Static Semantics Research Articles

The second genitive in the history of Russian and across its dialects

Abstract In this paper, we provide a survey of the diachronic development of the Russian second genitive (Gen2). As endpoints of this development, we consider data from Russian dialects representing different dialect groups. Assumedly, the expansion of Gen2 started off as ‘recycling’ of the genitive of a declension type that became obsolete already in the pre-written period. Nouns of this declension type were adopted by another declension, carrying their old genitive over as a variant form. This alternative ending started spreading, always as a variant, to other nouns in the adoptive declension. As the survey of the literature shows, in the course of this expansion new constraints evolved, including phonological, morphophonological, phonotactic, syntactic and semantic conditioning. While there is no declension class or even individual nouns where Gen2 became the only option, it expanded to different extents in different dialects. We believe that the diversity of functions associated with the form, the range of language-internal factors driving its expansion, as well as the current geographic distribution of constraints on its formation weaken the claim that emergence of Gen2 as a morphological category dedicated to partitive was due to contact with the languages of the Circumbaltic area, a suggestion made on a macro-areal basis and also based on comparison with the northern dialects alone. While we cannot argue that the data we present disproves the contact factor, we would at least expect that the increased granularity of dialectal data would provide some data to support it. This is not what happens, which we consider to be an argument against contact-induced change. The aim of the paper is two-fold: to present a synopsis of the discussions of the history of Gen2 and a survey of the data on the use of Gen2 in the dialects, both firsthand and available from the literature; and to question the role of contact in the emergence of the new category of Gen2 in Russian.

Deep-learning-based porous media microstructure quantitative characterization and reconstruction method.

Microstructure characterization and reconstruction (MCR) is one of the most important components of discovering processing-structure-property relations of porous media behavior and inverse porous media design in computational materials science. Since the algorithms for describing and controlling the geometric configuration of microstructures need to solve a large number of variables and involve multiobjective conditions, the existing MCR methods have difficulty in gaining a perfect trade-off among the quantitative generation and characterization capability and the reconstruction quality. In this work, an improved 3D Porous Media Microstructure (3DPmmGAN) generative adversarial network based on deep-learning algorithm is demonstrated for high-quality microstructures generation with high controllability and high prediction accuracy. The proposed 3DPmmGAN allows the model to utilize unlabeled data for complex high-randomness microstructures end-to-end training within an acceptable time consumption. Further analysis shows that the trained network has good adaptivity for microstructures with different random geometric configurations, and can quantitatively control the generated structure according to semantic conditions, and can also quantitatively predict complex microstructure features. The key results suggest the proposed 3DPmmGAN is a powerful tool to accelerate the preparation and the initial characterization of 3D porous media, and potentially maximize the design efficiency for porous media.

Multiscale Feature Enhancement Network for Salient Object Detection in Optical Remote Sensing Images

Aircraft detection in synthetic aperture radar (SAR) images plays an essential role in satellite observation and military decisions. Due to discrete scattering properties, speckle noise interference, and various aircraft types, many existing methods struggle to achieve the desired detection performance. In this article, we propose an innovative semantic condition constraint guided feature aware network (SCFNet) for detecting different aircraft categories in SAR images. First, considering the discrete scattering properties of aircraft, we design a local-global feature aware module (LGA-M) and morphological-semantic feature aware module (MSF-M), which can effectively extract the fine-grained feature information contained in SAR images. Second, to effectively fuse different feature information, we construct a feature fusion pyramid (FFP), which uses different branches and paths to reasonably merge multiple feature information types and suppresses background information interference. Third, according to the structure characteristics of aircraft, the global coordinate attention mechanism (G-CAT) is presented to highlight foreground target features and suppress speckle noise interference. Finally, we construct semantic condition constraints, including constraint condition setting, semantic information calculation, and template matching, to improve aircraft localization and recognition accuracy. Extensive experiments demonstrate that the proposed SCFNet can obtain state-of-the-art performance on the SAR aircraft detection dataset, which achieves AP and F1 Score of 94.83% and 95.58%, respectively. The related implementation codes will be made publicly available at https://github.com/darkseid-arch/AirDetection.

