Search

Abstract Background Image denoising technology removes noise from the corrupted image by utilizing different features between image and noise. Convolutional neural network (CNN)-based algorithms have been the concern of the recent progress on diverse image restoration problems and become an efficient solution in image denoising. Objective Although a quite number of existing CNN-based image denoising methods perform well on the simplified additive white Gaussian noise (AWGN) model, their performance often degrades severely on the real-world noisy images which are corrupted by more complicated noise. Methods In this paper, we utilized the multi-task learning (MTL) framework to integrate multiple loss functions for collaborative training of CNN. This approach aims to improve the denoising performance of CNNs on real-world images with non-Gaussian noise. Simultaneously, to automatically optimize the weights of individual sub-tasks within the MTL framework, we incorporated a self-learning weight layer into the CNN. Results Extensive experiments demonstrate that our approach effectively enhances the denoising performance of CNN-based image denoising algorithms on real-world images. It reduces excessive image smoothing, improves quantitative metrics, and enhances visual quality in the restored images. Conclusion Our method shows the effectiveness of the improved performance of denoising CNNS for real-world image denoising processing.

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

Abstract Immunotherapy has emerged as a promising modality for addressing advanced or conventionally drug-resistant malignancies. When it comes to lung adenocarcinoma (LUAD), T cells have demonstrated significant influence on both antitumor activity and the tumor microenvironment. However, their specific contributions remain largely unexplored. This investigation aimed to delineate molecular subtypes and prognostic indicators founded on T cell marker genes, thereby shedding light on the significance of T cells in LUAD prognosis and precision treatment. The cellular phenotypes were identified by scrutinizing the single-cell data obtained from the GEO repository. Subsequently, T cell marker genes derived from single-cell sequencing analyses were integrated with differentially expressed genes from the TCGA repository to pinpoint T cell-associated genes. Utilizing Cox analysis, molecular subtypes and prognostic signatures were established and subsequently verified using the GEO dataset. The ensuing molecular and immunological distinctions, along with therapy sensitivity between the two sub-cohorts, were examined via the ESTIMATE, CIBERSORT, and ssGSEA methodologies. Compartmentalization, somatic mutation, nomogram development, chemotherapy sensitivity prediction, and potential drug prediction analyses were also conducted according to the risk signature. Additionally, real-time qPCR and the HPA database corroborated the mRNA and protein expression patterns of signature genes in LUAD tissues. In summary, this research yielded an innovative T cell marker gene-based signature with remarkable potential to prognosis and anticipate immunotherapeutic outcomes in LUAD patients.

The efficient non-noble metal-based bifunctional electrocatalyst for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) has attracted great interest, which is highly significant to enhance the efficiency of hydrogen production from water electrolysis. Herein, inspired by the appropriate hydrogen adsorption free energy of transition metal alloy and the strong corrosion resistance of phosphide in alkaline electrolyte, carbon compound NiFeMo-P anchored on nickel foam (NiFeMo-P-C) is obtained by simple one-pot hydrothermal and subsequent hydrogen reduction treatment. Remarkably, the NiFeMo-P-C exhibits excellent bifunctional electrocatalytic performances toward HER and OER with low overpotentials of 87 and 196 mV at 10 mA·cm–2, respectively. Moreover, the electrolyzer using NiFeMo-P-C as both cathode and anode only requires a cell voltage of 1.50 V to reach a current density of 10 mA·cm–2, along with an outstanding long-term stability for 50 h. The synergistic effect among alloys and phosphide, partially broken hollow morphology and porous nickel foam substrate jointly impart NiFeMo-P-C high electrocatalytic activity and superior durability.

At present, most atomic spin precession detection schemes use discrete optical elements, which lead to bulky detection systems. However, chip-based spin precession detection schemes lack modulation, resulting in lower detection sensitivity. In this paper, we propose and simulatively demonstrate an integrated atomic spin precession detection scheme using an on-chip Mach-Zehnder-like interferometer. An on-chip polarization sorter is designed, with contrast ratio of 24 dB and coupling efficiency of 16.8% at 795 nm. With this device, linearly polarized probe light that experienced optical rotation can be split and coupled into two waveguide arms of the interferometer. To avoid the effect of low frequency noise, our scheme uses a micro-heater to modulate the phase difference signal, allowing for high sensitivity detection. The whole detection system can reach micron size, which provides a practical new technique for high precision atomic sensors that can be integrated into chips.

