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Isoflurane, a commonly used inhaled anesthetic, has been found to have a cardioprotective effect. However, the precise mechanisms have not been fully elucidated. Here, we found that isoflurane preconditioning enhanced OGD/R‐induced upregulation of miR‐210, a hypoxia‐responsive miRNA, in AC16 human myocardial cells. To further test the roles of miR‐210 in regulating the effects of isoflurane preconditioning on OGD/R‐induced cardiomyocyte injury, AC16 cells were transfected with anti‐miR‐210 or control anti‐miRNA. Results showed that isoflurane preconditioning attenuated OGD/R‐induced cardiomyocyte cytotoxicity (as assessed by cell viability, LDH and CK‐MB levels), which could be reversed by anti‐miR‐210. Isoflurane preconditioning also prevented OGD/R‐induced increase in apoptotic rate, caspase‐3 and caspase‐9 activities, and Bax level and decrease in Bcl‐2 expression level, while anti‐miR‐210 blocked these effects. We also found that anti‐miR‐210 prevented the inhibitory effects of isoflurane preconditioning on OGD/R‐induced decrease in adenosine triphosphate content; mitochondrial volume; citrate synthase activity; complex I, II, and IV activities; and p‐DRP1 and MFN2 expression. Besides, the expression of BNIP3, a reported direct target of miR‐210, was significantly decreased under hypoxia condition and could be regulated by isoflurane preconditioning. In addition, BNIP3 knockdown attenuated the effects of miR‐210 silencing on the cytoprotection of isoflurane preconditioning. These findings suggested that isoflurane preconditioning exerted protective effects against OGD/R‐induced cardiac cytotoxicity by regulating the miR‐210/BNIP3 axis. Isoflurane preconditioning elicited cardioprotection against OGD/R‐induced cardiomyocyte injury via maintaining mitochondrial function by regulating the miR‐210/BNIP3 axis. Our study provided new evidence for the underlying molecular mechanisms of protective effects of isoflurane preconditioning against OGD/R‐induced injury in cardiomyocytes. [ABSTRACT FROM AUTHOR]

As a hot research field at present, computer vision is devoted to the rapid acquisition and application of target information from images or videos by simulating human visual mechanism. In order to improve the accuracy and efficiency of image detection, image saliency region detection technology has received more and more attention in the field of computer vision research; an important research content in the field, the core part of which lies in the research on algorithms related to feature extraction and saliency calculation of targets. This paper analyzes the multi‐feature fusion saliency detection model and visual saliency calculation process, and based on the existing algorithm, by improving the VGG16 network, a fully convolutional network saliency detection algorithm is proposed. The qualitative and quantitative experimental results show that compared with the four mainstream methods of BL, GS, SF, and RFCN, our algorithm not only improves the accuracy of salient object detection, but also effectively solves the problem of target edge blur. Therefore, this study has improved the accuracy and efficiency of saliency detection, which can not only promote the development of computer vision technology, but also provide support for research in the field of image processing. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) in grasslands not only plays an important role in carbon cycle but also largely affects soil function and thus determines grasslands' productivity. However, the influence mechanism of different factors on SOC storage in grasslands of northern China remains unclear. Based on an extensive field investigation and multiple statistical approaches, we mapped SOC of the grassland in northern China, and explored their correlations with climatic factors, biological factors, human activity intensity (HAI), and soil physicochemical factors. The effects of these factors on SOC were also analyzed by structural equation model. The results showed that the SOC varied across the regions and was strongly correlated with soil chemical factors (i.e., soil total nitrogen [TN], amorphous Al, and amorphous Fe) and soil physical factors (i.e., clay, silt, and sand). HAI, which was mainly influenced by grazing, had a significant but negative impact on SOC. Different from previous studies, we found that climatic factors such as temperature and precipitation indirectly affected SOC by influencing biological factors such as vegetation coverage, vegetation height, Shannon–Weiner index, and species richness. The soil physicochemical properties and HAI were the dominant influencing factors for controlling SOC distribution in the grasslands of northern China. Our findings will further increase the understanding of the carbon cycle in grassland ecosystems, while providing important scientific references for temperate grassland ecosystem management. [ABSTRACT FROM AUTHOR]