The Paradigmatic and Syntagmatic Priming Effect of Part of Speech Representation

Part of speech feature is the representation between syntactic morphology and semantic category. Priming effect experiment can test the correlation between the parts of speech feature and the lexical processing process. This article puts forward part of speech representation paradigmatic and syntagmatic effect hypotheses. The experiments applied the design pattern of 3 (part of speech: noun by predicate by nonword) ∗ 2 (interval time: 50 by 500 milliseconds) ∗3 (English level: elementary by intermediate by advanced). Subjects are requested to make options of the part of speech of the target words. This study shows that when Chinese English learners extract an individual word, their choices are still influenced by part of speech factor without the restrictions of constructive syntagmatic semantic conditions. Both the syntagmatic and paradigmatic effects are verified. Part of speech priming effect intensity is influenced by the English acquisition levels of the subjects.

SCFNet: Semantic Condition Constraint Guided Feature Aware Network for Aircraft Detection in SAR Images

Aircraft detection in synthetic aperture radar (SAR) images plays an essential role in satellite observation and military decisions. Due to discrete scattering properties, speckle noise interference, and various aircraft types, many existing methods struggle to achieve the desired detection performance. In this article, we propose an innovative semantic condition constraint guided feature aware network (SCFNet) for detecting different aircraft categories in SAR images. First, considering the discrete scattering properties of aircraft, we design a local-global feature aware module (LGA-M) and morphological-semantic feature aware module (MSF-M), which can effectively extract the fine-grained feature information contained in SAR images. Second, to effectively fuse different feature information, we construct a feature fusion pyramid (FFP), which uses different branches and paths to reasonably merge multiple feature information types and suppresses background information interference. Third, according to the structure characteristics of aircraft, the global coordinate attention mechanism (G-CAT) is presented to highlight foreground target features and suppress speckle noise interference. Finally, we construct semantic condition constraints, including constraint condition setting, semantic information calculation, and template matching, to improve aircraft localization and recognition accuracy. Extensive experiments demonstrate that the proposed SCFNet can obtain state-of-the-art performance on the SAR aircraft detection dataset, which achieves AP and F1 Score of 94.83% and 95.58%, respectively. The related implementation codes will be made publicly available at https://github.com/darkseid-arch/AirDetection.

A Study on the Condition with Object of VC Structure in Sou Shen Ji

There are many VC structures in “Sou Shen Ji”. These structures cannot be simply regarded as the VCO structure omitting O. In the history of Chinese development, they reflect the grammatical characteristics of connecting the past and the next. Semantically, there is always a “behavior-result” semantic relationship between the V that explains the behavior and the C that supplements the result. This semantic relationship is gradually improved with the grammaticalization of the complement. Syntactically, the internal composition relationship of the VC structure is different, and the conditions for taking objects are also different. First, the VC structure that cannot take the object, including the structure that does not have the object itself, and the structure that cannot take the object without the support of causative usage. Second, the VC structure that can carry the object. According to the context, the object of the VC structure can be found. According to the semantic characteristics of V and C, after restoring the syntactic position of the object, two structures of VCO and VOC can be formed. Third, the VC structure in the sentence of object used as subject can also form two structures of VCO and VOC due to the different grammaticalization process. After satisfying certain syntactic and semantic conditions, these VOC structures will eventually develop into various forms of Predicate-Complement-Object structures.

An overactive mind: Investigating racing thoughts in ADHD, hypomania and comorbid ADHD and bipolar disorder via verbal fluency tasks

BackgroundAdults with Attention Deficit Hyperactivity Disorder (ADHD) often report mental restlessness akin to racing thoughts found in hypomanic and mixed episodes of bipolar disorder (BD). Past research has suggested that racing thoughts in BD can be tackled via process-oriented verbal fluency measures. In ADHD, it is still unknown whether racing thoughts is due to comorbid BD, and its neuropsychological underpinnings remain to be investigated. To this aim, this study investigates process-oriented verbal fluency measures in adults with ADHD compared to adults with BD in a hypomanic episode, adults with ADHD + BD and healthy controls. MethodsThree verbal fluency tasks, i.e., the free, the letter and the semantic conditions, were administered to 37 adults with ADHD, 25 adults with BD in a hypomanic episode, 22 adults with comorbid ADHD + BD (euthymia) and 31 healthy subjects. Word production, clustering, and switching were analysed in verbal fluency tasks. ResultsAdults with ADHD, ADHD + BD and hypomania showed increased switches in the free verbal fluency task, compared to healthy controls, despite equivalent number of words produced. Unlike the ADHD and ADHD + BD groups, phonological clustering measures in the semantic task were increased in the hypomanic group compared to healthy controls. LimitationsBD groups were under medication. ConclusionsSemantic overactivation, reflected by increased switches in the unconstrained verbal fluency task, appear to be a common mechanism involved in racing thoughts in both ADHD and BD. By contrast, unusual sounds-based associations are specific of hypomanic speech and might contribute to the distinction trait and state racing thoughts.

