Use of heuristic knowledge in Chinese language analysis

The syntactic structure of a sentence can be described as a tree that indicates the syntactic relationships between words. In spite of significant progress in unsupervised methods that retrieve the syntactic structure of sentences, guessing the right direction of edges is still a challenge. As in a syntactic dependency structure edges are oriented away from the root, the challenge of guessing the right direction can be reduced to finding an undirected tree and the root. The limited performance of current unsupervised methods demonstrates the lack of a proper understanding of what a root vertex is from first principles. We consider an ensemble of centrality scores, some that only take into account the free tree (non-spatial scores) and others that take into account the position of vertices (spatial scores). We test the hypothesis that the root vertex is an important or central vertex of the syntactic dependency structure. We confirm the hypothesis in the sense that root vertices tend to have high centrality and that vertices of high centrality tend to be roots. The best performance in guessing the root is achieved by novel scores that only take into account the position of a vertex and that of its neighbours. We provide theoretical and empirical foundations towards a universal notion of rootness from a network science perspective.

In order to support the processes of reading digital research articles, we propose a summarisation method focused on using the localised topic information of documents. The objective is to produce summaries containing topics which are detailed in a document rather than those representing a general overview. We obtain the summaries by ranking sentences based on key-terms cooccurring throughout the document structure, and key-terms within the syntactic structure of sentences. Our idea of using the concept of syntactic structures is that authors usually have their own writing styles, represented by grammatical structures. In this paper we present a description of the method along with an evaluation, comparing our method to other existing summarisation methods.

Natural Language Processing is the multidisciplinary area of Artificial Intelligence, Machine Learning and Computational Linguistic for processing human language automatically. It involves understanding and processing of human language. The way through which we share our contents or feelings have always great importance in understanding and processing of language. Parsing is the most suited approach in identifying and scanning what the available sentences expressed? Parsing is the process in which syntactic structure of sentence is identified using grammatical tags. The syntactically correct sentence structure is achieved by assigning grammatical labels to its constituents using lexicon and syntactic rules. Phrase and Dependency are two main structure formalisms for parsing natural language sentences. The growing use of web 2.0 has produced novel research challenges as people from different geographical areas are using this channel and sharing contents in their native languages. Urdu is one of such free word order native language which is widely shared over social media sites but identification and summarization of Urdu sentences is challenging task. In this review paper we present an overview to recent work in parsing of fixed order (i.e. English) and free word order languages (i.e Urdu) in order to reveal the most suited method for Urdu Language Parsing. This survey explored that dependency parsing is more appropriate for Urdu and other free word order languages and parsers of English language are not useful in parsing Urdu sentence due to its morphological, syntactical and grammatical differences.

The paper deals with methodological issues of teaching senior students of language universities to analyze the syntactic structure of sentences in modern Chinese at the phrase level. The technology of teaching Russian students to analyze the syntactic structure of sentences in modern Chinese is presented in the following stages: 1) theoretical explanation of the classification of phrases in modern Chinese and methods of mastering this phenomenon by students; 2) introduction to five different ways of syntactic analysis of sentences at the phrase level; 3) presentation of features of the analysis "from small to large"; 4) improvement of skills of independent analysis of offers by students using the specified method. Much attention is paid to the order of establishment of relations between lexical items in phrases, combined with each other semantically. At the same time, in the developed technology, it is recommended to analyze the group of subject and predicate separately, performing an analysis from right to left. When faced with more difficult cases - long complicated sentences, the authors recommend analyzing the sentence in both directions, both from left to right and from right to left. Russian translation is recommended when determining the type of a phrase in Chinese. It is recommended that you translate the phrase into Russian, set its type in Russian, and then make a conclusion about the type of this phrase based on the typology used in Chinese. The existing limitations of using this method are discussed. As the main method of analyzing the syntactic structure of Chinese sentences, the analysis "from small to large" is chosen as the most convenient in implementation and allows parsing long complicated sentences.

The paper offers a new way of presenting the structure of a sentence. None of the two widely known methods of representation the syntactic structure of a sentence can be of any avail when applied to the Lithuanian language. Neither the tree, based on the phrase structure principle, nor the tree, suggested by the dependency grammar, do reflect all the syntactic information, which a Lithuanian sentence contains. The paper points out the differences between the Lithuanian language and other languages as well as presents the reasons why a Lithuanian sentence should be represented by a graph. The paper presents a generalized structure of a simple sentence in the Lithuanian language, namely, such a structure, which would embrace all the possible instances of a Lithuanian simple sentence. Every sentence of the text would have to activate only one path in the generalized structure.