Background: Neuroblastoma is one common pediatric malignancy notorious for high temporal and spatial heterogeneities. More than half of its patients develop distant metastases involving vascularized organs, especially the bone marrow. It is thus necessary to have an economical, noninvasive method without much radiation for follow‐ups. Radiomics has been used in many cancers to assist accurate diagnosis but not yet in bone marrow metastasis in neuroblastoma. Methods: A total of 182 patients with neuroblastoma were retrospectively collected and randomly divided into the training and validation sets. Five‐hundred and seventy‐two radiomics features were extracted from magnetic resonance imaging, among which 41 significant ones were selected via T‐test for model development. We attempted 13 machine‐learning algorithms and eventually chose three best‐performed models. The integrative performance evaluations are based on the area under the curves (AUCs), calibration curves, risk deciles plots, and other indexes. Results: Extreme gradient boosting, random forest (RF), and adaptive boosting were the top three to predict bone marrow metastases in neuroblastoma while RF was the most accurate one. Its AUC was 0.90 (0.86–0.93), F1 score was 0.82, sensitivity was 0.76, and negative predictive value was 0.79 in the training set. The values were 0.82 (0.71–0.93), 0.80, 0.75, and 0.92 in the validation set, respectively. Conclusions: Radiomics models are likely to contribute more to metastatic diagnoses and the formulation of personalized healthcare strategies in clinics. It has great potential of being a revolutionary method to replace traditional interventions in the future. [ABSTRACT FROM AUTHOR]

Grammatical and vocabulary knowledge (i.e., breadth and depth) are widely acknowledged as key predictors of reading comprehension in a second language (L2). However, it remains unclear how different aspects of vocabulary depth may independently contribute to L2 reading comprehension and how learners' proficiency may moderate the relative contributions of vocabulary knowledge. Based on the Lexical Quality Hypothesis and the Reading Systems Framework, this study investigated 238 L2 Chinese learners who were college‐level students in China, using a set of reading‐related tasks. The results showed that (1) vocabulary breadth and grammatical knowledge independently contributed to L2 reading comprehension with grammatical knowledge being a more deciding factor; (2) different aspects of vocabulary depth (i.e., polysemy and synonymy), over and above vocabulary breadth and grammatical knowledge, played an independent role; and (3) more importantly, lower‐proficiency learners relied more on vocabulary breadth whereas higher‐proficiency learners made more use of vocabulary depth during text‐level comprehension. The Challenge: Do you really know this word during reading? What specifically do you know of the word, including its relationship with other words? These are an issue of vocabulary depth. How do different aspects of vocabulary depth matter in L2 reading comprehension? And how may the implication of vocabulary knowledge for reading comprehension differ between L2 Chinese readers with higher‐ and lower‐proficiency? This study provided answers. [ABSTRACT FROM AUTHOR]

The interpretability of the model is a hot issue in the field of computer vision. Score‐CAM is a kind of interpretable CAM method with good discrimination and gradient free calculation. It is a representative work in this field. However, it has the disadvantages of long calculation time and incomplete heatmap coverage. Therefore, this paper proposes an improved Score‐CAM method named FIMF Score‐CAM, which can fast integrate multiple features. Its contribution is reflected in two aspects: The weight of the feature map is directly calculated by using the feature template. Unlike Score‐CAM, this model greatly saves computation time because it only requires one convolutional calculation. Another contribution is that the feature map used to generate the heatmap integrates various semantic features of the local space, so that the heatmap of the object of interest can be generated with more complete coverage and better interpretation. The FIMF Score‐CAM is superior to the existing mainstream models in interpreting the visual performance and fairness indicators of the decision‐making, having more complete explanations of object classes and the advantage of faster calculation speed. [ABSTRACT FROM AUTHOR]

This study compared how distinct lexical competences, including lexical knowledge as well as processing skills at both word/lexical and sublexical/morphological levels, collectively and relatively predict reading comprehension in adult learners of English as a foreign language (EFL). The participants were 220 Arabic‐speaking EFL learners in a Saudi university. A battery of paper‐ and computer‐based tests was administered to measure the participants' lexical competences, reading comprehension ability, and working memory. Hierarchical regression analyses revealed that over and above working memory, both lexical and sublexical knowledge were significant and unique predictors of reading comprehension, and sublexical processing efficiency, as opposed to lexical processing efficiency, predicted reading comprehension significantly. In addition, among the measured lexical competences, lexical knowledge was the strongest predictor, and the two knowledge variables collectively had a far greater influence on reading comprehension than did the two processing efficiency variables. These findings are discussed in light of the lexical basis of text comprehension. [ABSTRACT FROM AUTHOR]