Towards an Extrinsic Formalization of Featherweight Java in Agda

Featherweight Java is one of the most popular calculi which specify object-oriented programming features. It has been used as the basis for investigating novel language functionalities, as well as to specify and understand the formal properties of existing features for languages in this paradigm. However, when considering mechanized formalization, it is hard to find an implementation for languages with complex structures and binding mechanisms as Featherweight Java. In this paper we formalize Featherweight Java, implementing the static and dynamic semantics in Agda, and proving the main safety properties for this calculus.

Neural and behavioural effects of typicality, denotation and composition in an adjective–noun combination task

ABSTRACT Formal semantics states that the meanings of phrases are composed from the meanings of constituent parts and syntax. Little is known about how composition is neurally implemented. We studied ERP and behavioural responses to determiner-adjective-noun phrases. We assessed the effects of typicality and denotation, using intersective (typical: “A green turtle”, atypical: “An orange turtle”) or subsective adjectives (typical: “A slow turtle”, atypical: “A fast turtle”). After each phrase, participants responded to two questions (e.g., for “A fast turtle”: “Is it a common turtle?”; “Is it a fast animal?”). We contrasted these 4 semantic conditions, requiring composition, to 2 nonsemantic conditions, where the adjective was replaced with a pseudoword or a nonword. This contrast revealed a larger P600, if participants performed the task without instructions and feedback (experiment 1), or a larger sustained negativity, if they were nudged to pay attention to meaning by instructions and feedback (experiment 2). Typicality or denotation had an impact only on behavioural responses. We discuss implications for theories of language processing and compositional semantics.

Interfered-Naming Therapy for Aphasia (INTA): a neuroscience-based approach to improve linguistic-executive processing

ABSTRACT Background and Aims Research just started to combine behavioural, computational, and neural accounts to investigate the nature of post-stroke aphasia, but the dynamic aspect of aphasia recovery has rarely been integrated. Moreover, executive functions in aphasia recently gained attention as an important contributor to language performance. Lexical picture/word interference embraces both executive control and language processing through distracted confrontation naming, as revealed by functional magnetic resonance imaging. Thus, we for the first time applied this complex paradigm in diagnostic and therapeutic settings for persons with aphasia (PWA) on the group level. In consideration of behavioural and computational data, we aimed at investigating the neural responses of persons with aphasia (a) to a novel treatment method targeting both word processing and language control by means of interfered-naming, and (b) to the interfering stimuli to determine preserved and impaired processing and changes thereof. Methods and Procedures Nineteen PWA at a mean age of 51 years (range 21–74) and 26 months post-onset (4–63) as well as 22 matched healthy controls were included in a diagnostic fMRI study comprising a pure naming test and the lexical fMRI interference paradigm with five distractor conditions (phonological, associative-semantic, categorical-semantic, unrelated word, unrelated noise) in a 3 T Philips scanner. Twelve participants completed the 4-weeks therapy, 11 the fMRI therapy study. During therapy, both comprehension of the interfering words and distracted but cued picture naming were trained. Outcomes and Results The distribution of lexical-semantic and -phonological impairments of PWA in the computational model was well balanced. The novel linguistic-executive treatment significantly improved pure and interfered naming for the PWA group, fostering generalisation to untrained items, reducing repetition of distractors, and ameliorating lexical-semantic processing. The predicted behavioural effects of distractor types were only found for the two semantic conditions. Neuroimaging revealed right-hemisphere compensation before treatment, activation decrease related to enhanced efficiency due to treatment, and both differential and overlapping responses to distractor types. Key brain regions encompassed inferior frontal gyrus and right posterior middle temporal gyrus as well as the basal temporal language area, cerebellum, and anterior cingulate cortex. Conclusions The novel interfered-naming in aphasia therapy revealed to be effective, but differential effects of distractor types were less prominent than expected. Behavioural, computational, and neural findings converge on identifying semantic-executive processing as the core source of improvements. This account of linguistic-executive processing in aphasia offers a step towards a comprehensive theory of neurorehabilitation.

