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This study examined how the properties of semantic radicals affect character meaning inference among adult learners of Chinese as a foreign language (CFL). A semantic radical is a component of a compound character whose primary function is to provide an aspect of the meaning of its host character. Because radicals differ in the nature of the information they supply and their relationships with the characters' meaning, their functions are not uniformly salient to users. This study focused on the notion of radicalfunctional salienceand its impacts on character learning and processing. In Study 1, we identified radical properties pertinent to functional salience via a sequence of property analyses, and determined how the identified properties were related to perceived familiarity with commonly used radicals among native Chinese speakers. Based on the analyses, in Study 2, we examined how functional salience affects the way CFL learners use radical information through character meaning extraction and inference tasks. The results demonstrated that functional salience was differentially related to performance variances. The findings suggest that CFL learners' use of radical information during character processing is explained jointly by the properties of semantic radicals and learners' radical knowledge. [ABSTRACT FROM PUBLISHER]

This study examined contribution of morphological awareness to reading comprehension in two typologically diverse languages, focusing on young Chinese EFL (English as a Foreign Language) readers in China. It was particularly interested in how cross-linguistic similarities and variations in morphological awareness affected its transfer in Chinese–English biliteracy acquisition. Grades 5 and 6 children were measured in compound awareness and reading comprehension in English, and compound awareness, radical awareness, and reading comprehension in Chinese. Hierarchical regression analyses revealed that compound awareness contributed to reading comprehension within both Chinese and English. In addition, over and above English compound awareness and Chinese reading comprehension, Chinese compound awareness, but not radical awareness, explained a unique amount of variance in English reading comprehension. After Chinese compound awareness was controlled for, English compound awareness, however, did not make a significant contribution to Chinese reading comprehension. These findings were discussed in light of the common and language/script-dependent aspects of morphological awareness in Chinese and English and the context of biliteracy acquisition. [ABSTRACT FROM AUTHOR]

Abstract: Thin films of La0.85Sr0.15MnO3 (LSM) are deposited on (100) silicon wafer and YSZ (yttria-stabilized zircornia) electrolyte substrates by magnetron sputtering using a single-phase LSM target. The conditions for sputtering are systematically studied, including substrate temperature (from room temperature to 600°C), the argon background pressure (from 1.2×10−2 to 3.0×10−2 mbar), and deposition time. Results show that the optimal conditions for producing a dense, uniform, and crack-free LSM film include a substrate temperature of 600°C and an argon pressure of 1.9×10−2 mbar. Further, a testing cell with a dense LSM film, an YSZ electrolyte membrane, and a porous LSM counter electrode is prepared and the electrochemical properties of the dense LSM film on YSZ substrate are studied. It was found that the thickness, morphology, and microstructure of LSM films critically influence the electrochemical properties. [Copyright &y& Elsevier]

The human eye has the behavior of fixation shift, which is represented by visual search mechanism. Human visual search mechanism has the characteristics of visual guidance from global to local. In order to imitate this behavior, this paper proposes a novel salient object detection model which integrates global and local perception based on visual search guidance. First, by using multi-level feature complementarity, a coarse global perceptual map can be obtained by encoding VGG network and decoding deconvolution network. Then, through the Maximally Stable External Regions (MSER) algorithm, the local hotspot sub-regions in the coarse global perceptual map are intercepted, and generating a visual guidance search path based on the maximum response principle, and the local fine perceptual map is successively merged through the Squeeze-and-Excitation Networks (SENet) step by step. Finally, the salient map integrating the coarse global and fine local perception is achieved. Because only one local area needs to be integrated at a time, which is equivalent to solving a relatively simple problem at a time, it is easy to get more accurate results. The experimental results show that the time-consuming of our model is relatively low and compared with the classical and more recent SOTA methods, our model also shows competitive results. • A global to local visual perceptual integration model for salient object detection is proposed. • It improves the precision of global coarse sensing through local fine sensing. • This paper realizes the dynamic observation behavior from global to local. • Exhibits excellent performance in salient object detection experiments is achieved. [ABSTRACT FROM AUTHOR]