Drought largely affects terrestrial gross primary productivity (GPP) by its duration (i.e., drought time‐scales). However, the large‐scale impact of drought time‐scales on GPP is still not well understood, partly due to limited understanding of ecological processes and difficulties in quantifying drought time‐scales. Here, we examined the responses of GPP to drought in China during the last four decades, using state‐of‐the‐art GPP data estimates and a multiscalar drought metric. Most of the GPP data suggested that the time‐scales at which drought has the largest influence on annual GPP (dominant drought time‐scales) were well related to climate region and vegetation type. The GPP responded to drought more rapidly in arid regions than that in semiarid and subhumid regions, with a mean dominant drought time‐scale of 15 and 20 months, respectively; as plants in arid regions can rapidly adapt to water shortage through physiological strategies, while, in semiarid and subhumid regions plants usually can withstand a degree of water deficits. In a humid region, GPP did not rapidly respond to drought, probably because the high soil water availability buffered the effect of drought. In addition, most of the GPP estimates suggested that grasslands and croplands tended to respond to drought at shorter time‐scales than that of forests, shrublands, and sparse vegetation. The study highlights the importance of improving the effects of water availability on vegetation activity and further consideration of vegetation adaptability to drought in both remote sensing GPP algorithms and parameterizations of current terrestrial ecosystem models. Plain Language Summary: Gross primary productivity (GPP) is the entire photosynthetic production of organic compounds in an ecosystem. It plays an important role in carbon cycles, and is the basis for food, fiber, and wood production. Drought widespreadly and negatively affects GPP by its duration (i.e., drought time‐scales). Thus, it is critical to understand the dominant time‐scale at which drought has the largest influence on GPP. We investigated dominant time‐scales of GPP response to drought in China using six GPP estimates and a multiscalar drought metric. We found that the dominant time‐scales were well related to climate region and vegetation type. The GPP responded to drought more quickly in arid regions than that in semiarid and subhumid regions. This might be due to plants in arid regions can rapidly adapt them to water shortage, while, in semiarid and subhumid regions, plants can withstand a degree of water deficits. In a humid region, GPP did not rapidly respond to drought, probably because the high soil water availability buffered the effect of drought. The grasslands and croplands responded to drought at shorter time‐scales than forests, shrublands, and sparse vegetation. The study could benefit the management and mitigation of drought effects on GPP. Key Points: The magnitudes of gross primary productivity (GPP) response to drought highly vary among different GPP estimates and across time‐scalesGPP responds to drought at shorter time‐scales in arid regions than that in other climate regionsGPP of forests responds to drought at longer time‐scales than that of shrublands, grasslands, and croplands [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]

The authors examined the complexity of the simple view of reading, focusing on morphological decoding fluency in fourth‐grade readers of English in Singapore. The participants were three groups of students who all learned to become bilingual and biliterate in the English language (EL) and their respective ethnic language in school but differed in the home language they used. The first group was ethnic Chinese students who used English as the dominant home language (Chinese EL1); the other two groups were ethnic Chinese and Malay students whose dominant home language was not English but Chinese (Chinese EL2) and Malay (Malay EL2), respectively. The measures included pseudoword decoding (phonemic decoding), timed decoding of derivational words (morphological decoding fluency), oral vocabulary, and passage comprehension. Path analysis showed that oral vocabulary significantly predicted reading comprehension across all three groups, yet a significant effect of morphological decoding fluency surfaced in the Chinese EL1 and Malay EL2 groups but not the Chinese EL2 group. Multigroup path analysis and commonality analysis further confirmed that morphological decoding played a larger role in the Chinese EL1 and Malay EL2 groups. These findings are discussed in light of the joint influence of target‐language experience and cross‐linguistic influence on second‐language or bilingual reading development. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays a key role in linking water, energy, and carbon cycles. However, at regional scales, variations and controls of ET are still not well understood, due to the substantial uncertainties in ET estimates. Here, the variations in ET over China during the last three decades and their drivers and controls were analysed at monthly, seasonal, and annual scales, using well‐evaluated land surface model simulations. The results suggested that (a) the spatially averaged ET over China increased during 1979–2012 at each temporal scale. Overall, the ET significantly increased (p <.05) in most of western China and decreased in several regions in eastern China during most months and seasons. (a) The increases in spatially averaged ET during the nongrowing season were mainly determined by warming. The increased annual ET, seasonal ET, and monthly ET within the growing season were jointly caused by vegetation greening and climate warming. (c) During November–March, ET was primarily determined by temperature in most of central China and was determined by water availability in the remaining regions. The annual ET and the monthly ET within April–October were mainly controlled by water availability in most of northern and western China, and several regions in central China, by solar radiation in most of central and southern China and by temperature in some regions in the Tibetan Plateau. The study highlights the large effects of warming and greening on ET over China during the last three decades. The results may benefit water resource management under climate change. [ABSTRACT FROM AUTHOR]