Blaga-Cioran: Incursiuni În Marginea Fiinţei

Abstract The following paper focuses on what lies between transcendence and reality, between self and non-self, between bounded and infinite, it focuses on that included third which contradicts Aristotelian logic and which is represented by the margin itself, by the boundary between these concepts, as it is reflected in the texts of Lucian Blaga and Emil Cioran. The role of the limit is analysed especially in those contexts in which, in addition to spatial references, the limit has a figurative meaning, that of term at the intersection of an antithetical binomial that advances the being, in Hegel’s vision, towards becoming. Consequently, the paper will refer to texts from Blaga’s poetry, where there are twenty occurrences of the word “limit” (Romanian: “margine”), six of which meet the semantic condition mentioned above, but also in Cioran’s texts that treat this matter.

Dorsal and Ventral Cortical Connectivity Is Mediated by the Inferior Frontal Gyrus During Facilitated Naming of Pictures.

Background: It is well recognized that semantic processing and auditory repetition facilitate subsequent naming of pictures. However, the neurocognitive mechanisms that underpin these facilitation effects remain unclear. Materials and Methods: The current study utilized a dynamic causal modeling (DCM) approach to examine high-density electroencephalographic (128-channel EEG) recordings and investigate connectivity modulations during facilitated naming of pictures in 18 healthy older adults (mean age 61.50 years). Source reconstruction of event-related potentials was performed in two specific time windows, (1) 150-250 msec and (2) 300-500 msec, to establish the timescale of significant cortical activations present during participation of semantic and phonological tasks. Hypothesis-driven DCM of source-activated regions was tested to ascertain which model most likely explained the semantic and phonological conditions, respectively. Results: DCM results indicated that a common cortical network comprising dorsal and ventral cortical connections best explained EEG task data derived from repetition and semantic tasks. For repetition (phonological) tasks, this model featured long feedback, bidirectional connections from inferior frontal gyrus (IFG) to occipitotemporal areas. Semantic tasks were most plausibly explained by a model that featured a self-inhibiting connection over the IFG only. Conclusions: Findings from this study reveal that a common cortical model comprising pathways that include dorsal and ventral regions is appropriate for characterizing EEG naming facilitation data, and that distinct cortical connections explain differences between semantic and auditory repetition processes. These models could be repurposed for naming facilitation paradigms in patients with language difficulties to optimize prediction and responsiveness to such paradigms. Impact statement The combination of semantic (word-level) and phonological (sound-level) processing in the cortex facilitates one of the most robust responses-the naming of pictures. Here, dynamic causal modeling of high-density electroencephalography during facilitated naming tasks revealed a model consisting of common dorsal and ventral connections that best explained response to semantic and phonological stimuli. Within this cortical network, phonological facilitation involved a long-range connection from inferior frontal gyrus (IFG) to occipitotemporal regions, whereas semantic facilitation contributed to self-inhibition of the IFG. The IFG is therefore a key region mediating cortical activity when switching between phonological and semantic conditions.

How does semantic pain and words condition pain perception? A short communication.

Language is one of the main tools with whom people describe their pain. The semantic value of words plays a fundamental role in the pain perception, intended as a complex process of modulation and processing in the brain. The priming effect is a cognitive process in which a certain stimulus can influence subsequent stimuli. It is therefore plausible that this effect plays a key role in the modulation and perception of pain. This study aimed to investigate the potential relationship between the semantic aspects of language, the priming effect, and the perception of pain. A narrative review of the literature was conducted. Sixteen studies were included and categorized in four groups based on the effect of the verbal suggestion on the experimental acute pain and chronic pain and on the effect of pain-related words in free pain and post-surgical subjects. There may be a link between language and pain, both at the behavioral and neural level. The processing of semantic information associated with pain influences the pain perception.