Wide weaving machines traditionally enhance the weaving width by increasing the shuttle’s initial velocity. However, this approach introduces challenges like pronounced equipment vibration, elevated noise levels, heightened energy consumption, and a reduced lifespan. Moreover, its efficacy in significantly widening fabric is constrained. Addressing these concerns, this paper proposes a wide-width warp insertion solution that involves driving the high-temperature superconducting shuttle to achieve high-speed horizontal flight through a traveling magnetic field. The inductive weft insertion system structure of wide weaving machines comprises an insertion guideway with an iron core and wound electromagnetic coils. The shuttle consists of a high-temperature superconducting block and a conductive plate, serving as the driving element. By establishing the equivalent circuit of the weft insertion guideway and the suspended shuttle, the calculation formula for the dynamic driving performance of the weft insertion guideway is obtained. Utilizing a transient 3D magnetic field simulation model, the impact of parameters like the current frequency, shuttle conductive plate thickness, and suspension gap on weft insertion performance is explored. Successful wide-width weft insertion motion is achieved by controlling coil input current parameters. Finally, an experimental platform is constructed to validate the correctness of the weft insertion system structure and simulation model through practical experiments.

Background Chloroplast genomes are usually circular molecules, and most of them are tetrad structures with two inverted repeat (IR) regions, a large single-copy region, and a small single-copy region. IR contraction and expansion are among the genetic diversities during the evolution of plant chloroplast genomes. The only previously released tool for the visualization of junction sites of the regions does not consider the diversity of the starting point of genomes, which leads to incorrect results or even no results for the examination of IR contraction and expansion. Results In this work, a new tool named CPJSdraw was developed for visualizing the junction sites of chloroplast genomes. CPJSdraw can format the starting point of the irregular linearized genome, correct the junction sites of IR and single-copy regions, display the tetrad structure, visualize the junction sites of any number (≥1) of chloroplast genomes, show the transcription direction of genes adjacent to junction sites, and indicate the IR expansion or contraction of chloroplast genomes. Conclusions CPJSdraw is a software that is universal and reliable in analysis and visualization of IR expansion or contraction of chloroplast genomes. CPJSdraw has more accurate analysis and more complete functions when compared with previously released tool. CPJSdraw as a perl package and tested data are available at http://dx.doi.org/10.5281/zenodo.7669480 for English users. In addition, an online version with a Chinese interface is available at http://cloud.genepioneer.com:9929/#/tool/alltool/detail/335.

The three-dimensional fluorescence spectroscopy features the advantage of obtaining emission spectra at different excitation wavelengths and providing more detailed information. This study established a simple method to discriminate both the producer and grade of matcha tea by coupling three-dimensional fluorescence spectroscopy analysis and distance discrimination. The matcha tea was extracted three times and three-dimensional fluorescence spectroscopies of these tea infusions were scanned; then, the dimension of three-dimensional fluorescence spectroscopies was reduced by the integration at three specific areas showing local peaks of fluorescence intensity, and a series of vectors were constructed based on a combination of integrated vectors of the three tea infusions; finally, four distances were used to discriminate the producer and grade of matcha tea, and two discriminative patterns were compared. The results indicated that proper vector construction, appropriate discriminative distance, and correct steps are three key factors to ensure the high accuracy of the discrimination. The vector based on the three-dimensional fluorescence spectroscopy of all three tea infusions resulted in a higher accuracy than those only based on spectroscopy of one or two tea infusions, and the first tea infusion was more sensitive than the other tea infusion. The Mahalanobis distance had a higher accuracy that was up to 100% when the vector is appropriate, while the other three distances were about 60–90%. The two-step discriminative pattern, identifying the producer first and the grade second, showed a higher accuracy and a smaller uncertainty than the one-step pattern of identifying both directly. These key conclusions above help discriminate the producer and grade of matcha in a quick, accurate, and green method through three-dimensional fluorescence spectroscopy, as well as in quality inspections and identifying the critical parameters of the producing process.