The cortical dynamics in building syntactic structures of sentences: An MEG study in a minimal-pair paradigm

The paper initially presents the results of a dynamic structural integrity assessment for fracture of cracked plate and tubular members under sinusoidal loading at different frequencies. The behavior of cracked members and joints in an offshore structure under wave loading (Stokes 5th order or gridded wave) is then examined. Global structural dynamic analyses of a whole offshore jacket were carried out as the first step, then, a set of sub-models of joints was selected from chosen locations and modeled with through thickness cracks under the loading extracted from the global analysis. The sub-model dynamic results were analyzed to obtain the fracture response in terms of variation of crack tip opening displacement (CTOD). Related values of K, J and their rates were also calculated. These results are used to give guidance on methods for design and assessment of structural integrity under dynamic loading.

Eleven sets of 16 sentences, previously rated as natural English statements, were presented to two groups of listeners. Each set of sentences differed in syntactic structure and contained four sentences of each of four lengths : 8, 10, 12, and 14 words. The listeners heard the sentences either under a fixed condition of filtering or without filtering; their task was to write as much of each sentence as possible immediately after it was presented. The sentences were scored for the number of words correctly reproduced, and differences in aural perception among the various sentence types and lengths were tested on the basis of the derived intelligibility scores. The results of the study indicated that (1) perception of the sentences was affected by their syntactic structure and varied, depending upon the grammatical complexity of the statements as specified by a generative-transformational grammar ; (2) the sentences of 12 words were more easily perceived than were the sentences of the other lengths ; (3) no relationship was established between the relative perception of the various sentence structures and their degree of naturalness.

Failure of civil infrastructure, such as, bridges and pipelines, can cause large public safety and economic consequences. Structural health monitoring (SHM) plays a significant role in preventing and mitigating the course of structural damage. In this work, a multi-scale SHM framework based on Hadoop Ecosystem (MS-SHM-Hadoop) to monitor and evaluate the serviceability of civil infrastructure is proposed. Through utilizing fault-tolerant distributed file system called Hadoop Distributed File System (HDFS) and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop has high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework including nationwide civil infrastructure survey, global structural integrity analysis, and structural components’ reliability analysis. The nationwide civil infrastructure survey uses deep-learning techniques to evaluate their serviceability according to real-time sensory data or archived civil infrastructure related data such as traffic status, weather conditions and civil infrastructure’s structural configuration. The global structural integrity analysis of a targeted civil infrastructure is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by deep learning technique, where the input data is derived from the measured structural load effect, hyper-spectral and 3D point cloud images, and moisture measurement about structural component. As one of its major contributions, this work employs Bayesian network to formulate the integral serviceability of a civil infrastructure according to components’ serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using statistics-oriented machine learning method (e.g., association rule learning) or structural mechanics modeling and simulation.

Introduction:This study investigates sentence comprehension in Mandarin-English bilinguals, focusing on whether the widely reported, yet contested, subject-relative processing advantage extends to bilingual speakers. We evaluate which theoretical accounts, based on syntactic structure and canonicity, best explain cross-linguistic patterns of sentence processing.Methods:Using a sentence-picture matching task, we examined the comprehension of canonical (e.g., actives) and non-canonical (e.g., passives) sentence structures in English and Mandarin for bilingual speakers of varying ages and Mandarin and English proficiency levels across two separate studies (n = 18 and n = 35).Results:In English, bilingual participants exhibited a robust canonical sentence advantage across studies, with better comprehension of subject-relative over object-relative sentences and active over passive sentences, mirroring monolingual processing patterns. However, in Mandarin, comprehension patterns were less robust and more variable. While subject-relative and object-relative comprehension did not significantly differ at the group level, passive vs. active sentences consistently posed greater difficulty and increased performance variability across both studies, particularly among lower-performing individuals.Discussion:These results suggest that sentence comprehension is shaped by language-specific constraints rather than a universal subject-relative advantage. Findings align with unified theoretical accounts that incorporate canonicity-based and structural factors, including word order, syntactic structure, and experience-, usage-, and frequency-based influences. Our results highlight the complex interplay between the aforementioned factors that differ across languages, with implications for both theoretical linguistics and clinical applications.

