Subjects: Geosciences >> Geography submitted time 2023-12-16 Cooperative journals: 《干旱区研究》
Abstract： To reveal the survival strategy of plants in semi- arid coal mining subsidence areas faced with soil erosion stress, 2-3-year-old Artemisia ordosica plants were used as the test materials and in- situ root structure destruction tests were carried out at four levels: severe stress (P1), moderate stress (P2), mild stress (P3), and control (CK). The changes in growth indices, photosynthetic characteristics, and physiological traits of A. ordosica were measured. The results showed that soil erosion stress significantly inhibited the growth rate of A. ordosica, and that the greater the degree of simulated damage, the more significant the growth inhibition. After severe stress, the growth rates of plant height, crown width, branch length, and branch diameter of A. ordosica decreased by an average of 36.91%, 43.90%, 69.76%, and 66.76 %, respectively, compared to control plants. Soil erosion stress also conferred a significant negative effect on the photosynthesis of A. ordosica, and the greater the degree of damage, the stronger the negative effect. After severe stress, the net photosynthetic rate, stomatal conductance, intercellular carbon dioxide concentration, transpiration rate, and chlorophyll content of A. ordosica decreased by 39.86%, 59.26%, 7.82%, 51.55%, and 12.33%, respectively, compared to control plants. After 70 days of erosion stress, the activities of superoside dismutase (SOD), peroxidase (POD), and oxidoreductase (CAT) in A. ordosica initially increased and later decreased, and tended to be stable when compared with the control. The malondialdehyde (MDA) content fluctuated within a certain range. Redundancy analysis showed that the level of SOD activity had the most significant effect on the photosynthetic characteristics of A. ordosica. Comprehensive analysis showed that the root fracture of A. ordosica caused by soil erosion in coal mining subsidence areas will reduce its growth rate and inhibit photosynthesis. However, A. ordosica can maintain its growth by regulating the activity of its antioxidase systems and can therefore be considered to be an ecological restoration plant species due to its excellent resistance and adaptability in erosive areas
Subjects: Digital Publishing >> New Media submitted time 2023-10-08 Cooperative journals: 《中国传媒科技》
Abstract：本文通过文献资料法、个案分析法对融媒体背景下主持人多元能力的塑造进行研究,了解主持人在新的传播环境下遇到的机遇和挑战,并提出了相关的建议。
Subjects: Materials Science >> Materials Science (General) submitted time 2023-03-31 Cooperative journals: 《腐蚀科学与防护技术》
Abstract： none
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： As a fundamental technique in natural language processing (NLP), word embedding quantifies a word as a low-dimensional, dense, and continuous numeric vector (i.e., word vector). This process is based on machine learning algorithms such as neural networks, through which semantic features of a word can be extracted automatically. There are two types of word embeddings: static and dynamic. Static word embeddings aggregate all contextual information of a word in an entire corpus into a fixed vectorized representation. The static word embeddings can be obtained by predicting the surrounding words given a word or vice versa (Word 2Vec and FastText) or by predicting the probability of co-occurrence of multiple words (GloVe) in large-scale text corpora. Dynamic or contextualized word embeddings, in contrast, derive a word vector based on a specific context, which can be generated through pre-trained language models such as ELMo, GPT, and BERT. Theoretically, the dimensions of a word vector reflect the pattern of how the word can be predicted in contexts; however, they also connote substantial semantic information of the word. Therefore, word embeddings can be used to analyze semantic meanings of text. In recent years, word embeddings have been increasingly applied to study human psychology. In doing this, word embeddings have been used in various ways, including the raw vectors of word embeddings, vector sums or differences, absolute or relative semantic similarity and distance. So far, the Word Embedding Association Test (WEAT) has received the most attention. Based on word embeddings, psychologists have explored a wide range of topics, including human semantic processing, cognitive judgment, divergent thinking, social biases and stereotypes, and sociocultural changes at the societal or population level. Particularly, the WEAT has been widely used to investigate attitudes, stereotypes, social biases, the relationship between culture and psychology, as well as their origin, development, and cross-temporal changes. As a novel methodology, word embeddings offer several unique advantages over traditional approaches in psychology, including lower research costs, higher sample representativeness, stronger objectivity of analysis, and more replicable results. Nonetheless, word embeddings also have limitations, such as their inability to capture deeper psychological processes, limited generalizability of conclusions, and dubious reliability and validity. Future research using word embeddings should address these limitations by (1) distinguishing between implicit and explicit components of social cognition, (2) training fine-grained word vectors in terms of time and region to facilitate cross-temporal and cross-cultural research, and (3) applying contextualized word embeddings and large pre-trained language models such as GPT and BERT. To enhance the application of word embeddings in psychological research, we have developed the R package “PsychWordVec”, an integrated word embedding toolkit for researchers to study human psychology in natural language.