Bidirectional pulsed current (BPC) heating has proven to be an effective method for internal heating. However, current research has primarily focused on the impact of symmetrical BPC on battery heat generation, while neglecting the influence of different BPC parameters. To address this gap, this paper investigates the effects of various BPC parameters on battery heat generation. Initially, an electro-thermal coupled model of the battery is constructed based on the results of electrochemical impedance spectroscopy (EIS) tests conducted at different temperatures and amplitudes at 20% state of charge (SOC). The validation results of the model demonstrate that the absolute errors of voltage and temperature are generally less than 50 mV and 1.2 °C. Subsequently, the influence of BPC parameters on battery heat generation is examined under different terminal voltage constraints, temperatures, and frequencies. The findings at 20% SOC reveal that symmetrical BPC does not consistently correspond to the maximum heating power. The proportion of charge time and discharge time in one cycle, corresponding to the maximum heating power, varies depending on the charge and discharge cut-off voltages. Moreover, these variations differ across frequencies and temperatures. When the terminal voltage is constrained between 3 V and 4.2 V, the maximum heat power corresponds to a discharge time share of 0.55 in one cycle. In conclusion, the results underscore the complex relationship between BPC parameters and battery heat generation, which can further enhance our understanding of effective heating strategies for batteries.

The atmospheric boundary layer provides useful information about the accumulation and diffusion of pollutants. As a fast method, remote sensing techniques are used to retrieve the atmospheric boundary layer height (ABLH). Atmospheric detection lidar has been widely applied for retrieving the ABLH by providing information on the vertical distribution of aerosols. However, these previous algorithms that rely on gradient change are susceptible to residual layers. Contrary to the use of gradient change to retrieve ABLH, in this paper, we propose using a cluster analysis approach through multifunction lidar remote sensing techniques due to its increasing availability. The clustering algorithm for multi-wavelength lidar data can be divided into two parts: characteristic signal selection and selection of the classifier. First, since the separability of each type of signal is different, careful selection of the input characteristic signal is important. We propose using Fourier transform for all the observed signals; the most suitable characteristic signal can be determined based on the dispersion degree of the signal in the frequency domain. Then, the performances of four common classifiers (K-means method, Gaussian mixture model, hierarchical cluster method (HCM), and density-based spatial clustering of applications with noise) are evaluated by comparing with the radiosonde measurements from June 2015 to June 2016. The results show that the performance of the HCM classifier is the best under all states (R2 = 0.84 and RMSE = 0.18 km). The findings obtained here offer insight into ABLH remote sensing technology.

Geosynchronous equatorial orbit (GEO) satellite-derived AOD possesses huge advantages for monitoring atmospheric aerosol with high frequency; however, the data missing existing in the satellite-derived AOD products dramatically limits this expected advantage due to cloud obscuration and aerosol retrieval algorithm. In recent years, numerous AOD fusion algorithms have been proposed, while these algorithms are mostly developed to blend daily AOD products derived from low Earth orbit (LEO) satellites and generally neglect discrepancies from different categories of products. Therefore, a spatiotemporal fusion framework based on the Bayesian maximum entropy theorem, blending GEO with LEO satellite observations and incorporating data discrepancies (GL-BME), is developed to complementarily recover the Advanced Himawari-8 Imager (AHI) AOD products over East Asia. The results show that GL-BME significantly improves the average spatial completeness of AOD from 20.3% to 67.6% with ensured reliability, and the accuracy of merged AODs nearly maintains that of original AHI AODs. Moreover, a comparison of the monthly aerosol spatial distribution between the merged and original AHI AODs is conducted to evaluate the performance and significance of GL-BME, which indicates that GL-BME could further restore the real atmospheric aerosol situation to a certain extent on the basis of dramatic spatial coverage improvement.

Immune checkpoint therapies (ICT) are promising for treating various cancers, but response rates vary. Here the authors show, in mouse models, that tumor-infiltrating mast cells colocalize with regulatory T cells, coincide with local reduction of MHC-I and CD8 T cells, and is associated with resistance to ICT, which can be reversed by c-kit inhibitor treatment.