The ERP correlates of self-knowledge in ageing

Self-knowledge is a type of personal semantic knowledge that concerns one’s self-image and personal identity. It has most often been operationalized as the summary of one’s personality traits (“I am a stubborn person”). Interestingly, recent studies have revealed that the neural correlates of self-knowledge can be dissociated from those of general semantic and episodic memory in young adults. However, studies of “dedifferentiation” or loss of distinctiveness of neural representations in ageing suggest that the neural correlates of self-knowledge might be less distinct from those of semantic and episodic memory in older adults. We investigated this question in an event-related potential (ERP) study with 28 young and 26 older adults while they categorised personality traits for their self-relevance (self-knowledge conditions), and their relevance to certain groups of people (general semantic condition). Participants then performed a recognition test for previously seen traits (episodic condition). The amplitude of the late positive component (LPC), associated with episodic recollection processes, differentiated the self-knowledge, general semantic, and episodic conditions in young adults, but not in older adults. However, in older adults, participants with higher composite episodic memory scores had more differentiated LPC amplitudes across experimental conditions. Moreover, consistent with the fact that age-related neural dedifferentiation may be material and region specific, in both age groups some differences between memory types were observed for the N400 component, associated with semantic processing. Taken together, these findings suggest that declarative memory subtypes are less distinct in ageing, but that the amount of differentiation varies with episodic memory function.

How semantic knowledge enhances word recognition? New evidence from struggling readers performances

The current study examined the contribution of semantic knowledge to the process of reading aloud unfamiliar words among thirty non-typical readers from third grade. The performances of reading aloud were tested by using three lists of pseudowords: semantic, phonological, and un-trained. For each pseudoword in the list of semantic condition, an invented meaning was matched, and the participants orally trained to learn such invented meaning. For the list of the phonological condition, the participants were orally taught the pronunciation of the pseudowords only, while the third list of pseudowords was not trained at all. After the training phase, the subjects were examined by reading aloud the pseudowords which were presented randomly. For all lists of the pseudowords, there was no orthographic exposure before the reading trial. The findings showed that the higher levels of accuracy were significantly recorded for the semantic condition as compared to the other conditions, without a significant difference in the reading rate between all the conditions. The current findings were discussed in the context of the contribution of semantic activation to reading aloud of written words.

On the automation-supported derivation of domain-specific UML profiles considering static semantics

In the light of standardization, the model-driven engineering (MDE) is becoming increasingly important for the development of DSLs, in addition to traditional approaches based on grammar formalisms. Metamodels define the abstract syntax and static semantics of a DSL and can be created by using the language concepts of the Meta Object Facility (MOF) or by defining a UML profile.Both metamodels and UML profiles are often provided for standardized DSLs, and the mappings of metamodels to UML profiles are usually specified informally in natural language, which also applies for the static semantics of metamodels and/or UML profiles, which has the disadvantage that ambiguities can occur, and that the static semantics must be manually translated into a machine-processable language.To address these weaknesses, we propose a new automated approach for deriving a UML profile from the metamodel of a DSL. One novelty is that subsetting or redefining metaclass attributes are mapped to stereotype attributes whose values are computed at runtime via automatically created OCL expressions. The automatic transfer of the static semantics of a DSL to a UML profile is a further contribution of our approach. Our DSL Metamodeling and Derivation Toolchain (DSL-MeDeTo) implements all aspects of our proposed approach in Eclipse. This enabled us to successfully apply our approach to the two DSLs Test Description Language (TDL) and Specification and Description Language (SDL).

Peirce’s Triadic Logic and Its (Overlooked) Connexive Expansion

In this paper, we present two variants of Peirce’s Triadic Logic within a language containing only conjunction, disjunction, and negation. The peculiarity of our systems is that conjunction and disjunction are interpreted by means of Peirce’s mysterious binary operations Ψ and Φ from his ‘Logical Notebook’. We show that semantic conditions that can be extracted from the definitions of Ψ and Φ agree (in some sense) with the traditional view on the semantic conditions of conjunction and disjunction. Thus, we support the conjecture that Peirce’s special interest in these operations is due to the fact that he interpreted them as conjunction and disjunction, respectively. We also show that one of our systems may serve as a suitable base for an interesting implicative expansion, namely the connexive three-valued logic by Cooper. Sound and complete natural deduction calculi are presented for all systems examined in this paper.

