Syntactic Ambiguity Research Articles

Perceptual salience and structural ambiguity resolution

AbstractThis study investigates whether the perceptual salience of grammatical morphemes influences the online processing of temporarily ambiguous sentences during adult first-language (L1) comprehension. In a bidirectional self-paced reading task, adult L1 English participants (N = 44) read sentences with time adjuncts that were in a structural position in which they could attach either to the most recent verb phrase (VP) or to a VP in a higher clause. Consistent with previous findings, the reading times on these sentences indicated processing difficulty when this adjunct allowed only for high attachment. Crucially, this effect was modulated by the perceptual salience of the grammatical morphemes used to indicate time reference in these clauses. Specifically, the processing cost for high attachment was larger when time in the lower clause was indicated by the auxiliary verb will compared to when it was indicated by the relatively less salient past -ed morpheme. These findings were taken to indicate that the influence of perceptual salience extends beyond the acquisition of and sensitivity to grammatical morphemes during L1 and L2 development. Rather, the perceptual salience of these forms also appears to affect online structural processing during adult L1 sentence comprehension.

Binary Semantic Pattern Rules for Chinese-English Machine Translation Based on Machine Learning Algorithms

With the increase of internationalization and the exponential growth of intercultural communication, the importance of interlingual translation has become increasingly prominent. Machine translation has been a booming area of research as technology has advanced. Due to the complexity of language ability and limited understanding of language laws, there are challenges for machine translation. This paper focused on how to construct and apply binary semantic pattern rules through machine learning to improve the translation effect in Chinese-English machine translation. The research results of this paper would contribute to the further development and improvement of Chinese-English machine translation technology. In order to produce high-quality translation results, research in machine translation has recognized the need to analyze and understand the semantics of natural language. To address the important issue of lexical and syntactic ambiguity, representations of binary semantic pattern rules have been developed to formally describe these rules. Based on this, this paper designed and implemented a corpus-based binary semantic rule extraction and optimization algorithm, which used machine learning algorithms to automatically detect the semantic rules of two or more than two phrases in the Chinese corpus, and then automatically optimized and converted them according to the statistical results, and realized the design of Chinese-English machine translation system. The article evaluated the quality of machine translation to test the effectiveness of machine translation binary semantic pattern rules based on machine learning algorithms. The study found that compared with the rule set A, the rule sets B and C obtained automatically by the rule mining algorithm had significantly improved accuracy, both reaching more than 90%. This showed that the binary semantic pattern rule mining algorithm and optimization algorithm proposed in this paper were reasonable.

Eye-tracking evidence from attachment structures favors a serial model of discourse–sentence interactivity

ABSTRACT Many psycholinguistic studies examine how people parse sentences in isolation; however, years of work in discourse processing have shown that sentence-level interpretations are influenced at some stage by discourse-level information. Evidence over the past 20 years remains mixed as to the temporal dynamics of such top-down interactions. In particular, dynamic accounts where readers use the discourse model to generate expectations for certain grammatical structures before and during parsing differ from serial accounts where an algorithmic first-pass processing mechanism precedes integration of sentence material into the discourse model. To test between these two theories, the current study investigates eye-movement behaviors when reading temporarily ambiguous attachment structures following discourses with biases either matching, mismatching, or neutral with respect to the attachment resolution. No evidence was found suggesting readers systematically use discourse information to generate structural expectations, in line with serial accounts of processing at the sentence–discourse interface. Scanpath analyses further highlight the confirmatory nature of rereading when participants encounter discourse continuations that do not fit with prior contexts.

Spectroscopic, DFT, molecular docking and anti-cancer studies of regioselectively designed 1-aryl-indenopyrazoles

L-Proline catalyzed condensation of 1-indanones with DMF-DMA (N,N-dimethylformamide dimethyl acetal) resulted in (Z)-2-((dimethylamino)methylene-2,3-dihydro-1H-inden-1-ones 2 instead of their E-isomers 3, which is further regioselectively transformed into 1-aryl-2,4-dihydroindeno[1,2-c]pyrazole 4 rather than 2-aryl-2,4-dihydroindeno[1,2-c]pyrazoles 5 by condensing with aryl hydrazines. Spectrochemical characterizations and single crystal X-ray diffraction studies were used to resolve syntactic ambiguity between the possible geometric isomers of enaminones (E & Z) and regioisomers 1H-indenopyrazole and 2H-indenopyrazoles. The experimental findings were correlated with computed values and have shown good correlation with the proposed structures. The synthesized indenopyrazoles 4a–f were tested for their ability to inhibit the proliferation of A549 human lung cancer cell lines, and the compound 4b have showed IC50 value 13.77 µM comparable to the reference medication erlotinib (10.26 µM). The complete cell cycle analysis have revealed the accumulation of mitotic cells in G1/S phase. The flow cytometric analysis also revealed the increase in apoptotic cells indicating tumor suppression by the derivative 4b. To get insight into the interactions of the compound and EGFR tyrosine kinase protein molecular docking was performed. Also, pharmacokinetic profiling revealed about the oral compatibility of the synthesized compounds.