submitted time 2023-03-25 Cooperative journals: 《心理科学进展》
Abstract： As a fundamental technique in natural language processing (NLP), word embedding quantifies a word as a low-dimensional, dense, and continuous numeric vector (i.e., word vector). This process is based on machine learning algorithms such as neural networks, through which semantic features of a word can be extracted automatically. There are two types of word embeddings: static and dynamic. Static word embeddings aggregate all contextual information of a word in an entire corpus into a fixed vectorized representation. The static word embeddings can be obtained by predicting the surrounding words given a word or vice versa (Word 2Vec and FastText) or by predicting the probability of co-occurrence of multiple words (GloVe) in large-scale text corpora. Dynamic or contextualized word embeddings, in contrast, derive a word vector based on a specific context, which can be generated through pre-trained language models such as ELMo, GPT, and BERT. Theoretically, the dimensions of a word vector reflect the pattern of how the word can be predicted in contexts; however, they also connote substantial semantic information of the word. Therefore, word embeddings can be used to analyze semantic meanings of text. In recent years, word embeddings have been increasingly applied to study human psychology. In doing this, word embeddings have been used in various ways, including the raw vectors of word embeddings, vector sums or differences, absolute or relative semantic similarity and distance. So far, the Word Embedding Association Test (WEAT) has received the most attention. Based on word embeddings, psychologists have explored a wide range of topics, including human semantic processing, cognitive judgment, divergent thinking, social biases and stereotypes, and sociocultural changes at the societal or population level. Particularly, the WEAT has been widely used to investigate attitudes, stereotypes, social biases, the relationship between culture and psychology, as well as their origin, development, and cross-temporal changes. As a novel methodology, word embeddings offer several unique advantages over traditional approaches in psychology, including lower research costs, higher sample representativeness, stronger objectivity of analysis, and more replicable results. Nonetheless, word embeddings also have limitations, such as their inability to capture deeper psychological processes, limited generalizability of conclusions, and dubious reliability and validity. Future research using word embeddings should address these limitations by (1) distinguishing between implicit and explicit components of social cognition, (2) training fine-grained word vectors in terms of time and region to facilitate cross-temporal and cross-cultural research, and (3) applying contextualized word embeddings and large pre-trained language models such as GPT and BERT. To enhance the application of word embeddings in psychological research, we have developed the R package “PsychWordVec”, an integrated word embedding toolkit for researchers to study human psychology in natural language.
Subjects: Mechanics >> Applied Mechanics submitted time 2023-03-20 Cooperative journals: 《应用力学学报》
Abstract： Surface instability of hard films adhered on soft substrate has always been a difficult problem forflexible electronic devices. Considering the shear stress between the bi-layer film and the elastic gradedsubstrate , an analytical model of bi-layer film/ elastic graded substrate is established.By using the dis-placement continuity of the interface , the analytical expressions of the critical strain and wavelength of thebi-layer film/elastic graded substrate are obtained. Then , through several examples , the validities of theproposed expressions are verified which are compared with those results obtained by the finite element analysis.At the same time, the influences of the geometric parameters of the bi-layer film and physical pa-rameters of the elastic graded substrate on the buckling behavior are analyzed. 'The results in this papershow that decreasing the thickness of device layer or increasing the thickness of encapsulation layer canimprove the stability of bilayer film/elastic graded substrate structure; if the substrate is relatively“soft”orthe device layer is “hard”,the shear force of the interface between the device layer and the substrate willbe taken into account , which can prevent the resistance of the three-layer film/ substrate structure from un-dergoing interface failure.Above all, the research will provide theoretical support for the fabrication of flex-ible electronic devices with hard film/elastic graded substrate structure.
Subjects: Psychology >> Social Psychology Subjects: Psychology >> Cognitive Psychology Subjects: Psychology >> Psychological Measurement Subjects: Computer Science >> Natural Language Understanding and Machine Translation submitted time 2023-01-30
Abstract： As a basic technique in natural language processing (NLP), word embedding represents a word with a low-dimensional, dense, and continuous numeric vector (i.e., word vector). Word embeddings can be obtained by using neural network algorithms to predict words from the surrounding words or vice versa (Word2Vec and FastText) or words’ probability of co-occurrence (GloVe) in large-scale text corpora. In this case, the values of dimensions of a word vector denote the pattern of how a word can be predicted in a context, substantially connoting its semantic information. Therefore, word embeddings can be utilized for semantic analyses of text. In recent years, word embeddings have been rapidly employed to study human psychology, including human semantic processing, cognitive judgment, individual divergent thinking (creativity), group-level social cognition, sociocultural changes, and so forth. We have developed the R package “PsychWordVec” to help researchers utilize and analyze word embeddings in a tidy approach. Future research using word embeddings should (1) distinguish between implicit and explicit components of social cognition, (2) train fine-grained word vectors in terms of time and region to facilitate cross-temporal and cross-cultural research, and (3) deepen and expand the application of contextualized word embeddings and large pre-trained language models such as GPT and BERT.