Precipitation is a manifestation of many interacting complex processes. How to grasp its temporal pattern that would reveal underlain dominant contributing factors is the key objective of the study. For this, we explored the application of multiscale sample entropy (MSE) in describing the long-term daily precipitation. Sample entropy (SE) adds similarity measure over the conventional information entropy, and it has been used in quantifying changing complexity in chaotic dynamic systems. With the further incorporation of multiscale consideration, the MSE analysis gives the trend of SE changes with scale, and provides a rich description of participating factors. The daily precipitation time series studied were taken from 665 weather stations across China that have been recorded for about 50–61 years. The SE estimates are a function of the length of time series (n), the dimension of similarity (m), and the match threshold (r). These parameters are problem-dependent, and through simulation, this study has determined that m = 2, r = 0.15, and n ≈ 20,000 would be appropriate for estimating SE up to the 30-day scale. Three general patterns of MSE for precipitation time series are identified: (1) Pattern A, SE increases with scale; (2) Pattern B, SE increases then decreases and followed by increase; and (3) Pattern C, SE increases then decreases. The MSE is found capable of detecting differences in characteristics among precipitation time series. Matching MSE thus could serve as a metric to evaluate the adequacy of simulated precipitation time series. Using this metric, we have shown that to embody seasonal changes one needs to use different monthly two-parameter gamma distribution functions in generating simulated precipitation time series. Moreover, for dry seasons, one also needs to consider interannual fluctuations: it is inadequate to use just one single function for simulating multi-year precipitation data. Finally, for the study region, MSE patterns show coherence over the distance in that stations that are close, which range from 40 to 80 km, exhibit similar MSE trends. The MSE patterns obtained are also found to be reflective of the regional precipitation patterns—this has important implications on water resources management.

Biodegradable composites consisting of Poly-(butylene adipate-co-terephthalate) (PBAT), thermoplastic starch, hydrophobically modified nanofibrillated cellulose (HMNC), and green surfactant (sucrose fatty acid ester) were prepared via the melt-mixing and film-blowing process (PBAT-HMNC). The composites were characterized using the Fourier transform infrared spectroscope (FT-IR), scanning electron microscope (SEM), and thermogravimetric analyzer (TGA). The mechanical and barrier properties were systematically studied. The results indicated that PBAT-HMNC composites exhibited excellent mechanical and barrier properties. The tensile strength reached the maximum value (over 13 MPa) when the HMNC content was 0.6% and the thermal decomposition temperature decreased by 1 to 2 °C. The lowest values of the water vapor transmission rate (WVTR) and the oxygen transmission rate (OTR) were obtained from the composite with 0.6 wt% HMNC, prepared via the film-bowing process with the values of 389 g/(m2·day) and 782 cc/(m2·day), which decreased by 51.3% and 42.1%, respectively. The Agaricus mushrooms still had a commodity value after 11 days of preservation using the film with 0.6 wt% HMNC. PBAT-HMNC composites have been proven to be promising nanocomposite materials for packaging.

This paper explores the impact of e-commerce on profit margin from the perspective of scale using nation-level survey data from China. The results show that e-commerce can increase the profit margin of cooperatives, and that a higher proportion of sales via e-commerce strengthens profitability. Secondly, the effects of agri-e-commerce on cooperative profit margin is highly dependent on young talents with rich experience and high education level; in particular, female leaders have a significantly stronger effect on improving profit margins by using e-commerce than male leaders. Thirdly, the operating scale of cooperatives does not have a direct impact on the profit margins, but a bigger operating scale can significantly enhance the effect of e-commerce on profit margins. Lastly, a higher degree of standardization of cooperatives and products more clearly evidences the role played by e-commerce, including the number of brands and certification. Overall, this research provides a micro-foundation for cooperatives to better incorporate the key role of e-commerce under the background of platform monopoly and sheds light on how the government can formulate relevant policies to better support China’s e-commerce development.

Food is the core of urban daily life and socio-economic activities but is rarely the focus of urban planning. The spatial layout of food retail outlets is important for optimizing the urban food system, improving land resource allocation, and encouraging healthy food consumption. Based on food retail POI data, this study employed kernel density estimation, road network centrality, spatial autocorrelation analysis, and locational entropy to analyze the spatial characteristics of supermarkets, produce markets, and small stores in an urban center in Beijing, and explored street coupling and supply-demand matching. The results indicated that within the study area: (1) supermarkets had an obvious “core-periphery” distribution, produce markets had a polycentric distribution, and small stores had a relatively uniform distribution; (2) road network centrality indices revealed a differentiated multi-core-edge distribution; (3) streets with high locational entropy values for supermarkets and produce markets were mostly concentrated in the central area, whereas the matching distribution of small stores was relatively balanced. From the perspective of urban planning, policy implications are proposed based on spatial and social equity, urban-rural differences, population structure and distribution status, and a resilient supply chain. The study findings have practical significance for guiding the development of urban food systems in a healthy, just, and sustainable direction, as well as rational urban land planning.