Abstract: In the present study, thermal barrier coatings (TBCs) with two layered bond coat of MCrAlY and MCrAlY–Si were prepared by means of electron beam physical vapor deposition (EB-PVD) on Ni3Al based alloy IC6 in order to suppress the diffusion of Mo contained in the alloy. For the bond coat without Si addition, Mo content near the surface was higher than 7wt% after isothermal oxidation at 1373K for 60h and 12.5wt% after thermal cycling tested at 1373K for 300h (600 cycles). However, in the two layered bond coat with MCrAlY and MCrAlY–Si, only 0.4wt% Mo was detected after isothermal oxidation at 1373K for 100h and about 0.6wt% after thermal cycling tested at 1373K for 400h (800 cycles). With the use of two layered bond coat of MCrAlY and MCrAlY–Si, the diffusion of Mo was effectively blocked and the thermal cycling behavior of the TBCs has been greatly improved. [Copyright &y& Elsevier]

Ni3Al based alloy IC6, a high performance cast alloy with approximately 14 wt.% Mo addition, has been developed for turbine blades and vanes of advanced aero-engines and other high temperature structural components. However, because of the high Mo content, during high temperature use, Mo will diffuse into the protective coating layer, which will affect the thermal cycling performance directly. In order to block the diffusion and improve the thermal cycling behavior of thermal barrier coatings (TBCs), a Si chemical gradient MCrAlY&z.sbnd;Si bond coat was prepared by changing the Si content from 0.35 wt.% at the interface of substrate and bond coat to almost 0 near to the surface of the bond coat. For comparison, conventional two-layered structural TBCs with MCrAlY as bond coat were also prepared. The fabricated coatings were evaluated for the microstructures and the composition distribution properties, such as thermal stability and resistance to oxidation. For the bond coat without Si addition, Mo content near the surface was higher than 7 wt.% after isothermal oxidation at 1373 K for 60 h and 12.5 wt.% after thermal cycling tested at 1373 K for 300 h (600 cycles). However, in the Si chemical gradient bond coat, only 0.4 wt.% Mo was detectable after isothermal oxidation at 1373 K for 100 h and approximately 0.66 wt.% after thermal cycling tested at 1373 K for 340 h (680 cycles). [Copyright &y& Elsevier]

Single image deraining as a fundamental task in computer vision is important in improving the visual quality of images and videos. In this paper, we propose a feature-guided dictionary learning method for patch-and-group sparse representation in single image deraining. Specifically, we develop an external dictionary that learns the generic feature representation from a lot of natural images using Gaussian mixture models (GMMs), and a novel strategy is designed to learn an internal dictionary using the given rainy image guiding by the generic features. The external dictionary and the internal dictionary are adaptively tailored to produce a coherent dictionary, which can extend the representation abilities of the learned dictionary for the group-based sparse representation. Moreover, we present a novel patch-and-group sparse representation framework to reconstruct an image tending to be free of rain by simultaneously combining the local sparsity and the nonlocal self-similarity property. This framework can integrate their advantages of the two representative methods capable of capturing more effective features for the single image deraining. The results of experiments on both the synthetic and the real-world rainy images demonstrate that the proposed method delivers more favorable visual effects and superior quality results, and it outperforms several other state-of-the-art methods. • A feature-guided dictionary learning method is proposed for single image deraining. • A coherent dictionary is learned using the rainy image guided by a lot of natural images. • A patch-and-group sparse representation framework is applied to reconstruct an image tended to be free of rain. • Experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Isorhamnetin (ISO) is an active flavonoid compound mainly isolated from the fruits of Hippophae rhamnoides L. and the leaves of Ginkgo biloba L. Previous studies have revealed the antifibrotic action of ISO in the liver and lungs, although its potential protective effects against renal fibrosis and the underlying mechanisms are still poorly understood. Given that many actions of ISO could be similarly attained by hydrogen sulfide (H2S), we speculated that ISO may work through the induction of endogenous H2S. To test the hypothesis, we established the unilateral ureteral obstruction (UUO) renal fibrosis rat model and transforming growth factor-β1(TGF-β1)-induced fibrosis in cultured renal tubular cells. ISO treatment inhibited epithelial–mesenchymal transition (EMT) formation, decreased extracellular matrix (ECM) deposition, and relieved renal fibrosis. Further analysis revealed that ISO stimulated the expression of the H2S-synthesizing enzyme cystathionine lyase (CSE) and cystathionine beta-synthase (CBS), and promoted H2S production in vivo and in vitro. The elevated H2S attenuated oxidative stress and elevated the thiol level. It induced Keap1 sulfhydration, disrupted Keap1-Nrf2 interaction, and promoted the entry of Nrf2 into the nucleus. Finally, we found that circulating H2S mainly derived from the liver, and not the kidney. Collectively, our study revealed that ISO alleviated renal fibrosis by inducing endogenous H2S and regulating Keap1-Nrf2 interaction through sulfhydration of Keap1. Endogenous H2S could be an important mediator underlying the pharmacological actions of ISO. Due to the multifunctional properties of H2S, the H2S-inducing nature of ISO could be exploited to treat various diseases. [ABSTRACT FROM AUTHOR]