In this study, an image representation method based on multi‐scale microstructural binary pattern extraction is proposed, which uses zero‐mean microstructural pattern binarisation. This method can express all kinds of important pattern structures that may appear in the image. By using the dominant binary pattern learning model, the dominant feature pattern sets adapted to different datasets can be obtained, which have good performance in the aspects of feature robustness, recognition, and representation ability. This method can greatly reduce the dimension of feature coding and improve the speed of the algorithm. The experimental results show that this method has strong recognition ability and robustness, is superior to the traditional local binary pattern and grey image micorstructure maximum response pattern methods, and has a competitive performance compared with the results of many latest algorithms. [ABSTRACT FROM AUTHOR]

A novel single image rain removal model is proposed. Based on the gradient magnitude and direction of rain streaks, the pure rain region can be extracted from the high‐frequency component of rainy image. To ensure proper rain removal, a pure rain dictionary is learned from the extracted pure rain region, and the learned rain dictionary is used to reconstruct the rainy mask from the decomposed high‐frequency component. To adaptively remove rain pixels and preserve more details of non‐rain pixels, a rainy mask is incorporated into the model. In the proposed model, an improved bilateral filter is only used to handle rain pixels. The experimental results show that the proposed model is superior to existing models in resolving the problems of over‐smoothing and rain‐streak remains in synthetic and real‐world rainy images. Consequently, a better quantitative index and visual quality can be achieved. [ABSTRACT FROM AUTHOR]

Background: While much is known about how morphological awareness (MA) contributes to reading development, little attention has been paid to how reading may conversely affect MA development, particularly in readers of Chinese in a bilingual/multilingual setting. Methods: The study adopted a cross‐lagged panel design. Young bilingual readers of Chinese were measured in MA, word reading and reading comprehension – all in Chinese – twice from Grade 3 to Grade 4. Results: Path analysis revealed that Grade 3 MA significantly predicted Grade 4 reading comprehension after controlling for the autoregressive effect. Over and above Grade 3 MA, Grade 3 reading also significantly predicted Grade 4 MA. Subsequent analyses, however, revealed disparate developmental patterns between those with Chinese and English, respectively, as their home language. Implications: These findings, while supporting reciprocity of developmental relationships between MA and reading, also suggested that the pattern of relationships can vary as a function of students' target language experiences in a bilingual/multilingual setting. Highlights: What is already known about this topic Morphological awareness predicts reading development in monolingual children, including Chinese‐speaking children. What this paper adds Morphological awareness predicts Chinese reading development in bilingual children with English as their primary reading language.There are developmentally reciprocal relationships between morphological awareness and reading abilities in those readers.The relationships vary in students with differential Chinese language experiences. Implications for theory, policy or practice Morphological awareness supports reading development but is also facilitated by reading experiences.Target language experiences moderate patterns of reading development.Morphological instruction may be particularly important for readers who do not speak the target language at home in a bilingual/multilingual setting. [ABSTRACT FROM AUTHOR]

This study examined the similarities and differences in the functioning of component processes underlying first language (L1) and second language (L2) word reading in Chinese. Fourth-grade Chinese children in Singapore were divided into L1 and L2 reader groups based on whether they used Mandarin or English as their home language. Both groups were administered a battery of tasks that assessed their orthographic processing skill (OP), phonological awareness (PA), morphological awareness (MA), oral vocabulary knowledge, as well as the ability to decode characters and multi-character compound words. Separate Structural Equation Modeling (SEM) analyses showed that in the L1 group, over and above all other variables, both OP and MA, as opposed to PA, were significant predictors of word reading, whereas in the L2 group, OP and PA, as opposed to MA, predicted word reading. Multiple-group SEM analysis further revealed that the effects of OP and MA were significantly larger in the L1 than in the L2 group, whereas a converse pattern was found for PA. These findings are discussed in light of the linguistic and language-to-print mapping properties of Chinese as well as the influence of L1 and L2 learners' differential experience on how they learn to read in Chinese. [ABSTRACT FROM AUTHOR]