Subjects: Geosciences >> Geography submitted time 2021-02-13 Cooperative journals: 《干旱区地理》
Abstract： 区域建设用地开发强度是揭示土地利用效率、社会经济发展水平与国土空间开发状态的 重要指标，对其变化进行监测与管治是优化国土空间开发格局，实现区域可持续发展的重要手 段。构建建设用地开发强度量化模型，以陕西省为例，计算 2000—2015 年县域建设用地开发强度 指数，利用空间自相关分析方法揭示其空间格局和演化特征，并采用最小二乘法（OLS）和地理加权 回归（GWR）模型识别建设用地开发强度格局演化的影响因素。结果表明：（1）2000—2015 年陕西 省建设用地开发强度总体呈现增长态势，内部空间分异显著，高强度区集中在榆林、延安、西安、安 康等地，低强度区集中在咸阳、宝鸡、铜川、商洛、渭南、汉中等地。（2）陕西省建设用地开发强度呈 现出明显的空间集聚状态，热点区稳定分布在西安市辖区及周边区县，冷点区分布在延安南部、咸 阳、铜川、渭南和汉中等部分区域；县域建设用地开发强度逐步提升的同时，区域开发不平衡现象 日益突显。（3）固定资产投资、居民消费水平、财政投入力度、耕地资源和地形条件是影响陕西省建 设用地开发强度空间分异的主要因素，但在不同县域其影响程度大小具有显著差异，且个别因素 的影响具有不稳定性。
Subjects: Geosciences >> Geography submitted time 2020-12-17 Cooperative journals: 《干旱区研究》
Abstract：为研究不同辐射强度对里海盐爪爪不同组织中内生微生物群落的影响，利用Biolog-Eco微平板法结合土壤的理化性质，对新疆不同辐射强度污染区的里海盐爪爪地上部分和根部内生微生物群落代谢活性、碳源利用类型、多样性、主成分和环境因子间的差异进行了分析。结果表明：（1）各处理间代谢活性随培养时间的延长而提高，植物不同组织内生菌群落代谢活性存在明显差异。（2）地上部分样品中的主要菌群为利用碳水化合物类、氨基酸类的微生物；根部样品中的主要菌群为利用碳水化合物类、氨基酸类、羧酸类和多聚物类的微生物。（3）不同辐射强度污染区植物样品及植物不同部位的内生菌群落结构也存在显著差异。尤其在根部样品中，中度辐射污染区的代谢活性和多样性指数显著低于其他污染区。（4）土壤全氮、有机质、速效钾和氯根与微生物群落多样性显著相关，但辐射强度与里海盐爪爪内生菌群落多样性之间没有显著的相关性。本研究揭示了不同辐射强度对植物内生微生物生长代谢、碳源利用及群落多样性的影响，为辐射污染区微生物资源的开发和利用提供了科学依据。
Subjects: Biology >> Zoology submitted time 2018-12-25 Cooperative journals: 《动物营养学报》
Abstract：本试验旨在研究在妊娠后期及哺乳期母猪饲粮中添加不同量的膨化苜蓿草粉–亚麻籽对其繁殖性能及初乳脂肪酸组成的影响。试验选用80头妊娠后期（妊娠83 d）长×大二元初产母猪，随机分为4个组，每组4个重复，每个重复5头。对照组饲喂基础饲粮，试验组在基础饲粮中分别添加5%、10%和15%膨化苜蓿草粉–亚麻籽。试验预试期7 d，正试期55 d。结果表明：1）与对照组相比，饲粮中添加膨化苜蓿草粉–亚麻籽可显著提高母猪平均日采食量（P0.05）；3）仔猪断奶（21日龄）时，15%膨化苜蓿草粉–亚麻籽添加组的均匀度最好。由此可见，膨化苜蓿草粉–亚麻籽可以提高母猪繁殖性能及初乳中MUFA含量与UFA/SFA值。
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2018-11-08 Cooperative journals: 《干旱区研究》
Abstract：为明确干旱矿区侵蚀发生后折力损伤对植物根系力学特性的影响及其受损后的自修复机制，利用HG100数显式推拉力计和自制便携式试验机台，对小叶锦鸡儿1~4 mm径级直根和侧根分支处未受损及受损自修复后的抗折力学特性进行研究。结果表明： 生长季初期，未受损小叶锦鸡儿根系极限抗折力与根径呈幂函数正相关，抗折强度与根径幂函数负相关，直根极限抗折力和抗折强度均大于侧根分支处； 折力损伤会明显抑制根系正常生长，小叶锦鸡儿根系受损自修复后，活性、生长量和保存率均低于平行对照，根径和根型均是影响这种抑制作用的重要因素，侧根分支处活性和保存率在受损后的减少程度显著大于直根； 小叶锦鸡儿根系受损自修复后，极限抗折力与抗折强度相比，生长季初期有所增加，但外力损伤会显著阻碍这种增长，导致其增长率显著低于平行对照，3个月后极限抗折力修复率为48.91%，抗折强度修复率为57.59%，说明根系受损后不会彻底丧失固土能力，通过自修复可以逐步恢复原有功能，但短期内自修复程度有限。直根极限抗折力修复率为60.55%，侧根分支处仅为36.34%，说明在同等外力荷载条件下，小叶锦鸡儿直根受损自修复能力显著大于侧根分支处，具备更强的再次抵御外力破坏的能力。
Subjects: Astronomy >> Astrophysical processes submitted time 2017-09-26 Cooperative journals: 《天文研究与技术》