A framework for doctoral education in developing students’ mental well-being by integrating the demand and resources of the program: An integrative review

Background: Research on doctoral students’ mental well-being has gained importance in recent years. The findings of such studies were uncertain about the critical demand and resource of a doctoral program that largely influence students’ mental health. This review aims to integrate the literature to bring out the nature, importance and relationship between differentiated demands, contextual and personal resource, and doctoral students’ well-being. Methods: An integrative review was conducted based on the five-stage structure of Whittemore and Knafl. The study identified 45 articles published from 2000 onwards following the Joanna Briggs Institute quality evaluation criteria and PRISMA reporting guidelines for selecting eligible articles. Results: The integrative review findings disclose that the differentiated demand of doctoral program were categorized into challenge-hindrance demand. This demand experienced by doctoral students were grouped as ambiguity in doctoral program structure, resource inadequacy, workload, complexity, and responsibility. In addition, institutional support, research supervisory support, and intrinsic motivation were treated as essential resource to mitigate the effects of the demands of the doctoral program. Conclusions: An integrated conceptual model was built exclusively for doctoral programs and suggests that the universities and supervisors design and structure healthy, constructive doctoral programs. As an outcome of the review, differentiated demands, contextual, personal resources at the doctoral education and mental well-being of students are supported by the Transactional Model of Stress and Coping, Conservation of Resources, Causality Orientations Theory and Basic Psychological Need Theory respectively. The current review is an initial attempt to synthesize challenge-hindrance demands and contextual-personal resources in determining the mental well-being of doctoral students.

The Analysis of Ambiguity in Rachel Lippincott’s Novel “Five Feet Apart”

This study deals with the analysis of Ambiguity in Rachel Lippincott’s Novel “ Five Feet Apart” The objectives of this research are to find out the lexical and syntactical ambiguities found in Rachel Lippincott’s Novel “Five Feet Apart”, to find out the most dominant causal factors of ambiguities appeared in Rachel Lippincott’s Novel “Five Feet Apart”, and to describe how the lexical and syntactic ambiguities appeared in Rachel Lippincott’s Novel “Five Feet Apart”. Descriptive qualitative method was used in this study. The data of this study were taken from Rachel Lippincott’s Novel “Five Feet Apart”. There are seven types of lexical ambiguity appeared in the novel. They are Polysemy, Homonymy, Synonym, Hyponymy, Antonym, Redundancy, and Part of speech. Meanwhile there are six types of syntactical ambiguity. They are Personal pronoun, Adjective, Noun, Preposition, Verb and Adverb. Redundancy ambiguity is the most dominant lexical ambiguity and personal pronoun is the most dominant syntactical ambiguity used in this novel. There are two ways how the writer used lexical ambiguity in Rachel Lippincott’s Novel “Five Feet Apart”. First, the writer repeated the words to insist the readers that everything is the same. Second, the writer made sure the readers what the writer described. In syntactical ambiguity, the researcher found that in Rachel Lippincott’s Novel “Five Feet Apart”, the writer often missed the subject pronoun in the novel

Understanding Ambiguity in Knowledge, Value and Institutional Structure: A Case Study of Chinese Open Network Community

Being a space for organizations to realize their value, it is necessary to minimize the structural Uncertainty of the virtual world. The analysis shows structural problems are the internal logical starting point of ambiguity in the net- work community and the underlying cause of gradual accumulation and pre- cipitation in social tension. Analyzing the structural stain from the dimension of knowledge, value, and institutional structure in the network community, multifarious ambiguity is found in Chinese network governance. A representative survey object is selected to understand Chinese network governance after COVID 2019. We choose The Changtze River Cloud com- munity on TikTok as the survey unit to analyze the public space management satisfaction ratio. Through theoretical discussion and case study, specific countermeasures are proposed, such as broadening the channels of expression, constructing cultural diversity in virtual space, and establishing clear specification standardization. It is expected that explicitness instead of ambiguity transmitted by authority can promote existing order to more open, creative, and satisfying institutional design for net citizens in virtual communities.