According to the characteristics of maize disease spot performance in the image, this paper designs two-histogram segmentation method based on evolutionary algorithm, which combined with the analysis of image of maize diseases and insect pests, with full consideration of color and texture characteristic of the lesion of pests and diseases, the chroma and gray image, composed of two tuples to build a two-dimensional histogram, solves the problem of one-dimensional histograms that cannot be clearly divided into target and background bimodal distribution and improved the traditional two-dimensional histogram application in pest damage lesion extraction. The chromosome coding suitable for the characteristics of lesion image is designed based on second segmentation of the genetic algorithm Otsu. Determining initial population with analysis results of lesion image, parallel selection, optimal preservation strategy, and adaptive mutation operator are used to improve the search efficiency. Finally, by setting the fluctuation threshold, we continue to search for the best threshold in the range of fluctuations for implementation of global search and local search. [ABSTRACT FROM AUTHOR]

Background In spite of considerable advancements in our understanding of the different factors involved in achieving vocabulary-learning success, the overall pattern and interrelationships of critical factors involved in L2 vocabulary learning - particularly, the mechanisms through which learners regulate their motivation and learning strategies - remain unclear. Aims This study examined L2 vocabulary learning, focusing on the joint influence of different motivational factors and learning strategies on the vocabulary breadth of adolescent learners of English as a foreign language (EFL) in China. Sample The participants were 107 tenth graders (68 females, 39 males) in China. Methods The data were collected via two questionnaires, one assessing students' motivation towards English-vocabulary learning and the other their English vocabulary-learning strategies, along with a test measuring vocabulary breadth. Results Structural equation modelling (SEM) indicated that learning strategy partially mediated the relationship between motivation (i.e., a composite score of intrinsic and extrinsic motivation) and vocabulary learning. Separate SEM analyses for intrinsic (IM) and extrinsic motivation (EM) revealed that there were significant and positive direct and indirect effects of IM on vocabulary knowledge; and while EM's direct effect over and above that of learning strategies did not achieve significance, its indirect effect was significant and positive. Conclusions The findings suggest that vocabulary-learning strategies mediate the relationship between motivation and vocabulary knowledge. In addition, IM may have a greater influence on vocabulary learning in foreign-language contexts. [ABSTRACT FROM AUTHOR]

Using a Chinese Word Associates Test (WAT-C), this study examined the vocabulary depth of second language learners of Chinese and its contribution to the learners' reading comprehension. Results showed no significant effects of word frequency, word class (i.e., adjectives vs. verbs), and type of association relationships (i.e., paradigmatic vs. syntagmatic) on learners' WAT-C performance. More important, vocabulary depth was found to be a significant and unique predictor of reading comprehension over and above vocabulary size. On the other hand, the relative contributions of vocabulary depth and size depended on what types of texts were read and what comprehension skills were assessed. Specifically, for the long passage comprehension task with questions testing literal comprehension, vocabulary size was a more important predictor, whereas for the short passage comprehension task with questions testing inferencing, vocabulary depth was a more important predictor. These findings were discussed in light of the different levels of lexical complexity between the short and long passages and the different cognitive processing demands the questions of the two comprehension tasks placed on learners. [ABSTRACT FROM AUTHOR]

Using structural equation modeling analysis, this study examined the contribution of vocabulary and grammatical knowledge to second language reading comprehension among 190 advanced Chinese English as a foreign language learners. Vocabulary knowledge was measured in both breadth (Vocabulary Levels Test) and depth (Word Associates Test); grammatical measures focused on learners' implicit (timed grammaticality judgment task), as well as explicit knowledge (grammatical error correction task); reading comprehension had three indicators, namely, co-reference, textual inference, and gist. Vocabulary knowledge related significantly to reading comprehension; grammatical knowledge showed a weak contribution to reading comprehension after controlling for the effect of vocabulary knowledge. In addition, learners' implicit knowledge of grammar had a stronger relationship to reading comprehension than explicit knowledge, over and above the effect of vocabulary size. [ABSTRACT FROM AUTHOR]