Objective: The nutritional status and inflammatory responses of patients with aneurysmal subarachnoid hemorrhage (aSAH) play a vital prognostic role. We investigated the relationship between preoperative prognostic nutritional index (PNI)、neutrophil/albumin ratio (NAR)、platelet/albumin ratio (PAR) and other factors and the clinical prognosis of patients who underwent clipping for aSAH and its predictive model. Methods: The clinical data of 212 patients with aSAH who underwent neurosurgery at Nanyang Central Hospital between 2018 and 2023 were retrospectively analyzed. Based on the Glasgow Outcome Scale (GOS) score at 6 months postoperatively, the patients were categorized into two groups: poor (GOSI-III) and good (GOSIV-V) prognosis groups. Multivariate logistic regression analysis was performed to determine the predictive value of preoperative PNI、NAR、PAR、hyperlipidemia and Glasgow Coma Scale (GCS) for prognosis. Furthermore, nomograms and prognostic prediction models were constructed. Receiver operating characteristic curves and area under the curve (AUC) were utilized to determine the predictive values. Results: Multivariate logistic regression analysis revealed that PNI (OR = 1.250, 95%CI 1.060 ~ 1.475, P = 0.008), NAR (OR = 0.000, 95%CI 0.000 ~ 0.004, P = 0.000), PAR(OR = 0.515, 95%CI 0.283 ~ 0.937, P = 0.030), hyperlipidemia (OR = 4.627, 95%CI 1.166 ~ 18.367, P = 0.029), and GCS(OR = 1.446, 95%CI 1.041 ~ 2.008, P = 0.028) are independent risk factors for poor postoperative prognosis. The total score of the nomogram was 200, and the AUC value was 0.972. Conclusions: PNI and NAR can reflect the nutritional status and inflammatory responses of patients.They are significantly associated with the postoperative prognosis of patients with aSAH. Comprehensively analyzing PNI and NAR combined with other clinical indicators can more effectively guide treatment and help predict prognosis. [ABSTRACT FROM AUTHOR]

Multilevel thresholding image segmentation is an important technique, which has attracted much attention in recent years. The conventional exhaustive search method for image segmentation is efficient for bilevel thresholding. However, they are time expensive when dealing with multilevel thresholding image segmentation. To better tackle this problem, an improved cuckoo search algorithm (ICS) is proposed to search for the optimal multilevel thresholding in this paper, and Otsu is considered as its objective function. In the ICS, two modifications are used to improve the standard cuckoo search algorithm. First, a parameter adaptation strategy is utilized to improve exploration performance. Second, a dynamic weighted random-walk method is adopted to enhance the local search efficiency. A total of six benchmark test images are used to perform the experiments, and seven state-of-the-art metaheuristic algorithms are introduced to compare with the ICS. A series of measure indexes such as objective function value and standard deviation, PSNR, FSIM, and SSIM as well as the Wilcoxon rank sum and convergence performance are performed in the experiments; the experimental results show that the proposed algorithm is superior to other seven well-known heuristic algorithms. [ABSTRACT FROM AUTHOR]