An Aggregation‐Induced Emission Molecule‐Assembled Nanovaccine with Self‐Adjuvanted Function for Cancer Immunotherapy

AbstractCancer nanovaccine is a promising therapeutic strategy; however, the complicated composition and ambiguous structure of cancer nanovaccines hinder their clinical application. Thus, developing minimalist nanovaccine with simple structural molecule and potent immunostimulatory function is with great value. Herein, an organic small molecule with well‐defined molecular structure and strong aggregation‐induced emission (AIE) activity is synthesized. This molecule can self‐assemble into nanoparticle (NM‐7) acting as not only adjuvant but also carrier to capture model antigen ovalbumin to form nanovaccine, which can effectively deliver and chronically release antigens and induce effective antigen cross‐presentation in draining lymph nodes. Additionally, the photophysical property of AIE molecule facilitates the determination of in vivo tissue distribution of NM‐7. Notably, NM‐7/ovalbumin (OVA) nanovaccine induces robust tumor‐specific CD8+ T‐cell responses with greatly reduced cell exhaustion. Accordingly, NM‐7/OVA nanovaccine shows potent efficacy in both prevention and therapeutic tumor models, and produces an impressive synergistic therapeutic effect when combined with immune checkpoint blockade (ICB) therapy. Therefore, AIE nanomaterial NM‐7 with simple synthesis, well‐defined molecular structure and self‐adjuvanted function provides a new reference and general strategy for cancer vaccine development.

Ambiguity in Chinese College Students’ L2 Tertiary-Level Writing: A Thematic Analysis

The current study investigated ambiguity errors that characterise the L2 tertiary-level writing of Chinese college students. Data were drawn from 56 authentic English writings from 11 students of different disciplines across 10 different Chinese institutions. A thematic analysis was conducted to examine the ambiguity error patterns at the lexical and syntactic levels. Lexical ambiguities were found to include Chinglish, ambiguous references, and ambiguous abstractions, and syntactic ambiguities were found to consist of misplaced and dangling modifiers. It was also found that lexical ambiguity far exceeded syntactic ambiguity. The results demonstrate Chinese English as a foreign language (EFL) students’ limited L2 linguistic competence and struggle with accurate L2 production. This study aims to draw attention to the unpreparedness of Chinese EFL students for tertiary-level L2 writing and to the need for linguistic support in their written L2 output. Given the increasing demand for academic writing, writing with clarity is of great significance for EFL students. Whereas ambiguity resolution in L2 input has received much scholarly attention, limited empirical research has been conducted on ambiguity errors that characterise EFL students’ L2 written output. Therefore, the current study aims to fill this gap by examining the ambiguity patterns that characterise the L2 writing of Chinese college students, thus informing future teaching.

Effective assignment of positional isomers in dimeric shikonin and its analogs by 1H NMR spectroscopy

An approach for distinguishing two types of positional isomers of dimeric shikonin and its analogs was explored with 4JC,H long-range correlation by prolonging the acquisition time at 2,3JC,H values of 2.0 and 8.0 Hz. Furthermore, the 1H (proton) nuclear magnetic resonance (NMR) pattern of phenolic hydroxyl protons was developed as a “diagnosis signal” to ascertain the relative location of each side chain in DMSO‑d6 at sample concentrations of 0.022–0.034 mol/L. The chemical shift differences of 0.6 ppm between OH-5′ and OH-1 and between OH-8′ and OH-4 are assigned to Type A and Type B, respectively. All reported ambiguous structures were corrected by this pattern. Additionally, the steric structures of isolated compounds were elucidated by quantum chemical calculations of electronic circular dichroism (ECD) spectra.

Insight into the Structural Ambiguity of Actinide(IV) Oxalate Sheet Structures: A Case for Alternate Coordination Geometries.

Invited for the cover of this issue is the group of Amy Hixon at the University of Notre Dame. The image depicts the newly identified structure of a PuIV oxalate sheet compared to the historically assumed structure. Read the full text of the article at 10.1002/chem.202301164.

Front Cover: Insight into the Structural Ambiguity of Actinide(IV) Oxalate Sheet Structures: A Case for Alternate Coordination Geometries (Chem. Eur. J. 47/2023)

Front Cover: Insight into the Structural Ambiguity of Actinide(IV) Oxalate Sheet Structures: A Case for Alternate Coordination Geometries (Chem. Eur. J. 47/2023)

Insight into the structural ambiguity of actinide(IV) oxalate sheet structures: a case for alternate coordination geometries.

