesangial matrix expansion were also used to assess DN in these mice. Concurrently, renal inflammation was assessed by measuring IL-6 and HMGB1, while also quantifying renal cell apoptosis, and apoptotic signaling pathways. Results We found that Leprdb/db mice exhibited increased markers of BUN, creatinine, NGAL, KIM-1, IL-6, cytochrome C, and HMGB-1. These abnormalities were also accompanied by histologic kidney injury (mesangial matrix expansion and apoptosis). Remarkably, all such pathologies were significantly reduced by GTS-21. Conclusions Collectively, our results provide new evidence that the α7nAChR agonist GTS-21 has the ability to attenuate diabetes-induced kidney injury. Potentially, GTS-21 engages the vagus nerve cholinergic anti-inflammatory reflex pathway (CAP) to produce this beneficial effect.

Magnetomotive photoacoustic/ultrasound imaging has shown superior specificity in visualizing targeted objects at cellular and molecular levels. By detecting magnet-induced displacements, magnetic-particles-targeted objects can be differentiated from background signals insensitive to the magnetic field. Unfortunately, background physiologic motion interferes during measurement, such as cardiac-induced motion and respiration, greatly reducing the robustness of the technique. In this paper, we proposed cyclic magnetomotive imaging with narrowband magnetic excitation. By synchronizing magnetic motion with the excitations, targeted objects moving coherently can be distinguished from background static signals and signals moving incoherently. HeLa cells targeted with magnetic nanoparticle-polymer core-shell particles were used as the targets for an initial test. A linear ultrasound array was interfaced with a commercial scanner to acquire a photoacoustic/ultrasound image sequence (maximum 1000 frames per second) during multi-cycle magnetic excitation (0.5 – 40 Hz frequency range) with an electromagnet. An image mask defined by a threshold on the displacement-coherence map was applied to the original images for background suppression. The results show that contrast was increased by more than 60 dB in an in-vitro experiment with the tagged cells fixed in a polyvinyl-alcohol gel and sandwiched between porcine liver tissues. Using a single sided system, cells injected subcutaneously on the back of a mouse were successfully differentiated from the background, with less than 20 µm coherent magnetic induced displacements isolated from millimetric background breathing motion. These results demonstrate the technique’s motion robustness for highly sensitive and specific diagnosis.

The effect of a pulsed magnetic field on the microstructure of a QAl9-4 aluminium bronze alloy was studied in this work. It was found that the dislocation density, grain boundary angle, and microhardness of the alloy significantly changed after the magnetic field treatment with a peak magnetic induction intensity of 3T, pulse duration of about 100 us, pulse interval of 10 s, and pulse time of 360. EBSD was used to test the KAM maps of the alloy microzone. It was found that the alloy’s dislocation density decreased by 10.88% after the pulsed magnetic field treatment; in particular, the dislocation in the deformed grains decreased significantly. The quantity of dislocation pile-up and the degree of distortion around the dislocation were reduced, which decreased the residual compressive stress on the alloy. Dislocation motion caused LAGB rotation, which reduced the misorientation of adjacent points inside the grain. The magnetic field induced the disappearance of deformation twins and weakened the strengthening effect of twins. The microhardness test results show that the alloy’s microhardness decreased by 8.06% after pulsed magnetic field treatment. The possible reasons for the magnetic field effect on dislocation were briefly discussed. The pulsed magnetic field might have caused the transition to the electronic energy state at the site of dislocation pinning, which led to free movement of the vacancy or impurity atom. The dislocation was easier to depin under the action of internal stress in the alloy, changing the dislocation distribution and alloy microstructure.

Optical coherence tomography angiography (OCTA) images suffer from inevitable micromotion (breathing, heartbeat, and blinking) noise. These image artifacts can severely disturb the visibility of results and reduce accuracy of vessel morphological and functional metrics quantization. Herein, we propose a multiple wavelet-FFT algorithm (MW-FFTA) comprising multiple integrated processes combined with wavelet-FFT and minimum reconstruction that can be used to effectively attenuate motion artifacts and significantly improve the precision of quantitative information. We verified the fidelity of image information and reliability of MW-FFTA by the image quality evaluation. The efficiency and robustness of MW-FFTA was validated by the vessel parameters on multi-scene in vivo OCTA imaging. Compared with previous algorithms, our method provides better visual and quantitative results. Therefore, the MW-FFTA possesses the potential capacity to improve the diagnosis of clinical diseases with OCTA.