This study examined the crosslinguistic sharing of morphological awareness (MA) in biliteracy development. The analysis included 34 correlational studies with 41 independent samples (N = 4,104). Correlational coefficients were meta‐analyzed, yielding four main findings: (a) the correlation between first language (L1) and second language (L2) MA was small (r =.30); (b) the interlingual correlations between L1 MA and L2 word decoding and between L1 MA and L2 reading comprehension were both small (r =.35,.39, respectively); (c) the intralingual correlations between L2 MA and L2 word decoding and between L2 MA and L2 reading comprehension were both moderate (r =.46,.52, respectively); and (d) MA measurement type and age were significant moderators. Our review suggests that there is a need for future research to align the definition and measurement of MA. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aimed to investigate the safety and long-term survival outcomes of salvage liver resection in patients with initially unresectable hepatocellular carcinoma (HCC) who had undergone triple combination conversion therapy (TACE/HAIC + TKIs + ICIs). While hepatectomy following conversion therapy exhibited elevated incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure, and Clavien–Dindo grade IIIa complications compared to pure hepatectomy, their safety profiles remained acceptable when appropriate medical interventions were administered. Patients with initially unresectable HCC, who successfully underwent conversion resection, demonstrated comparable overall survival (OS) and recurrence-free survival (RFS) to patients with initially resectable HCC. Triple combination conversion therapy, involving transcatheter arterial chemoembolization (TACE) or hepatic arterial infusion chemotherapy (HAIC) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), has shown an encouraging objective response rate (ORR) and successful conversion surgery rate in initially unresectable hepatocellular carcinoma (HCC). However, the safety and long-term survival outcomes of subsequent liver resection after successful conversion still remain to be validated. From February 2019 to February 2023, 726 patients were enrolled in this retrospective study (75 patients received hepatectomy after conversion therapy [CLR group], and 651 patients underwent pure hepatectomy [LR group]). Propensity score matching (PSM) was used to balance the preoperative baseline characteristics. After PSM, 68 patients in the CLR group and 124 patients in the LR group were analyzed, and all the matching variables were well-balanced. Compared with the LR group, the CLR group experienced longer Pringle maneuver time, longer operation time, and longer hospital stays. In addition, the CLR group had significantly higher incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure (PHLF), and Clavien–Dindo grade IIIa complications than the LR group. There were no significant statistical differences in overall survival (OS) (hazard ratio [HR] 0.724; 95% confidence interval [CI] 0.356–1.474; p = 0.374) and recurrence-free survival (RFS) (HR 1.249; 95% CI 0.807–1.934; p = 0.374) between the two groups. Liver resection following triple combination conversion therapy in initially unresectable HCC may achieve favorable survival outcomes with manageable safety profiles; presenting as a promising treatment option for initially unresectable HCC. [ABSTRACT FROM AUTHOR]

Ulcerative colitis (UC), often known as UC, is an inflammatory disease of the intestines that has frequent and long-lasting flare-ups. It is unknown precisely how the traditional Chinese drug Indigo Naturalis (IN) heals inflammatory bowel disease, despite its long-standing use in China and Japan. Finding new metabolite biomarkers linked to UC could improve our understanding of the disease, speed up the diagnostic process, and provide insight into how certain drugs work to treat the condition. Our work is designed to use a metabolomic method to analyze potential alterations in endogenous substances and their impact on metabolic pathways in a mouse model of UC. To determine which biomarkers and metabolisms are more frequently connected with IN's effects on UC, liquid chromatography-tandem mass spectrometry analysis of the serum metabolomics of UC mice and normal mice was performed. The outcomes demonstrated that IN boosted the health of UC mice and reduced the severity of their metabolic dysfunction. In the UC model, it was also found that IN changed the way 17 biomarkers and 3 metabolisms functioned. [ABSTRACT FROM AUTHOR]

The increasing imaging capability of spaceborne Synthetic Aperture Radar (SAR) systems makes a challenging task in matching slant-range (SR) SAR images acquired from different orbit and side-viewing directions. However, currently existing algorithms for the SR SAR images matching are unsatisfactory and the correct homologous points cannot be matched. In this work, a robust and adaptable high-precision method for matching flipped SAR images based on oriented descriptors is proposed. Firstly, the ratio gradient calculation based on Gabor odd filter is introduced. Secondly, the oriented descriptors are built to eliminate the diversity of feature-based descriptors of homologous points of flipped SR SAR images, enabling directly match the flipped SAR images. Finally, the feasibility and reliability of the proposed method are verified by the experimental results of simulated flipped SAR images and actual flipped SAR images, and two directional descriptors of the slave image are constructed to match non-flipped SAR images. The results show that the proposed method performs better in precision with the root mean square error (RMSE) less than 1 pixel, and the proposed oriented descriptors can match SR SAR images. [ABSTRACT FROM AUTHOR]

In this paper, to recover the missing geometry details on 3D surfaces, we develop a novel geometry detail recovery algorithm for 3D surfaces based on Empirical Mode Decomposition (EMD). EMD is a powerful tool for processing non-linear and non-stationary signals and has been successfully used in 3D surface analysis and processing. Given a signal defined on 3D surface, EMD could represent the signal in a multi-scale fashion and decompose the signal into a number of Intrinsic Mode Functions (IMFs) and a residue, which usually encode the multi-level finer-scale details and the overall shape of the signal, respectively. Benefiting from the multi-scale representation of geometry details, the EMD-based multi-scale geometry detail recovery algorithm is developed. Our strategy starts from an initial smooth filling of a hole and then transfers the desirable details from the most similar region to the smoothly-filled surface within the framework of EMD. Taking the advantages of EMD, we first apply EMD on the whole completed surface to obtain the multi-scale representation of geometry details. Then, the most similar region corresponding to the hole region is located by the patch descriptor constructed from Heat Kernel Signature (HKS). Finally, the missing geometry details can be effectively recovered by transferring the geometry details from the found similar region to the smoothly-filled surface. Traditional methods, such as context-based methods or example-based methods, usually cut the similar patch and paste them onto the hole region, and they require to match with the hole boundary, are complex in general. In contrast, our method is simple and can transfer different scale details individually or in a concerted way, which makes our algorithm more flexible and can achieve versatile detail recovery results. Comprehensive experiments and quantitative comparisons on popular models have been used to demonstrate the effectiveness of our EMD-based multi-scale geometry detail recovery algorithm. [ABSTRACT FROM AUTHOR]