Plutonium(IV) oxalate hexahydrate (Pu(C2O4)2∙6H2O; PuOx) is an important intermediate in the recovery of plutonium from used nuclear fuel. Its formation via precipitation is well studied, yet its crystal structure remains unknown. Instead, the crystal structure of PuOx is assumed to be isostructural with neptunium(IV) oxalate hexahydrate (Np(C2O4)-2∙6H2O; NpOx) and uranium(IV) oxalate hexahydrate (U(C2O4)-2∙6H2O; UOx) despite the high degree of unresolved disorder that exists when determining water positions in the crystal structures of the latter two compounds. Such assumptions regarding the isostructural behavior of the actinide elements have been used to predict the structure of PuOx for use in a wide range of studies. Herein, we report the first crystal structures for PuOx and Th(C2O4)2·6H2O (ThOx). This data, along with new characterization of UOx and NpOx, has resulted in the full determination of the structures and resolution of the disorder around the water molecules. Specifically, we identify the coordination of two water molecules with each metal center, which necessitates a change in oxalate coordination mode from axial to equatorial that has not been reported in the literature. This work exemplifiesthe need to revisit previous assumptions regarding fundamental actinide chemistry, which are heavily relied upon within the current nuclear field.

Pauses and Parsing: Testing the Role of Prosodic Chunking in Sentence Processing

It is broadly accepted that the prosody of a sentence can influence sentence processing by providing the listener information about the syntax of the sentence. It is less clear what the mechanism is that underlies the transmission of this information. In this paper, we test whether the influence of the prosodic structure on parsing is a result of perceptual breaks such as pauses or whether it is the result of more abstract prosodic elements, such as intonational phrases. In three experiments, we test whether different types of perceptual breaks, e.g., intonational boundaries (Experiment 1), an artificial buzzing sound (Experiment 2), and an isolated pause (Experiment 3), influence syntactic attachment in ambiguous sentences. We find that although full intonational boundaries influence syntactic disambiguation, the artificial buzz and isolated pause do not. These data rule out theories that argue that perceptual breaks indirectly influence grammatical attachment through memory mechanisms, and instead, show that listeners use prosodic breaks themselves as cues to parsing.

A superior image inpainting scheme using Transformer-based self-supervised attention GAN model

Image inpainting is the task of reconstructing the missing regions in diverse imaging as well as graphic applications which includes object elimination, image restoration, as well as manipulation. Although various deep learning techniques have attained a notable progress in restoration of images, because of local nature of different operations, they cannot effectively capture both global as well as semantic information, leading to issues such as structural ambiguity and semantic incompleteness, particularly for larger missing areas. To overcome these limitations, this article proposes a novel Transformer-based self-supervised attention-generating adversarial image painting method that leverages the Transformer's self-attention strategy to capture global semantic data. The proposed technique establishes a self-supervised attention module in the Transformer to overcome the limitations of convolutional operations. Additionally, a hierarchical Swin Transformer with a shift window is used in the discriminator to remove the image's contextual features, while semantic feature learning is performed using the transformer structure. The generator also employs a depthwise over-parameterized convolutional layer (DO-Conv) to extract features and enhance model performance. The experimental evaluations are carried out and result analysis demonstrated that the proposed technique outperformed various other existing approaches. Overall, the proposed method effectively addresses the limitations of existing approaches and demonstrates the superiority of the Transformer-based generative adversarial network structure over the full convolution approach.

Perceptions of Undergraduate ESL Learners towards Syntax Contents & Teaching Methodology

Syntax is one of the important branches of theoretical linguistics that deals with the study of structural constructions of various languages. However, learners often find studying and internalizing the contents of syntax a challenging and daunting task. To address this issue, mixed-method research was conducted to evaluate the perceptions of fifty non-randomly selected sixth-semester undergraduate ESL students with reference to the course contents and teaching methodology. The survey research design was employed, and the data were collected through a comprehensive questionnaire. Findings reveal that most learners studied grammar at schools and colleges through the deducted approach. This grammar background has enabled them to grasp course contents of syntax rather effortlessly. Moreover, the learning process was facilitated by comparing English syntactic constructions to those of the Urdu language in addition to the structures of other languages. However, there are some topics that learners find somewhat laborious and challenging to internalize. These contents include tree diagrams, structural ambiguity, forms and functions, phrase structure rules, and X-bar rules. Personalized instruction and extensive practice can make these course contents less challenging. The learners generally have felt their overall satisfaction with the teacher's interactive and learner-centered teaching methodology.