Objective This study aimed to apply radiomics analysis of the change of deep medullary veins (DMV) on susceptibility-weighted imaging (SWI), and to distinguish mild hypoxic-ischemic encephalopathy (HIE) from moderate-to-severe HIE in neonates. Methods A total of 190 neonates with HIE (24 mild HIE and 166 moderate-to-severe HIE) were included in this study. All of them were born at 37 gestational weeks or later. The DMVs were manually included in the regions of interest (ROI). For the purpose of identifying optimal radiomics features and to construct Rad-scores, 1316 features were extracted. LASSO regression was used to identify the optimal radiomics features. Using the Red-score and the clinical independent factor, a nomogram was constructed. In order to evaluate the performance of the different models, receiver operating characteristic (ROC) curve analysis was applied. Decision curve analysis (DCA) was implemented to evaluate the clinical utility. Results A total of 15 potential predictors were selected and contributed to Red-score construction. Compared with the radiomics model, the nomogram combined model incorporating Red-score and urea nitrogen did not better distinguish between the mild HIE and moderate-to-severe HIE group. For the training cohort, the AUC of the radiomics model and the combined nomogram model was 0.84 and 0.84. For the validation cohort, the AUC of the radiomics model and the combined nomogram model was 0.80 and 0.79, respectively. The addition of clinical characteristics to the nomogram failed to distinguish mild HIE from moderate-to-severe HIE group. Conclusion We developed a radiomics model and combined nomogram model as an indicator to distinguish mild HIE from moderate-to-severe HIE group.

Since childhood, children have been drawn to the aesthetics of music. In the current exploratory study, we investigate the relationship between age, gender, and music education in terms of the perception of music preferences and musical emotions, which are two fundamental aspects of the aesthetic experience of music, using the children of teachers. I utilized the sectional design. We have established an experimental method for addressing particular children's musical interests and tendencies to do this. Melodic emotions and style are highly regarded. The melody consisted of three brief piano pieces: a significant piece, a minor piece, and a freetone piece. This article describes the "Reasoning of Music Education" or "Philosophy of Music Education" field (MEP). Method of music instruction is a relatively young field, and many music educators are unaware of its existence, as well as its inclination and value. In North America and most other nations, specialized MEP courses are not currently common in undergraduate and graduate curricula. The most surprising aspect of music is the variety of human advancements and individuals that create, utilize, evaluate, teach, learn, and invent "music" items, cycles, encounters, etc. Similarly, billions of people have invested a great deal of time, effort, thought, emotion, money, and in some cases, their lives creating specific sounds and related activities. I also acknowledge that it has been completed. Although music is an important and visible component of human civilisation, certain types of "music" sounds are created and listened to fulfill basic survival demands. Infrequent (if not entirely bizarre) compared to the enormous effort we exert. As many have noted, music does not appear biologically essential, yet it permeates all cultures.

Genome-scale functional screening accelerates comprehensive assessment of gene function in cells. Here, we have established a genome-scale loss-of-function screening strategy that combined a cytosine base editor with approximately 12,000 parallel sgRNAs targeting 98.1% of total genes in Corynebacterium glutamicum ATCC 13032. Unlike previous data processing methods developed in yeast or mammalian cells, we developed a new data processing procedure to locate candidate genes by statistical sgRNA enrichment analysis. Known and novel functional genes related to 5-fluorouracil resistance, 5-fluoroorotate resistance, oxidative stress tolerance, or furfural tolerance have been identified. In particular, purU and serA were proven to be related to the furfural tolerance in C. glutamicum . A cloud platform named FSsgRNA-Analyzer was provided to accelerate sequencing data processing for CRISPR-based functional screening. Our method would be broadly useful to functional genomics study and strain engineering in other microorganisms.