We report on prime-boost vaccine regimens with two simian adenovirus (Ad) vectors (SAdV) or two human serotype Ad vectors (HAdV) expressing Gag and gp160 of simian immunodeficiency virus (SIV)mac239 tested in HAdV-seropositive rhesus macaques (RMs) repeatedly challenged rectally with low doses of SIVmac251. Both vaccine regimens reduced set point and peak viral loads (PVL) and accelerated viral clearance. In SAdV-vaccinated controller genotype RMs resistance against infection correlated with levels of envelope (Env)-specific antibody (Ab) titers. In both vaccine groups CD8+T cells controlled viral loads (VL) upon infection. Circulating CD4+ and CD8+ T cells showed significant changes in their transcriptome over time following vaccination, which differed between the vaccine groups. T cells from SIV-resistant RMs had unique transcriptional profiles indicating that both follicular T helper (TFH) cell responses and highly activated CD8+ T cells may play a role in protection. Keywords: HIV-1 vaccine, Adenovirus vector, Mucosal challenge, Protection, Gene expression profiles

An experimental study on the C60 concrete was carried out under five different curing conditions based on the maturity theory. The influence patterns of the curing conditions on the increase of the C60 concrete strength were discussed. The experimental data were fitted using different strength-maturity models, the accuracies of which were then analyzed. The results show that the mapping relation between the compressive strength and maturity of the C60 concrete could be well characterized by the logarithmic functional relation.

The piezoelectric cantilever with a large proof mass is a classic vibration energy harvesting structure. In this study, in order to harvest much more energy from low frequency vibration in the finite volume, a novel L type mass block is proposed and compared with a traditional rectangular mass block for the piezoelectric cantilever. A theoretical modeling of lumped parameter system is carried out considering the effect of mass block length on mass, stiffness and damping. A series of PZT bimorph cantilevers with brass proof mass prototypes are fabricated for the experimental verification. Their eigenfrequency and maximum piezoelectric power output are analyzed by the experiment and simulation. The piezoelectric cantilever with L type mass block avoids the weakness of decreasing the effective length of piezoelectric cantilever, and has lower eigenfrequency and larger piezoelectric power output than that with rectangular mass block. Its piezoelectric power output of 192 mW/(g2) can be obtained at the low resonant frequency of 18.1 Hz and the optimal load impedance of 5kΩ, and the unit volume power density is as high as 24.6 mW/(cm3×g2).

BACKGROUND:Estimates of current global rabies mortality range from 26,000 to 59,000 deaths per annum. Although pre-exposure prophylaxis using inactivated rabies virus vaccines (IRVs) is effective, it requires two to three doses and is regarded as being too expensive and impractical for inclusion in routine childhood immunization programmes. METHODOLOGY/ PRINCIPAL FINDINGS:Here we report the development of a simian-adenovirus-vectored rabies vaccine intended to enable cost-effective population-wide pre-exposure prophylaxis against rabies. ChAdOx2 RabG uses the chimpanzee adenovirus serotype 68 (AdC68) backbone previously shown to achieve pre-exposure protection against rabies in non-human primates. ChAdOx2 differs from AdC68 in that it contains the human adenovirus serotype 5 (AdHu5) E4 orf6/7 region in place of the AdC68 equivalents, enhancing ease of manufacturing in cell lines which provide AdHu5 E1 proteins in trans. We show that immunogenicity of ChAdOx2 RabG in mice is comparable to that of AdC68 RabG and other adenovirus serotypes expressing rabies virus glycoprotein. High titers of rabies virus neutralizing antibody (VNA) are elicited after a single dose. The relationship between levels of VNA activity and rabies virus glycoprotein monomer-binding antibody differs after immunization with adenovirus-vectored vaccines and IRV vaccines, suggesting routes to further enhancement of the efficacy of the adenovirus-vectored candidates. We also demonstrate that ChAdOx2 RabG can be thermostabilised using a low-cost method suitable for clinical bio-manufacture and ambient-temperature distribution in tropical climates. Finally, we show that a dose-sparing effect can be achieved by formulating ChAdOx2 RabG with a simple chemical adjuvant. This approach could lower the cost of ChAdOx2 RabG and other adenovirus-vectored vaccines. CONCLUSIONS/ SIGNIFICANCE:ChAdOx2 RabG may prove to be a useful tool to reduce the human rabies death toll. We have secured funding for Good Manufacturing Practice- compliant bio-manufacture and Phase I clinical trial of this candidate.

An improved fuzzy neural network (FNN)/proportion integration differentiation (PID) compound control scheme based on variable universe and back-propagation (BP) algorithms is proposed to improve the ability of disturbance rejection of a three-axis inertially stabilized platform (ISP) for aerial remote sensing applications. In the design of improved FNN/PID compound controller, the variable universe method is firstly used for the design of the fuzzy/PID compound controller; then, the BP algorithm is utilized to finely tune the controller parameters online. In this way, the desired performances with good ability of disturbance rejection and high stabilization accuracy are obtained for the aerial ISP. The simulations and experiments are, respectively, carried out to validate the improved FNN/PID compound control method. The results show that the improved FNN/PID compound control scheme has the excellent capability in disturbance rejection, by which the ISP’s stabilization accuracy under dynamic disturbance is improved significantly.

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS®; then, to analyze the system’s kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB® SIMULINK® controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance.

This article presents an extended state observer/proportion integration differentiation compound control scheme based on dynamic modelling for a three-axis inertially stabilized platform applied for aerial remote sensing. To reveal the effects of dynamic couplings among different gimbals and the base on the system control performance, the dynamic modelling of the inertially stabilized platform system is developed. Then, an extended state observer /proportion integration differentiation composite controller is designed to improve the tracking precision and stability of the inertially stabilized platform, whose disturbance rejection ability is analysed by simulations. During simulation analysis, the LuGre friction model is introduced to represent the effects of main disturbance torques. To verify the method, the experiments are conducted. The results show that the extended state observer/proportion integration differentiation compound scheme has excellent capability in disturbance rejection, by which the stabilization accuracy of the inertially stabilized platform has improved significantly.

This article describes an adaptive fuzzy/proportion integration differentiation (PID) compound control scheme to promote the disturbance rejection ability of an aerial inertially stabilized platform. To deal with the serious influence of predominant unbalance torque disturbance on the steady precision of inertially stabilized platform, dynamic modeling and simulation analysis are conducted, which reveal that the unbalance torque disturbance is nonlinear and time varying. Then, an adaptive fuzzy/PID compound controller is designed that can automatically adjust and control parameters of the system in real time. In this way, the effects of unbalance torque disturbance on control performance are suppressed greatly so that the pointing accuracy and stability are obviously improved. To validate the scheme, the simulations and experiments are conducted to a real three-axis inertially stabilized platform. The results show that under the environment of unbalance torque disturbance, the inertially stabilized platform could reach better dynamic performances by the compound scheme, leading to the high pointing accuracy and stability.

Flue dust generated during the process of manufacturing corundum is a carrier of critical metal gallium. In this study, a process of alkali leaching-carbonation-acid leaching-solvent extraction was developed to recover and enrich gallium from corundum flue dust. Over 93% of the gallium in corundum flue dust could be recovered through a two-stage alkali leaching process, which consists of 120 min of concentrated alkali leaching in NaOH solution and a subsequent 30-min dilute alkali leaching (after dilution), with an alkali-to-ore mass ratio of 1.2:1. Liquid to solid ratios in two alkali leaching stages were 1.5:1 and 8:1, respectively. The carbonation process was employed to remove high-level Si in alkali leachate. After carbonation and HCl leaching, over 96% of gallium in the NaOH leachate could be dissolved into acid solution. After extracting gallium from the HCl leachate using N235 as extracting agent, 1% NaOH solution was used to strip gallium from the organic phase. The extraction and stripping efficiency of gallium was over 99% and 97%, respectively.

Lithium-sulfur (Li-S) batteries have been identified as the greatest potential next- generation energy-storage systems because of the large theoretical energy density of 2600 Wh kg−1. However, its practical application on a massive scale is impeded by severe capacity loss resulted from the notorious polysulfides shuttle. Here, we first present a novel technique to synthesize sandwich-type nitrogen and sulfur codoped graphene-backboned porous carbon (NSGPC) to modify the commercial polypropylene separator in Li-S batteries. The as-synthesized NSGPC exhibits a unique micro/mesoporous carbon framework, large specific surface area (2439.0 m2 g−1), high pore volume (1.78 cm3 g−1), good conductivity, and in situ nitrogen (1.86 at %) and sulfur (5.26 at %) co-doping. Benefiting from the particular physical properties and chemical components of NSGPC, the resultant NSGPC-coated separator not only can facilitate rapid Li+ ions and electrons transfer, but also can restrict the dissolution of polysulfides to alleviate the shuttle effect by combining the physical absorption and strong chemical adsorption. As a result, Li-S batteries with NSGPC-coated separator exhibit high initial reversible capacity (1208.6 mAh g−1 at 0.2 C), excellent rate capability (596.6 mAh g−1 at 5 C), and superior cycling stability (over 500 cycles at 2 C with 0.074% capacity decay each cycle). Propelling our easy-designed pure sulfur cathode to a extremely increased mass loading of 3.4 mg cm−2 (70 wt. % sulfur), the Li-S batteries with this functional composite separator exhibit a superior high initial capacity of 1171.7 mAh g−1, which is quite beneficial to commercialized applications.

The influence of diaphragm bending stiffness distribution on the stress concentration characteristics of a pressure sensing chip had been analyzed and discussed systematically. According to the analysis, a novel peninsula-island-based diaphragm structure was presented and applied to two differenet diaphragm shapes as sensing chips for pressure sensors. By well-designed bending stiffness distribution of the diaphragm, the elastic potential energy induced by diaphragm deformation was concentrated above the gap position, which remarkably increased the sensitivity of the sensing chip. An optimization method and the distribution pattern of the peninsula-island based diaphragm structure were also discussed. Two kinds of sensing chips combined with the peninsula-island structures distributing along the side edge and diagonal directions of rectangular diaphragm were fabricated and analyzed. By bonding the sensing chips with anti-overload glass bases, these two sensing chips were demonstrated by testing to achieve not only high sensitivity, but also good anti-overload ability. The experimental results showed that the proposed structures had the potential to measure ultra-low absolute pressures with high sensitivity and good anti-overload ability in an atmospheric environment.

Estimation of soil moisture distribution in desert regions is challenged by the deep unsaturated zone and the extreme natural environment. In this study, an entropy-based method, consisting of information entropy, principle of maximum entropy (PME), solutions to PME with constraints, and the determination of parameters, is used to estimate the soil moisture distribution in the 10 m deep vadose zone of a desert region. Firstly, the soil moisture distribution is described as a scaled probability density function (PDF), which is solved by PME with the constraints of normalization, known arithmetic mean and geometric mean, and the solution is the general form of gamma distribution. A constant arithmetic mean is determined by considering the stable average recharge rate at thousand year scale, and an approximate constant geometric mean is determined by the low flow rate (about 1 cm a year). Followed, the parameters of the scaled PDF of gamma distribution are determined by local environmental factors like terrain and vegetation: the multivariate linear equations are established to qualify the relationship between the parameters and the environmental factors on the basis of nineteen random soil moisture profiles about depth through the application of fuzzy mathematics. Finally, the accuracy is tested using correlation coefficient (CC) and relative error. This method performs with CC larger than 0.9 in more than a half profiles and most larger than 0.8, the relative errors are less than 30% in most of soil moisture profiles and can be as low as less than 15% when parameters fitted appropriately. Therefore, this study provides an alternative method to estimate soil moisture distribution in top 0–10 m layers of the Badain Jaran Desert based on local terrain and vegetation factors instead of drilling sand samples, this method would be useful in desert regions with extreme natural conditions since these environmental factors can be obtained by remote sensing data. Meanwhile, we should bear in mind that this method is challenged in humid regions since more intensive and frequent precipitation, and more vegetation cover make the system much more complex.

A compound control scheme is proposed to achieve high control performance for a two-axis inertially stabilized platform (ISP) with multi-sensors applied to an unmanned helicopter (UH)-based airborne power line inspection (APLI) system. Compared with the traditional two closed-loop control scheme that is composed of a high-bandwidth rate loop and a lower bandwidth position loop, a new current loop inside rate loop is particularly designed to suppress the influences of voltage fluctuation from power supply and motor back electromotive force (BEMF) on control precision. In this way, the stabilization accuracy of the ISP is greatly improved. The rate loop, which is the middle one, is used to improve sensor’s stability precision through compensating for various disturbances. To ensure the pointing accuracy of the line of sight (LOS) of multi-sensors, the position loop is designed to be the outer one and acts as the main feedback path, by which the accurate pointing angular position is achieved. To validate the scheme, a series of experiments were carried out. The results show that the proposed compound control scheme can achieve reliable control precision and satisfy the requirements of real APLI tasks.