Oil spill pollution from ships has always being a highly noteworthy topic in the field of marine pollution. Although shipping technology has developed rapidly in recent years, oil spills from ships have occurred over time. Analyzing the oil plume morphological evolution of ship collision-incurred oil spills is crucial for effective oil spill containment to prevent further pollution. Existing studies have not yet comprehensively examined the critical characteristic parameters of emergent containment. In this study, a three-dimensional multiphase VOF model based on a well-validated solver was developed to investigate oil plume development with a focus on the two critical aspects of emergent oil containment- L s and T s. Good validation results were achieved by analyzing the oil plume morphological evolution of oil spills from a rectangular tank. The verified model was then employed to evaluate the effects of the following parameters on L s and T s with the consideration of the effects of the ship model: For oil spills above the water surface, the cross-wind speed predominantly influences T s with minimal impacts on L s ; In the case of underwater spill, the comprehensive influences of the ship draught- d S p , leakage port size- d o , ambient current velocity- U w a t e r , ship model-current angle- θ and oil density- ρ o on the oil plume development and the subsequent emergent containment were studied in detail. These results offer crucial insights into shaping the response to emergent oil containment following ship collision-induced oil spills. • The oil plume development and its corresponding effects on the emergent oil containment for the ship collision incurred oil spills were numerically studied. • Large freeboard of the leakage port is beneficial for the emergent oil containment response. • The ship-current angle θ = 90 ° is the most unfavorable for emergent oil containment. • The ship draught, leakage port size, oil parameters and the ambient environmental parameters all influence the two critical aspects of emergent oil containment significantly. [ABSTRACT FROM AUTHOR]

Aftershocks have the potential to further aggravate the damage of masonry structures caused by mainshock. To quantitatively analyze the effect of aftershocks, this paper investigates the seismic response of unreinforced masonry structures subjected to mainshock-aftershock (M-A) sequences. Firstly, an analytical method for estimating the maximum storey drift of masonry structures subjected to M-A sequences is proposed, which is based on the non-iterative equivalent linearization method and the soft-storey failure mechanism of multi-storey masonry structures. Then, a finite element method is employed to verify the effectiveness of the proposed method. Finally, a parametric analysis is performed to evaluate the effects of aftershock intensity, anti-seismic wall area ratio, site classes, number of storeys, and mortar strength on the seismic responses of masonry structures subjected to M-A sequences, respectively. The results indicate that an excellent agreement for the maximum storey drift (θmax) between analytical and numerical results. The effect of aftershocks on masonry structures in plastic phase is more distinct than that in elastic phase. Furthermore, the effect of aftershocks on the θmax of masonry structures can be ignored when the relative intensity of aftershock is less than 0.5, and the θmax can increase by approximately 19.0% when the relative intensity of aftershock is equal to 1.0. Additionally, for the masonry structures subjected to M-A sequences, the effects of site classes on the θmax cannot be ignored, the θmax can decrease with increasing anti-seismic wall area ratio and mortar strength, and increases with increasing number of storeys. [ABSTRACT FROM AUTHOR]

Attention mechanism is beneficial to capture the contextual information in visual task. This paper proposes a feature-enhanced position attention network (FPANet) for semantic segmentation based on framework of FCN. On the top of dilated FCN, we design a feature integration module, which aggregates the context over local features by expanding the receptive field and multiscale representation, to promote a position attention module, which models spatial interdependencies over features, so as to form a feature-enhanced position attention module to enhance the discrimination of features for better semantic segmentation. Experimental comparisons show that our proposed FPANet is superior to other state-of-the-art models in the performance of segmentation accuracy on datasets PASCAL VOC 2012 and Cityscapes. [ABSTRACT FROM AUTHOR]