WS2 nanosheets hold great promise for a variety of applications yet faces a grand challenge in terms of large-scale synthesis. We report a reliable, scalable, and high-yield (>93 %) synthetic strategy to fabricate WS2 nanosheets, which exhibit highly desirable electrocatalytic properties toward both the alkaline sulfion (S2- ) oxidation reaction (SOR) and the acidic hydrogen evolution reaction (HER). The findings prompted us to develop a hybrid alkali-acid electrochemical cell with the WS2 nanosheets as bifunctional electrode catalysts of alkaline anodic SOR and acidic cathodic HER. The proof-of-concept device holds promise for self-power or low-electricity electrolytic H2 generation and environmentally friendly recycling of sulfion with enhanced electron utilization efficiency.

With the rapid development of sequencing technology, scientists have been able to study and acquire a better understanding of non-coding RNAs (ncRNAs). Circular RNAs (circRNAs), a unique class of ncRNAs with a special loop structure, have been found to possess modulatory properties with respect to various biological processes, such as interacting with nucleic acids or proteins. In addition to their tissue-specific expression and high conservation across species, circRNAs are abundant and dynamically expressed in the nervous system, especially in nerve synapse, indicating their potential regulation in synaptic plasticity or neuronal disorders. In this review, we discuss the characteristics of circRNAs and their common biological functions, as well as their significant role in neurodevelopment, drug addiction and neurodegenerative diseases, aiming to guide further disease diagnoses and efficient therapy.

Visible-light-driven photocatalysts for hydrogen production have been made great progress in recent years, there yet remain grand spaces to be improved further for implementing practical feasibility. We herein report a chlorine doped carbon nitride (Cl-p-C3N4) with ultrathin nanostrips morphology, which displays excellent photocatalytic hydrogen generation performance (5976 μmol h−1 g−1, 16.5 times higher than that of bulk C3N4) under visible light irradiation, with an apparent quantum yield of 8.91% at 420 nm. Experimental results and DFT calculations show that the ultrathin Cl-p-C3N4 nanostrips with heteroatom doping are greatly conducive to reduce the band gap, increase the surface area, and promote the separation efficiency of the photogenerated charge carrier, leading to the improvement of the charge carrier migration to the material surface or co-catalyst during the photocatalytic reaction. This work sheds light on the effective strategy to construct excellent photocatalyst by reasonably regulating the band structure and morphology.

Brain network classification has attracted increasing attention with the widespread application in the automatic diagnosis of brain diseases. However, limited by the higher cost of detecting and marking for medical imaging, the amount of brain network data is usually small, which largely restricts the performance of current brain network classification models. In this paper, we propose a new sparse data augmentation model (SDAM) based on EncoderForest to effectively enhance the brain network data and improve the classification performance. The EncoderForest based SDAM uses a generator which innovatively encodes the rules of a set of parallel decision trees to generate sparse data with only discriminative connections. The generated data expands the original data set effectively by utilizing the advantages of EncoderForest in learning data feature sparsely and constructing a feature association generation model compactly. In addition, the SDAM is flexible to combine with different classification models, such as random forest, support vector machine, deep neural network, etc. The experimental results on three common brain disease data sets show that our model is able to reasonably augment the brain network data and remarkably improve the performance of various classifiers.

Realizing a high color rendering index (CRI) in Ce:LuAG transparent ceramics (TCs) with desired thermal stability is essential to their applications in white LEDs/LDs as color converters. In this study, based on the scheme of configuring the red component by Cr3+ doping, an efficient spectral regulation was realized in Ce,Cr:LuAG TCs. A unilateral shift phenomenon could be observed in both photoluminescence (PL) and photoluminescence excitation (PLE) spectra of TCs. By constructing TC-based white LED/LD devices in a remote excitation mode, luminescence properties of Ce,Cr:LuAG TCs were systematically investigated. The CRI values of Ce:LuAG TC based white LEDs could be increased by a magnitude of 46.2%. Particularly, by combining the as fabricated Ce,Cr:LuAG TCs with a 0.5 at% Ce:YAG TC, surprising CRI values of 88 and 85.5 were obtained in TC based white LEDs and LDs, respectively. Therefore, Ce,Cr:LuAG TC is a highly promising color convertor for high-power white LEDs/LDs applied in general lighting and displaying.

The motion control of the divertor maintenance system of the China Fusion Engineering Test Reactor (CFETR) was studied in this paper, in which CFETR Multi-Functional Maintenance Platform (MFMP) was simplified as a parallel robot for the convenience of theoretical analysis. In order to design the motion controller of parallel robot, the kinematics analysis of parallel robot was carried out. After that, the dynamic modeling of the hydraulic system was built. As the large variation of heavy payload on MFMP and highly nonlinearity of the system, A Fuzzy-PID controller was built for self-tuning PID controller parameters by using Fuzzy system to achieve better performance. In order to test the feasibility of the Fuzzy-PID controller, the simulation model of the system was built in Simulink. The results have showed that Fuzzy-PID controller can significantly reduce the angular error of the moving platform and provide the stable motion for transferring the divertor.

Micro-diffusion flames have received much research attention due to their use in micro-energy systems. Experiments are performed with liquid heptane fuel at room temperature to assess the effects o...

Microalgae concentrations have been studied as an important factor to reflect water qualities. High concentration of microalgae should cause water eutrophication then cause environment pollution. However, conventional methods to monitor algal concentration in source water whose use is hampered by high-cost, complicated operation and the need of a centralized laboratory for practical samples’ analysis. In order to overcome these constraints, here in this work, we developed a portable and real-time monitoring platform which consists of a microfluidic chip for algae enrichment, a portable microscopic imaging system integrated with a commercial smartphone. The chip is designed and fabricated with a multi-layer electrode structure to trap algaes via alternating current electrokinetics (ACEK) effect. A temperature dependent fully coupled numerical model is presented to calculate the ACEK flow, showing satisfied trapping performance by adjusting the applied voltage and frequency. Moreover, preliminary experiments are performed in our chip using freshwater samples, in which algae trapping behavior is visually observed and recorded by a self-designed portable microscope. Then the trapping performance of this system can be semi-quantitatively figured out by image processing. This lab-on-a-chip system shows high potential in concentrating bio-particles and developing a portable, integrated and automated system for monitoring the quality of water resources in nature. [2020-0381]

In the Dempster-Shafer (D-S) evidence theory, how to transform the objective data in reality into the basic probability assignment (BPA) is still an open issue. Based on this problem, a new method of generating BPA based on interval number distance and model reliability is proposed. First, construct the interval number model under each attribute. Secondly, calculate the interval number distance between the test sample and the interval number model and convert it into the initial basic probability assignment (IBPA). Thirdly, the final BPA is obtained by discounting the IBPA by constructing the comprehensive reliability from the static reliability and dynamic reliability of the interval number model. Finally, the Dempster combination rule is used to fuse the final BPA one by one, and the decision is made according to the fusion result. The ten-fold cross-validation results show that the classification accuracy under the three data sets is higher than other methods, and the classification accuracy of the Iris data set is 0.9733. At the same time, it is verified that the proposed method still has good effectiveness and robustness in the incomplete information environment.

Aqueous Zn-S battery with high energy density represents a promising large-scale energy storage technology, but its application is severely hindered by the poor reversibility of both S cathode and Zn anode. Herein, we develop a "cocktail optimized" electrolyte containing tetraglyme (G4) and water as co-solvents and I

Chlorinated polyfluorinated ether sulfonic acids (Cl-PFESA) and perfluorobutane sulfonate (PFBS), used as perfluorooctanesulfonate (PFOS) alternatives, were indicated as thyroid hormone disruptive toxicants in experimental studies. However, it is unclear whether prenatal exposure to Cl-PFESA and PFBS affects neonatal thyroid stimulating hormone (TSH) in human.To disclose the relationships between prenatal Cl-PFESAs and PFBS exposure and neonatal thyroid-stimulating hormone (TSH) levels based on a perspective cohort study.A total of 1015 pairs of mother and newborn were included from an ongoing birth cohort study in Wuhan, China, between 2013 and 2014. Six PFASs in cord blood sera and TSH concentration in neonatal postpartum heel sticks blood were quantified. Mixed linear and weighted quantile sum (WQS) regression models were applied to assess the individual and combination effects of PFASs exposure on neonatal TSH levels with multiple covariates adjustments.After adjusting for potential confounders and other five PFASs, for each 1-ng/mL increase of PFBS or 8:2 Cl-PFESA, was negatively associated with 25.90% (95%CI: 37.37%, -12.32%; P 0.001) and 27.19% (95%CI: 46.15%, -1.55%; P = 0.033) change in TSH in male but not female infants, respectively. No significant association was found between other PFASs exposure and neonatal TSH. Higher PFAS mixture in cord blood was significantly associated with decrease TSH concentration in all newborns (β = -0.36; 95%CI: 0.58, -0.13; P = 0.001) identified by WQS regression model. PFBS, PFOS and 6:2 Cl-PFESA were the major contributors to the neonatal TSH decrement with the weights of 56.50%, 18.71%, 12.81% among PFAS mixture, respectively.our prospective cohort study suggested a negative association of cord serum PFBS and 8:2 CI-PFESA with TSH concentration in newborns, especially for boys. Additional studies are required to elaborate on the underlying biological mechanisms, especially for PFBS.

Sodium based dual-ion battery (SDIB) has been regarded as one of the promising batteries technologies thanks to its high working voltage and natural abundance of sodium source, its practical application yet faces critical issues of low capacity and sluggish kinetics of intercalation-type graphite anode. Here, a tubular nanohybrid composed of building blocks of carbon-film wrapped WS

In order to explore the cracking law and failure characteristics of segments, a model test of shield segment cracking was conducted. The microscopic and macroscopic crack evolution process of the segment is studied by using acoustic emission detection technology and crack opening displacement (CMOD). According to the acoustic emission signal and CMOD, characteristics generated in the process of segment cracking, in the form of numerical value, the evolution characteristics of each stage of segment cracking are directly reflected. Based on acoustic emission energy and CMOD, the segment cracking damage model was established to determine the segment fracture damage degree. The result shows that segment cracking can be divided into three stages, and the acoustic emission detection results and CMOD have different degrees of change in each cracking stage. This proves that both the acoustic emission acquisition results and CMOD can be used as evaluation indicators of damage degree. Acoustic emission can accurately identify the crack evolution process, and the yield strengthening is an important stage of crack damage evolution. The damage data points in this stage account for 76.83% of all the damage data points, the occurrence rate of damage data points is 0.225 s, and the density of data points in the damaged area is 3.219 × 10−4 mm3, which is larger than the other two stages. The segment cracking damage model can effectively reflect the segment cracking degree and provide a reference for the actual segment cracking assessment.

Genome-scale functional screening accelerates comprehensive assessment of gene function in cells. Here, we have established a genome-scale loss-of-function screening strategy that combined cytosine base editor with approximately 12,000 parallel sgRNAs targeting 98.1% of total genes in Corynebacterium glutamicum ATCC 13032. Unlike previously data processing methods developed in yeast or mammalian cells, we developed a new data processing procedure to locate candidate genes by statistical sgRNA enrichment analysis. Known as well as novel functional genes related to 5-fluorouracil resistance, 5-fluoroorotate resistance, oxidative stress tolerance or furfural tolerance have been identified. Especially, purU and serA, were proven to be related to the furfural tolerance in C. glutamicum for the first time. A cloud platform named FSsgRNA-Analyzer was provided to accelerate sequencing data processing for CRISPR based functional screening (https://fssgrna.biodesign.ac.cn/). Our method would be broadly useful to functional genomics study and strain engineering in other microorganisms.

A rotary valve coupled in a combustor assembly can generate periodic pressure oscillations inside the combustor and can be used to study the combustion instability in the combustion chamber of a rocket engine. This paper proposes a cold gas flow experimental system based on a rotary valve and a corresponding rotation model. A 3D numerical model is proposed to obtain the transient flow inside the rotary valve, and the dynamic mesh technique and User-Defined Functions (UDFs) are adopted to implement a swing motion instead of a rotary motion. Several cold gas flow experiments are carried out at rotating speeds of 75 225, and 375 rpm to verify the validity of the numerical model. The effects of rotating speed, stroke length ratio and radius of the RED (Rotor Exhaust Duct) on the pressure oscillations are studied using this numerical model. The results show that the maximum and peak-to-peak values of the pressure oscillations gradually decrease with increasing rotating speed. The ratio of the corresponding peak-to-peak value to the maximum pressure (pressure amplitude ratio) is reduced from 1.81 to 0.6%. The stroke length ratio affects the pressure waveform because it leads to a change in the time spent in the non-exhaust stage. When the stroke length ratio is 0, the waveform closely resembles a sine wave. With the increase in the stroke length ratio, the pressure waveform exhibits a more square or a triangular wave shape. Finally, a high-frequency and high-amplitude pressure oscillation can be obtained by appropriately increasing the radius of the RED.

In this paper, the degradation related parameters of GaInP/GaAs/Ge triple-junction solar cell induced by electron irradiation are carried out by numerical simulation. The degradation results of short-circuit current, open-circuit voltage, maximum power have been investigated, and the degradation mechanism is analyzed. Combining the degradation results, the degradation of normalized parameters versus displacement damage dose is obtained. The results show that the degradation increases with the increase of the electron fluence and electron irradiation energy. The degradation normalized related parameters versus displacement damage dose can be characterized by a special curve that is not affected by the type of irradiated particles. By calculating the annual displacement damage dose and the on-orbit operation time of special space orbit, the degradation of normalized parameters can be obtained with the fitting curve in the simulation. The study will provide an approach to estimate the radiation damage of triple-junction solar cell induced by space particle irradiation.

Polyester/cotton blend fabrics are widely used in clothing and household textiles which combine the comfort of cotton and excellent mechanical strength of polyester. However, their high flammability due to the special "wick effect" resulting from the different thermal decomposition process of cotton and polyester causes greatly potential fire hazards. In this study, fully bio-based intumescent flame retardant (IFR) coating of chitosan/phytic acid (CS/PA) was layer-by-layer (LBL) assembly constructed on polyester/cotton blend fabrics. The LOI value of polyester/cotton blend fabric which was LBL assembly coated by 20 bilayers CS/PA reached 29.2%. And the dripping of coated fabric was eliminated. The results of cone calorimetry test confirmed CS/PA coating greatly improved the flame retardancy of polyester/cotton blend fabrics. Thermogravimetric analysis (TGA) results showed CS/PA coating changed the thermal decomposition process to promote the char formation of polyester/cotton blend fabrics. CS/PA coating on fabric could form the IFR system which acts through both condensed phase action by the catalysis dehydration reaction to forming stable char and gas phase action by the blowing effect. This research provides a new strategy to eco-friendly flame retardant and dripping-resistant for polyester/cotton blend fabrics by bio-based IFR system through facile LBL assembly method.

Social Networking Services (SNSs) provide online platforms for users with two kinds of behavior: user-user social behavior (e.g., following a user, making friends with others) and user-item consumption behavior (e.g., rating, showing likeness, clicking, giving thumbs up to items). With the increasing popularity of SNSs and demand for SNS features, predicting potential social links and recommending preferable items to users have become two hot research lines. However, previous works either modeled just one of these two kinds of behaviors in isolation or only considered the observed user behavior data. In fact, social scientists have long recognized that the user-user and user-item behaviors have a mutual reinforcement effect. On the one hand, the two behaviors have correlations, and they can influence each other. On the other hand, due to the sparsity of the observed user behavior data, the user behavior prediction performance is far from satisfactory, although, using two types of behavioral data at the same time can mitigate the sparsity problem. These two problems remains open: how to better model the correlation of user-user social and user-item consumption activities and how to mitigate the data sparsity issue. In this paper, we propose a random walk based distributed representation learning model to jointly predict these behaviors on SNSs. Specifically, we first construct a joint behavior graph that combines the two behaviors, with the edges denoting the sparse observed user behavior data. Then, we adopt a random walk to capture higher-order relationships between users and items. After that, we utilize a distributed learning approach to embed both users and items into a latent space. In this way, the behavior prediction tasks are transformed into similarity calculations in the latent space. Finally, extensive experimental results using two real-world datasets demonstrate the effectiveness of our proposed approach on the two behavior prediction tasks.

