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Abstract Suitable and effective matching area selection is crucial for gravity matching‐aided navigation. In this paper, an all‐field extended extremum algorithm based on an adaptive threshold (AT‐AEE) is proposed for matching area selection in the Arctic Sea. The gradient data is obtained by using the convolution of gravity reference graph data and all‐field extended extremum parameters. Then, the adaptive threshold method was employed to determine the optimal gradient threshold based on gravity anomaly data across various test areas. Data points with gradients exceeding the specified threshold are identified as local candidate points for matching areas. The test areas containing a certain proportion of local candidate points are designated as the suitable matching areas. Nine test areas in the Arctic Sea with different gravity change characteristics were chosen for simulation experiments to verify the performance of the proposed algorithm. Simulation experiments showed that superior navigation positioning results could be obtained in the matching areas selected by the AT‐AEE algorithm. Compared to traditional algorithm, the matching areas derived from the AT‐AEE algorithm performed with a better consistency in the gravity matching navigation results. In suitable matching areas with the proportion of local candidate points reaching 70%, the average positioning errors could be reduced to less than 1.5 n miles.

Objectives To evaluate the minimal clinically important difference (MCID) value for acupuncture treatment in chronic spontaneous urticaria (CSU), providing guidance for its application in CSU management.Design Secondary analysis of data from a multicentre randomised controlled trial.Setting Three tertiary hospitals across three cities in China.Participants 103 CSU patients (78.7% female) with an average age of 39.97 years.Interventions Participants received acupuncture treatment for 4 weeks in the original study.Outcome measures MCID and minimal detectable change (MDC) for the Urticaria Activity Score over 7 days (UAS7) in acupuncture treatment of CSU. Convergent validity assessed by intraclass correlation coefficient (ICC). Responsiveness evaluated through Spearman correlation between UAS7 improvements and anchor tools (physician’s and patient’s assessments). MDC calculated using SE of measurement of changes in UAS7 scores. MCID estimated using distribution-based and anchor-based methods.Results The ICC for UAS7 was 0.86. Improvements in UAS7 scores were significantly correlated with patient (r=0.44, p

Seed germination is the process by which an organism grows from a seed. It requires suitable conditions and environmental factors. Maize is one of the most important crops worldwide. Germination influences both final maize yield and quality. Seed germination is regulated by a complex gene network. It is also influenced by endogenous (phytohormones and nutrients) and exogenous (temperature and water) inputs, involving molecular networks only partly identified to date. This review describes current understanding of the influence of temperature, water, phytohormones, and nutrients in regulating maize seed germination, and indicates knowledge gaps that should be addressed.

Abstract Seed germination is the process through which a quiescent organ reactivates its metabolism culminating with the resumption cell divisions. It is usually the growth of a plant contained within a seed and results in the formation of a seedling. Post-transcriptional regulation plays an important role in gene expression. In cells, post-transcriptional regulation is mediated by many factors, such as RNA-binding proteins, microRNAs, and the spliceosome. This review provides an overview of the relationship between seed germination and post-transcriptional regulation. It addresses the relationship between seed germination and RNA-binding proteins, microRNAs and alternative splicing. This presentation of the current state of the knowledge will promote new investigations into the relevance of the interactions between seed germination and post-transcriptional regulation in plants.

For inertial navigation systems (INS), as one of the major methods for underwater navigation, errors diverge over time. With the development of geophysical navigation technology, gravity navigation has become an effective method of navigation. Significant changes in the gravity characteristic of the matching region ensure that gravity matching navigation works effectively. In this paper, we combine artificial intelligence algorithms and statistical metrics to classify gravity-matching navigation regions. Firstly, this paper analyzes and extracts gravity anomaly data from a matching region in different ways. Then, a particle swarm optimization (PSO) algorithm is used to optimize the network weights of a back propagation (BP) NN. Finally, based on principal component analysis (PCA) theory and PSO-BP NN, this paper proposes the PPBA method to classify the matching area. Moreover, the Terrain Contour Matching (TERCOM) matching algorithm and gravity anomaly data from the Western Pacific are used to verify the classification performance of the PPBA method. The experiments prove that the PPBA method has a high classification accuracy, and the classification results are consistent with the matching navigation experimental results. This work can provide a reference for designing navigation regions and navigation routes for submarines.