Encoding legislation: a methodology for enhancing technical validation, legal alignment and interdisciplinarity

This article proposes an innovative methodology for enhancing the technical validation, legal alignment and interdisciplinarity of attempts to encode legislation. In the context of an experiment that examines how different legally trained participants convert select provisions of the Australian Copyright Act 1968 (Cth) into machine-executable code, we find that a combination of manual and automated methods for coding validation, which focus on formal adherence to programming languages and conventions, can significantly increase the similarity of encoded rules between coders. Participants nonetheless encountered various interpretive difficulties, including syntactic ambiguity, and intra- and intertextuality, which necessitated legal evaluation, as distinct from and in addition to coding validation. Many of these difficulties can be resolved through what we call a process of ‘legal alignment’ that aims to enhance the congruence between encoded provisions and the true meaning of a statute as determined by the courts. However, some difficulties cannot be overcome in advance, such as factual indeterminacy. Given the inherently interdisciplinary nature of encoding legislation, we argue that it is desirable for ‘rules as code’ (‘RaC’) initiatives to have, at a minimum, legal subject matter, statutory interpretation and technical programming expertise. Overall, we contend that technical validation, legal alignment and interdisciplinary teamwork are integral to the success of attempts to encode legislation. While legal alignment processes will vary depending on jurisdictionally-specific principles and practices of statutory interpretation, the technical and interdisciplinary components of our methodology are transferable across regulatory contexts, bodies of law and Commonwealth and other jurisdictions.

Syntactic adaptation leads to updated knowledge for local structural frequencies.

Syntactic adaptation has been shown to occur for various temporarily ambiguous structures, wherein an initially unexpected resolution becomes easier to process after repeated exposure. More controversial and less replicated is the claim that this adaptation towards a locally frequent structure occurs due to a strategic shifting of expectations to match short-term statistical regularities such that readers adapt away from the a priori more frequent structure. Experiment 1 replicates the initial adaptation towards a coordination garden path structure using self-paced reading; however, this paradigm has been criticised for its low reliability for detecting such small effects. To this end, Experiments 2 and 3 use a combination of self-paced reading and sentence completion tasks to replicate initial adaptation towards both coordination and reduced relative garden path structures and show evidence for a preference for these structures over their a priori more frequent alternatives. Together, these data reveal that participants may be tracking local structural statistics in real time; however, they may not be able to rapidly use that information to update processing behaviours.

Removal of the Vertical Structure Ambiguity in the Thermodynamic Retrieval from Multiple-Doppler Radar Synthesized Wind Fields

Abstract It has been long recognized that in the retrieved thermodynamic fields using multiple-Doppler radar synthesized winds, an unknown constant exists on each horizontal level, leading to an ambiguity in the retrieved vertical structure. In this study, the traditional thermodynamic retrieval scheme is significantly improved by the implementation of the Equation of State (EoS) as an additional constraint. With this new formulation, the ambiguity of the vertical structure can be explicitly identified and removed from the retrieved three-dimensional thermodynamic fields. The only in situ independent observations needed to perform the correction are the pressure and temperature measurements taken at a single surface station. If data from multiple surface stations are available, a strategy is proposed to obtain a better estimate of the unknown constant. Experiments in this research were conducted under the observation system simulation experiment (OSSE) framework to demonstrate the validity of the new approach. Problems and possible solutions associated with using real datasets and potential future extended applications of this new method are discussed.

Time series prediction with granular neural networks

Conventional artificial neural networks are inherently equipped with an ambiguous (uncertain) structure which is hard to be quantified and explained. Time series forecasting using neural networks thus becomes a highly challenging task also due to the fact that time series data are always nonlinear and uncertain (because of some disturbances). Considering this, we propose a granular neural network-based time series prediction model connecting the uncertainty of models and data with the concept of information granularity. We aim to provide an explainable time series prediction model to resist the disturbance inner time series data and reduce the vagueness of the model. The functionalities of the granular neural network model are threefold: (1) It reveals the uncertainty of a time series data set through the level of granularity, coverage and specificity and possesses high prediction accuracy; (2) It provides an optimized interval output endowed with enough specificity and sufficient coverage and this interval is more robust than a single value; (3) It owns an interpretable and flexible structure that reflects the uncertainty of the initial numeric neural network and the generalization and robustness of connections while being faced with disturbances. The experimental studies elaborate on each function of our model in detail and show that the developed method performed better than the existing approaches present in the literature when experimenting on several time series data sets.