PROBLEMS OF TRANSLATION OF FRENCH AND UZBEK DEOPOETONYMS

Introduction. In world onomatology, the weight of research devoted to the study of the lexicon of the French language, including the basics of the origin of deopoetonyms, structural and semantic conditioning, the scope of use in comparison with other languages is growing. As a logical consequence, the comparison of linguistic-stylistic, poetonymic, gender features of the French and Uzbek deopoetonyms in the language lexical-semantic, national-cultural, literary text has gained priority and relevance in the field of linguistics. Indeed, the definition of the semantic and stylistic potential of these units, the interpretation of general and differential motivational aspects of naming within different systematic languages serve to improve the system of representation of deopoetonyms in dictionaries, to determine the laws of functional equivalence and adequacy in the translation process. Research methods. In the use of words expressing the names of natural phenomena in literary texts, their special reliance on linguocognitive and linguocultural semantics is more clearly understood in the process of translation. In particular, reliance on denotative semaphores rather than expressive semaphores of deemoetonyms in artistic texts is one of the important aspects of the poetic skill of creators. This is especially the case in poetic texts. The translation process should take into account the etymology, methodological features, derivational properties, semantics (synonymy), formality (homonymy), ambiguity (polysemantic), hierarchy (graduonymic), semantic contradiction (antonymicity), etc. will be. When direct and indirect translations of some poetic texts written in French are observed, it becomes clear that deopoetonyms are preserved and expressed at different levels in them. Results and discussion. In dictionaries deopoetonyms are given in the system of el-yagyn names, but in the dictionaries compiled later their etymology, linguistic meanings, lexical-semantic semantics, formality, antonyms, hyphenation, hierarchical formation, methodological features, derivational properties, diachronic and synchronous forms, vital giving features such as denotative, connotative expression on the basis of concepts is necessary to achieve perfection of lexicographic interpretation. Conclusion. It is natural that there are still some problems with the lexicographic interpretation of deopoetonyms, which will cause some problems in the smooth implementation of translation work in this regard. Such problems are especially evident in the presentation of lexical graduonomic series related to them, in the expression of close concepts, connotative and denotative meanings

Friendly Fire

IoT platforms enable users to connect various smart devices and online services via reactive apps running on the cloud. These apps, often developed by third-parties, perform simple computations on data triggered by external information sources and actuate the results of computations on external information sinks. Recent research shows that unintended or malicious interactions between the different (even benign) apps of a user can cause severe security and safety risks. These works leverage program analysis techniques to build tools for unveiling unexpected interference across apps for specific use cases. Despite these initial efforts, we are still lacking a semantic framework for understanding interactions between IoT apps. The question of what security policy cross-app interference embodies remains largely unexplored. This article proposes a semantic framework capturing the essence of cross-app interactions in IoT platforms. The framework generalizes and connects syntactic enforcement mechanisms to bisimulation-based notions of security, thus providing a baseline for formulating soundness criteria of these enforcement mechanisms. Specifically, we present a calculus that models the behavioral semantics of a system of apps executing concurrently, and use it to define desirable semantic policies targeting the security and safety of IoT apps. To demonstrate the usefulness of our framework, we define and implement static analyses for enforcing cross-app security and safety, and prove them sound with respect to our semantic conditions. We also leverage real-world apps to validate the practical benefits of our tools based on the proposed enforcement mechanisms.

Preferred Lexical Access Route in Persian Learners of English: Associative, Semantic or Both

Background: Words in the Mental Lexicon (ML) construct semantic field through associative and/ or semantic connections, with a pervasive native speaker preference for the former. Non-native preferences, however, demand further inquiry. Previous studies have revealed inconsistent Lexical Access (LA) patterns due to the limitations in the methodology and response categorization. Objectives: To fill the gap, we employed a primed Picture Naming (PN) task for investigating the relations between concepts in the ML of Iranian EFL (English as a foreign language) learners. We also explored whether conscious priming at a long prime-target stimulus onset asynchrony affected the naming latency of the learners with different proficiency levels. Materials & Methods: The participants were 31 EFL learners (11-16 years old) at A1 and A2 levels based on the Common European Framework of Reference for languages. They were recruited in summer 2020 from language institutes in Bushehr and Kazeroon cities, Iran, through a convenience sampling method. They performed a PN task, including 66 prime-target pairs presented in associative, semantic, both semantic and associative, or unrelated conditions. The mixed-effects modeling was used for data analysis. Results: Based on the likelihood ratio test of model comparisons for condition effect (χ2 (1) =9.07, P=0.002), the interaction of condition, frequency, and length was significant in the semantic condition (t=2.72, P=0.008). A slight effect was also observed from the prime frequency in the associative condition (t=1.82, P=0.07). Conclusion: Results indicate one-level access to the ML, which is indeed a function of language proficiency. Findings are further discussed in terms of ML structure and patterns of LA.