A small-scale experimental burner with an improved rotary valve has been designed to measure solid-propellant pressure-coupled response for mean pressures on the order of 2.2–2.9 MPa and oscillating frequencies of 23–161 Hz, within 9% amplitudes. This paper proposes an indirect method for measuring the instantaneous valve area and phase delay angle based on a circular grating system and a corresponding mathematical model, and the validity of which is confirmed by several cold-gas experiments and numerical simulations. The effects of frequency on oscillating pressure, exhaust mass flow rate and pressure-coupled response are studied by carrying out several hot-gas experiments and numerical simulations. The results show that the mean pressure is not affected by the oscillating frequency and maintains at 2.9 MPa. The exhaust mass flow rate of the rotary valve is determined by the instantaneous valve area and independent of frequency. The peak-to-peak pressure is inversely proportional to the oscillating frequency, reducing from 0.539 MPa at 23 Hz to 0.053 MPa at 161 Hz. The magnitude of pressure-coupled response appears to be constant (0.8) at 23–161 Hz, with pressure oscillations lagging instantaneous valve area by 0.504π-0.531π。The study is expected to benefit research on similar rotary valves and can serve as a basis for measuring the solid-propellant pressure combustion response.

Epoxy resins (EP) have been commonly used, but their poor flame retardant properties have prevented their widespread use. In order to improve the flame retardant properties of EP, an organic-inorganic composite flame retardant (HKDC) containing multi-element P/N/Si was successfully synthesized in this work using a typical aldehyde amine condensation reaction. This flame retardant utilizes the synergistic effect of multiple elements to simultaneously perform the flame retardant function of each element, and it can achieve excellent flame retardant effect by using low addition amount in EP. At the same time, this flame retardant can not only reduce the migration of molecules through the structure of inorganic substances, but also the C = C reaction in EP can form large molecules and increase the compactness with the EP matrix. The flame retardants were then quantified by measuring their flame retardant properties, combustion behavior and thermal stability. When the flame retardant HKDC is added, the flame retardant performance of EP is improved and the vertical combustion test achieves a V-0 rating. Most importantly, the addition of flame retardant HKDC effectively suppressed the toxic gas and smoke emissions of EP, with TSP values much lower than those of pure EP, and CO and CO2 emissions were suppressed.

Electrode materials with high conductivity and high mass transport rate are highly desirable for a variety of electrochemical energy devices but face a grand challenge to be readily prepared yet. Here, we propose the design and preparation of a nanohybrid of V2O3 nanoparticles embedded in a multichannel carbon nanofiber (V2O3@MCNF) network with high conductivity and high mass transport. We demonstrate the V2O3@MCNF shows superior capability for sodium storage with an excellent capacity of 214.3 mA h g-1 even at 5 A g-1, thanks to its high conductivity for electron transfer and facilitated mass transportation endowed by the one-dimensional conductive multichannel fiber structure. Such favorable structures and properties in V2O3@MCNFs enable them to be applied as high-performance anodes of sodium-ion hybrid capacitors (SIHCs), successfully addressing the critical kinetics imbalance between Faradaic anodes and capacitive cathodes for application of SIHCs, which show impressively high energy/power densities along with impressive cycling performance over 10,000 cycles.

No abstract

Side-scan sonar is widely utilized in the field of underwater exploration. Accurate segmentation of the side-scan sonar images is an essential part of sonar image processing. To improve the accuracy of image segmentation and reduce the occupancy of computing resources, a new active contour model for image segmentation is proposed in this article. Firstly, we make the energy function of each pixel determined by itself and its neighbors. This article embeds the local texture neighborhood region system and define its structure to against the noise and object boundary pollution of the image. Further, we introduce a Bayesian framework that embeds the Markov Random Field model and local texture information to counteract the problem of intensity inhomogeneity, improve the accuracy of segmentation, and reduce computational cost. Finally, according to this model, we customize a new multi-class energy function which applied to the level set function. By minimizing this energy equation, we can divide the image into three classes: object, shadow, and seabed background. The experimental results show that this method has a good effect on the synthesized high-noise sonar images and real sonar images, and also have significantly increased the accurate recognition of underwater targets.