Any antimicrobial use (AMU) in humans and animals selects for antimicrobial resistance (AMR) and responsible AMU should therefore be promoted both in human and veterinary medicine. Insight into current AMU in companion animal clinics is necessary to be able to optimise antimicrobial (AM) prescribing behaviour. The objective of this study was to describe systemic AMU in 44 Dutch companion animal clinics over a 3-year time period (2012–2015), using retrospectively collected data. The number of Defined Daily Doses for Animals (DDDAs) per month and per clinic were calculated from prescription data for total, 1st, 2nd and 3rd choice AMU (classification according to Dutch policy on veterinary AMU). Time trends, seasonality and the influence of potential determinants (e.g., the number of dogs, cats and rabbits per clinic and other clinic characteristics) were explored using statistical modelling. Overall, the findings show that total AMU decreased over time and a shift in used classes of antimicrobials towards more 1st choice AMs was visible. Mean total AMU decreased from 1.82 DDDA/year in 2012–2013 to 1.56 DDDA/year in 2014-2015. Aminopenicillins, with and without clavulanic acid, accounted for the largest group of antimicrobials used; 38.7% (2012–2013), 40.2% (2013–2014) and 39.3% (2014–2015) of total AMU, respectively. Strong seasonal differences in AMU were found, with highest AMU in July-August and lowest in February-March. The distribution of different animal species per clinic appeared to affect AMU as well. In clinics with a larger proportion of dogs, 2nd choice AMU was significantly higher, whereas in clinics with a larger proportion of rabbits, 2nd choice AMU was significantly lower. Despite the decrease of AMU during the study period, there is still room for improvement left, especially with regard to the antimicrobial classes prescribed. According to Dutch classification of veterinary AMU, 1st choice AMs should be used as empirical therapy. A decrease in 2nd (might select for ESBL-producing bacteria) and 3rd choice AMU (i.e. fluoroquinolones and 3rd generation cephalosporins) should be aimed for.

Due to economic reasons the industry is seeking new lightweight solutions for large steel structures. However, when moving from traditional steel plate thicknesses, i.e. 5 mm or larger, to thinner ones, the fatigue design becomes challenging due to larger initial distortions caused by welding. The fatigue assessment methods used for thicker welded structures are not fully validated for thinner ones. This paper deals with the fatigue assessment of large thin-walled structures starting from the global response analysis of a whole structure to the stiffened panel and finally welded joint. A modern cruise ship is used as an example case, where traditional superstructure deck plate thickness of 5 mm is replaced by 3 mm. The influence of initial distortion at different levels of structural analysis is studied using geometrically nonlinear finite element (FE) analysis. For the lowest level of analysis, i.e. small welded joint, the experiments have been carried out including geometry measurements and fatigue tests. It is shown that for a large thin-walled structure the global response analysis can be carried out with acceptable accuracy using ideally straight plates and geometrically linear FE analysis. For intermediate level of analysis, i.e. stiffened panel, the analysis can also be geometrically linear, but the actual shape of the plates influences the structural stresses near welds significantly. When analyzing small welded specimens to define experimental fatigue strength, both the actual shape and the geometrically nonlinear FE analysis are needed in order to capture the straightening effect and to obtain the correct structural stress.

Parts and boundaries

A new fullwave global analysis of complex inhomogeneous microwave structures including passive or active, linear or nonlinear lumped elements is presented. For a given structure, only one electromagnetic simulation of the distributed part, by a three-dimensional (3-D) finite element method using edge elements, is needed corresponding to the insertion of variable lumped elements placed at the same position. Simulation results of various test cases, containing either resistor, diode, or active component, are compared with those provided by a commercial circuit analysis software or with measurements results. Our validated electromagnetic simulator is then used for analyzing a planar balanced mixer operating in the millimetric range.

How speakers sequence words and phrases remains a central question in cognitive psychology. Here we focused on understanding the representations and processes that underlie structural priming, the speaker’s tendency to repeat sentence structures encountered earlier. Verb repetition from the prime to the target led to a stronger tendency to produce locative variants of the spray-load alternation following locative primes (e.g., load the boxes into the van) than following with primes (e.g., load the van with the boxes). These structural variants had the same constituent structure, ruling out abstract syntactic structure as the source of the verb boost effect. Furthermore, using cleft constructions (e.g., What the assistant loaded into the lift was the equipment), we found that the thematic role order (thematic role-position mappings) of the prime can persist separately from its argument structure (thematic role-syntactic function mappings). Moreover, both priming effects were enhanced by verb repetition and interacted with each other when the construction of the prime was also repeated in the target. These findings are incompatible with the traditional staged model of grammatical encoding, which postulates the independence of abstract syntax from thematic role information. We propose the interactive structure-building account, according to which speakers build a sentence structure by choosing a thematic role order and argument structure interactively based on their prior co-occurrence together with other structurally relevant information such as verbs and constructions.