Abstract：为了进一步研究光学天文时纬残差异常在地震预测中的作用，介绍了光学天文时纬残差震前异常的发现和在地震预测中的研究实践，以及云南天文台光电等高仪的时纬残差异常变化与其周邻强震的对应关系，最后以讨论的形式给出了这种关联的可能的地球物理机制，目前在地震预测中的局限性和可能的解决途径。重要的是，X10年以来的预测实践进一步表明，利用光学天文时纬残差的同步异常提供地震预测信息，既没有虚报，也没有漏报。这就说明它是完全可以作为地震预测的一种手段，投入地震预测实践中，值得更多重视和更加深入的研究。
Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2017-06-07 Cooperative journals: 《工程热物理学报》
Abstract：为了探究不同转速对某亚音轴流压气机叶尖泄漏流非定常性的影响，采用动态压力测量技术获得不同转速机匣壁处压力信号。试验测量表明，在近失速工况压力信号的频谱出现表征旋转不稳定性的特征频率驼峰。其驼峰峰值处频率随转速的提高相对减小。在此基础，分别进行不同转速的多通道数值模拟。数值模拟中，叶尖区的静压监测信号频谱与试验具有一致性，转子叶尖存在逆转子传播的周向行波。该周向行波对应了试验中的旋转不稳定现象。进一步的数值模拟流场分析表明，该周向行波在53%设计转速时是源于叶顶泄漏流自我维持的非定常性。在71%设计转速时，在某些时刻泄漏涡发生破碎并参与到周向行波的形成过程。
Subjects: Materials Science >> Materials Science (General) submitted time 2017-03-31 Cooperative journals: 《金属学报》
Abstract：通过对3种不同W(6%-8%, 质量分数, 下同)含量的第三代镍基单晶高温合金铸态, 热处理态和热暴露后的组织观察和成分分析, 研究了W对元素偏析, 热处理组织及热暴露过程中组织演化的影响. 结果表明: W含量的提高对合金元素的铸态偏析, 完全热处理后的γ′相形貌, 尺寸和体积分数无明显影响. 在950 ℃热暴露过程中, W含量的提高抑制了γ′相的粗化, 但加速了γ′相的连接变形. 3种合金在热暴露过程中析出的TCP相主要为μ相和σ相, 且TCP相析出量随W含量的增加缓慢增大. 此外, 3种合金在1000 ℃热暴露时TCP相析出量最大, 在950 ℃热暴露时次之, 在1050 ℃热暴露时析出量最小.
Subjects: Geosciences >> Space Physics submitted time 2017-01-22
Abstract： Wind and temperature data detected by the first meteorological rocket of the Meridian Space Weather Monitoring Project was used tostudy quasi-monochromatic inertia gravity waves over Hainan rocket launch site(19.5°N,109°E).The GW extracted from the stratosphere (troposphere)revealed by rocketsonde is upward(downward) GW,both propagate against the background wind.The intrinsic period, vertical wavelength ，horizontal wavelength ，vertical group velocity ,and horizontal group velocity of Stratospheric(Tropospheric)GWare 20.1 h(22.4 h),9.5 km(4 km), 2900 km(753 km) ,0.0887（0.0298）m/s,and12.7（3.65）m/srespectively. There is a significant difference between and because of the background wind. The ratio and is 305:1(188:1) and 143:1(122:1) for the stratospheric(tropospheric) GW, the former is about 1.62(1.17) times of the latter.
Peer Review Status:
Awaiting Review
Subjects: Materials Science >> Materials Science (General) submitted time 2016-11-08 Cooperative journals: 《腐蚀科学与防护技术》
Abstract：综述了杂环化合物类酸洗缓蚀剂的研究进展。对目前研究报道较多的五元、六元及苯并杂环化合物的分子结构特点、缓蚀作用原理及缓蚀性能做了详细分析，并对该领域的研究发展方向进行展望。
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