Under the “dual carbon” goal, the core issue at present is to improve the environment while ensuring economic development. As a result, green finance, that is a tool that integrates finance and environmental protection, has shown increasingly significant carbon reduction effects. With the panel data of 30 provinces in China from 2012 to 2021 being the research object, this study employs a spatial Durbin model to examine the impact of green finance on carbon emissions and further discusses its mechanism effects. The empirical results indicate the following: firstly, the development of green finance effectively suppresses carbon emissions; secondly, by decomposing the spatial effect of green finance on carbon emissions, it is found that green finance also reduces carbon emissions in neighboring regions due to the spillover effects; finally, green finance can suppress carbon emissions through technological innovation and industrial structure upgrading. Therefore, it is imperative to actively engage in practical work related to green finance, to establish a sound system for green finance, and simultaneously, to enhance cooperation among regions in terms of green finance, in order to fully leverage its role in suppressing carbon emissions.

By designing several extrusion parameters, the Mg-0.12Ca-0.08Ba (wt%) alloy with dilute alloy content was processed, the microstructure and tensile property of alloys have been reasonably examined by means of electron backscattered diffraction, scanning electron microscopy and X-ray diffraction. The results demonstrate the grains of Mg-0.12Ca-0.08Ba alloys are refined after extrusion, and the alloys form uniform dynamic recrystallized grains. There are two different types of texture components in the extruded alloy, rare earth texture and extruded fiber texture, which crystallographic orientation is ∥ED and ∥ED, respectively. This “rare earth texture” component was found to be suppressed at high extrusion temperatures. The extrudants at 380 °C exhibits the best performance, its yield strength (YS) and ultimate tensile strength (UTS) are 197 MPa and 252 MPa, respectively, and the elongation-to-fracture (EL) is 33.1%. The plastic enhancement after extrusion mainly comes from grain refinement and texture weakening in the alloys.

The J-TEXT capability is enhanced compared to two years ago with several upgrades of its diagnostics and the increase of electron cyclotron resonance heating (ECRH) power to 1 MW. With the application of electron cyclotron wave (ECW), the ECW assisted plasma startup is achieved; the tearing mode is suppressed; the toroidal injection of 300 kW ECW drives around 24 kA current; fast electrons are generated with toroidal injected ECW and the runaway current conversion efficiency increases with ECRH power. The mode coupling between 2/1 and 3/1 modes are extensively studied. The coupled 2/1 and 3/1 modes usually lead to major disruption. Their coupling can be either suppressed or avoided by external resonant magnetic perturbation fields and hence avoids the major disruption. It is also found that the 2/1 threshold of external field is significantly reduced by a pre-excited 3/1 mode, which can be either a locked island or an external kink mode. The disruption control is studied by developing prediction methods capable of cross tokamak application and by new mitigation methods, such as the biased electrode or electromagnetic pellet injector. The high-density operation and related disruptions are studied from various aspects. Approaching the density limit, the collapse of the edge shear layer is observed and such collapse can be prevented by applying edge biasing, leading to an increased density limit. The density limit is also observed to increase, if the plasma is operated in the poloidal divertor configuration or the plasma purity is increased by increasing the pre-filled gas pressure or ECRH power during the start-up phase.

Color consistency optimization for multiple images is a challenging task in remote sensing and computer vision. To ensure that the visual quality of corrected images is satisfactory, not only should the color discrepancies between multiple images be invisible but also the contrast of individual images should be visually appealing. Most color correction approaches focus on eliminating drastic color discrepancies, but ignore the problem of image contrast enhancement. Some color correction approaches even tend to degrade the image contrast to ensure that the image tones are consistent especially when the contrast of input images is low. To solve this problem, we present a contrast-aware color consistency correction approach in this article. We attempt to eliminate the drastic color differences and enhance the contrast of input images simultaneously. We creatively integrate the problems of color consistency correction and image contrast enhancement into the same global energy optimization framework, and we also design a special cost function to minimize the color discrepancies and enhance the image contrast using the original color information. Thus, although the contrast of input images is low, our approach can still generate the corrected images with consistent tones and visually appealing contrast. At last, we select several challenging datasets to evaluate our approach. The experimental results visually and quantitatively demonstrate the effectiveness and superiority of the proposed contrast-aware color consistency correction approach. The results also demonstrate that our approach significantly outperforms the existing approaches, especially when the contrast of the input images is low.

Abstract Background Person-centered care is widely recognized as a gold standard and is based on a supportive psychosocial climate for both residents and staff in nursing homes. Residents and staff may have different perspectives as to whether the climate in which they interact is person-centered, perhaps due to their different expectations of the nursing home environment and the provision of care services. The aim of this study was to explore and compare resident and staff perspectives of person-centered climate in aged care nursing homes. Methods This is a descriptive cross-sectional study using a cluster random sampling method. The study collected data in 2016 from residents (n = 251) and nursing staff (n = 249) in 23 nursing homes using a Person-centered Climate Questionnaire-Patient version and Person-centered Climate-Staff version. T-tests for independent-samples were used to compare scores ranked by nursing staff and residents. Results The mean scores of ‘A climate of safety’ subscale and ‘A climate of everydayness’ subscale rated by residents were significantly lower than those rated by nursing staff. The mean scores of ‘A climate of hospitality’ rated by residents were very low among the three subscales, an indicator of the need to improve a more home-like environment for residents. Residents in larger size nursing homes showed a higher score of person-centered climate compared with their counterparts in small size nursing homes. Conclusions This study reveals that the perspectives and perceptions of person-centered climate differ between residents and nursing staff. Therefore, both resident and staff perspectives should be taken into account in attempting to improve person-centered climate for better care outcomes.

Talent is an important strategic resource for regional economic development. Based on the background of “the talent war” that has broken out between various cities in recent years, this study empirically verified the influence of the talent policy on urban innovation in 277 prefecture-level cities in China from 2010 to 2019 using the multi-period difference-in-differences model. The results indicated that “the talent war” caused by the talent policy has positively influenced urban innovation, causing, for instance, a dramatic increase in the number of patents for inventions. Among the subsidy methods of “the talent war” policy, the employment and entrepreneurship subsidy had the greatest incentive effect on urban innovation, followed by the talent housing subsidy. Moreover, the “the talent war” policy exerted a positive impact on urban innovation by improving the innovation willingness of cities and the level of talent gathering. At present, “the talent war” cities have, to a certain extent, restrained the improvement of urban innovation in neighboring cities because of the siphon effect, resulting in the division of the regional labor market. A heterogeneity analysis showed that “the talent war” has significantly promoted substantive innovation and the development of coastal cities with a better business environment and a higher degree of intellectual property protection.

The utilization of upper extremity exoskeleton robots has been proved to be a scientifically effective approach for rehabilitation training. In the process of rehabilitation training, it is necessary to detect the fatigue degree during rehabilitation training in order to formulate a reasonable training plan and achieve better training efficiency. Based on the integral value of surface electromyography (sEMG), heart rate variability, and instantaneous heart rate, this article proposes a fatigue judgment method for multi-information fusion. Based on the integral value data, the feature extraction of the bioelectrical signals were implemented separately, then the fatigue recognition was conducted using the decision-level data fusion method. The bioelectrical signal acquisition system of electromyogram signals and electrocardiograph signals was developed for upper limb exoskeleton rehabilitation robot, and the acquisition and processing of electromyogram signals and electrocardiograph signals were completed. Finally, the fuzzy logic controller with instantaneous heart rate, heart rate variability, and surface electromyography signal was designed to judge fatigue degree, including the fuzzy device, fuzzy rule selector, and defuzzifier. The moderate fatigue state data were selected for testing, and the experimental results showed that the error of fatigue judgment is 4.3%, which satisfies the requirements of fatigue judgment.

The human embryonic stem cell (hESC) line NERCe002-A-1 was generated through lentiviral transduction of the original NERCe002-A-1 hESC line with Zoanthus sp. green fluorescent protein (ZsGreen). Cells that expressed ZsGreen showed a >8.6-fold increase in fluorescence intensity compared with that of cells that expressed enhanced green fluorescent protein. The fluorescent hESC line can aid in identification of biological characteristics in vitro and in vivo by tracking cell growth, migration, and differentiation. Characteristic tests confirmed that the NERCe002-A-1 cell line expressed typical markers of pluripotency and had the capability to form the three germ layers in vivo.

The human embryonic stem cell line NERCe002-A-2 was generated by transduction of NERCe002-A cells with an expression vector carrying the luciferase gene. The stem cells labelled with luciferase can be transplanted into animals and detected by the bioluminescence imaging technology. This provides optimal prospects of application to in vivo stem cell tracing. Luciferin served as a substrate to detect the activity of luciferase, and luciferase expression was measured by quantitative PCR. Characterization assays suggested that the NERCe002-A-2 cell line expresses typical markers of pluripotency and can form the 3 germ layers in vivo.

In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas.