String Languages Research Articles

Targeting ferroptosis reveals a new strategy for breast cancer treatment: a bibliometric study

BackgroundStudies exploring the role of ferroptosis in the pathogenesis of breast cancer have proliferated over the past decade, especially in 2023, with a staggering 217 publications in related studies. However, there are still significant gaps in comprehensive scientometric analysis and mapping of scientific studies, especially in terms of temporal and study area tracking, principal investigators, and the emergence of new hotspots.ObjectiveThis study aims to summarize the role of ferroptosis in the development of breast cancer and the latest research results on the ferroptosis-targeted treatment of breast cancer and to use bibliometric methods to draw a visual map to explore future research trends.MethodsOn May 11, 2024, this study updated the research progress related to ferroptosis and breast cancer over the past 11 years by retrieving data from January 1, 2014, to May 1, 2024, from the Web of Science database. In this research, many scientific analysis software including VOSviewer, chorddiag R Language Pack, Scimago Graphica, Citespace 6.3.R1, Cluster Profiler, enrichplot, ggplot2 R Language Pack, Cytoscape, and STRING online platform are used to make in-depth scientific analysis and visualization of the measurement results.ResultsStatistical analysis of these data showed that China accounted for 74.43% of the total publications, highlighting China’s dominant role in research on the relationship between ferroptosis and breast cancer. Several research institutions, including Sun Yat-sen University, Zhejiang University, and Shanghai Jiao Tong University, have achieved impressive results. Efferth, Thomas is the most prominent author in this field and has the highest number of publications in the subfield of oncology. This study clearly shows that ferroptosis plays a crucial role in the development of triple-negative breast cancer, hepatocellular carcinoma, glioma, leukemia, mitochondrial disease, lymphoma, bladder tumors, lung adenocarcinoma, and esophageal tumors.ConclusionThis study provides a comprehensive bibliometric evaluation that deepens our understanding of the role of ferroptosis in the pathogenesis of breast cancer and the current status of targeting ferroptosis for treating breast cancer. Thus, it helps researchers in related fields explore new research directions by comprehensively extracting important information and research hotspots.

Completeness Theorems for Kleene algebra with tests and top

We prove two completeness results for Kleene algebra with tests and a top element, with respect to guarded string languages and binary relations. While the equational theories of those two classes of models coincide over the signature of Kleene algebra, this is no longer the case when we consider an additional constant ``top'' for the full element. Indeed, the full relation satisfies more laws than the full language, and we show that those additional laws can all be derived from a single additional axiom. We recover that the two equational theories coincide if we slightly generalise the notion of relational model, allowing sub-algebras of relations where top is a greatest element but not necessarily the full relation. We use models of closed languages and reductions in order to prove our completeness results, which are relative to any axiomatisation of the algebra of regular events. For one of our constructions, we extend the concept of finite monoid recognisability to guarded-string languages; this device makes it possible to obtain a PSpace algorithm for the equational theory of binary relations.

Prosody outweighs statistics in 6-month-old German-learning infants' speech segmentation.

It is well established that infants use various cues to find words within fluent speech from about 7 to 8months of age. Research suggests that two main mechanisms support infants' speech segmentation: prosodic cues like the word stress patterns, and distributional cues like transitional probabilities (TPs). We tested 6-month-old German-learning infants' use of prosodic and statistical cues for speech segmentation in three experiments. In Experiment 1, infants were familiarized with an artificial language string where TPs signaled either word boundaries or iambic words-a stress pattern that is disfavored in German. Experiment 2 was a control and only the test phase was presented. In Experiment 3, prosodic cues were absent in the string and only TPs signaled word boundaries. All experiments included the same conditions at test: disyllabic words with high TPs in the string, words with low TPs and words with non-co-occurring syllables. Results showed that infants relied more strongly on prosodic cues than on TPs for word segmentation. Notably, no segmentation evidence emerged when prosodic cues were absent in the string. This finding underlines early impacts of language-specific structural properties on segmentation mechanisms.

Learning Picture Languages Using Dimensional Reduction

One-dimensional (string) formal languages and their learning have been studied in considerable depth. However, the knowledge of their two-dimensional (picture) counterpart, which retains similar importance, is lacking. We investigate the problem of learning formal two-dimensional picture languages by applying learning methods for one-dimensional (string) languages. We formalize the transcription process from a two-dimensional input picture into a string and propose a few adaptations to it. These proposals are then tested in a series of experiments, and their outcomes are compared. Finally, these methods are applied to a practical problem and an automaton for recognizing a part of the MNIST dataset is learned. The obtained results show improvements in the topic and the potential to use the learning of automata in fitting problems.

Pipeline for the Automatic Extraction of Procedural Knowledge from Assembly Instructions into Controlled Natural Language

This paper presents the application of a Natural Language Processing (NLP) pipeline, which automatically extracts procedural knowledge in a standardized way from assembly instructions. The developed pipeline is able to parse and process written German assembly instructions regardless of the language discourse. The pipeline helps resolve ambiguities in assembly instructions by converting them into a Controlled Natural Language (CNL). The pipeline fully automates the translation process from free-text assembly instructions to CNL representations. We investigated and evaluated the efficiency and robustness of the NLP pipeline along multiple dimensions, such as different assembly process designers, language and fuzzy string matching models. To test the developed pipeline we used to automatically extract procedural knowledge in a standardized way for 2,740 assembly instructions obtained from automotive industry. Our investigation shows that the NLP pipeline is able to extract CNL representations with high accuracy (ø 87%). Downstream applications, such as assembly line balancing, can reuse the uniformly extracted procedural knowledge.

Automatic Extraction of English-Chinese Translation Templates Based on Deep Learning

Translation templates are an important cause of knowledge in machine translation (MT) systems. Their quality and scale directly influence the performance of MT systems. How to obtain high-quality and efficient translation templates from corpora has become a hot topic in recent study. In this paper, a tree to String alignment template (TAT) based on syntactic structure is proposed. This template describes the alignment between the source language syntax tree and the target language string. The syntactic structure, a large number of construction tags, and variables are introduced into the template, which enables the syntactic model to deal with discontinuous phrases and has the ability of generalization. Templates can be used in syntactic statistics, case-based, and rule-based MT systems according to different decoders. ATTEBSC algorithm is a basic method to learn translation templates by comparing sentence pairs. It demands that sentence pairs be constructed in a precise comparison structure ahead of time, but there are no strict guidelines on how to do it. In this paper, we propose a method to calculate the specific comparison scheme using the longest common subsequence (LCS) and use the normalized LCS distance to screen sentences with high similarity and then use the ATTEBSC algorithm to automatically remove the template. Experiments show that this method is easy and effective, and many expensive templates can be learned.

Context-sensitive fusion grammars and fusion grammars with forbidden context are universal

Context-sensitive fusion grammars and fusion grammars with forbidden context are special cases of context-dependent fusion grammars where instead of finite sets of positive and negative context conditions in the first case a rule has only a single positive context condition and in the second case a rule has only a finite set of negative context conditions. In this paper, we show that several decision problems can be formulated quite intuitively by these grammars. In particular, we show that the Boolean satisfiability problem as well as the Post correspondence problem can be transformed into a context-sensitive fusion grammar and that the graph coloring problem can be transformed into a fusion grammar with forbidden context such that the generated languages give solutions for the problems. Furthermore, we prove that both grammar types can generate all recursively enumerable string languages (up to representation of strings as graphs) and are universal in this respect.

Computational completeness of spiking neural P systems with inhibitory rules for generating string languages

Spiking neural P systems with inhibitory rules (in short, SNP-IR systems) are a distributed parallel computing model, abstracted by the spiking and inhibitory mechanisms of biological neurons. Computational completeness of SNP-IR systems as number generating/accepting and function computing devices has been studied recently. However, computational completeness of SNP-IR systems as language generating devices still has not been investigated. We discuss the relationship of languages generated by SNP-IR systems with regular languages. Moreover, we prove that SNP-IR systems can generate recursively enumerable languages by means of a projection of inverse-morphic image.

Mixed computation

AbstractProof-theoretic models of grammar are based on the view that an explicit characterization of a language comes in the form of the recursive enumeration of strings in that language. That recursive enumeration is carried out by a procedure which strongly generates a set of structural descriptions Σ and weakly generates a set of strings S; a grammar is thus a function that pairs an element of Σ with elements of S. Structural descriptions are obtained by means of Context-Free phrase structure rules or via recursive combinatorics and structure is assumed to beuniform: binary branching trees all the way down. In this work we will analyse natural language constructions for which such a rigid conception of phrase structure is descriptively inadequate and propose a solution for the problem of phrase structure grammars assigning too much or too little structure to natural language strings: we propose that the grammar can oscillate between levels of computational complexity in local domains, which correspond to elementary trees in a lexicalised Tree Adjoining Grammar.

On embedding Lambek calculus into commutative categorial grammars

AbstractWe consider tensor grammars, which are an example of ‘commutative’ grammars, based on the classical (rather than intuitionistic) linear logic. They can be seen as a surface representation of abstract categorial grammars (ACG) in the sense that derivations of ACG translate to derivations of tensor grammars and this translation is isomorphic on the level of string languages. The basic ingredients are tensor terms, which can be seen as encoding and generalizing proof nets. Using tensor terms makes the syntax extremely simple and a direct geometric meaning becomes transparent. Then we address the problem of encoding noncommutative operations in our setting. This turns out possible after enriching the system with new unary operators. The resulting system allows representing both ACG and Lambek grammars as conservative fragments, while the formalism remains, as it seems to us, rather simple and intuitive.

Nonlinear neural P systems for generating string languages

Nonlinear spiking neural P (NSNP) system is a distributed parallel computing model inspired from the mechanisms of spiking neurons. Computational completeness of NSNP systems as number generating/accepting devices and function computing devices has been already discussed. However, universality result of NSNP systems as language generating devices has not been established so far. This paper investigates computational power of NSNP systems as language generating devices. The relationships of languages generated by NSNP systems with regular languages are investigated. Moreover, we prove that recursively enumerable languages can be characterized by the projection of inverse-morphic images of languages generated by NSNP systems.

Strong Equivalence of TAG and CCG

Tree-adjoining grammar (TAG) and combinatory categorial grammar (CCG) are two well-established mildly context-sensitive grammar formalisms that are known to have the same expressive power on strings (i.e., generate the same class of string languages). It is demonstrated that their expressive power on trees also essentially coincides. In fact, CCG without lexicon entries for the empty string and only first-order rules of degree at most 2 are sufficient for its full expressive power.

Semantically Ambiguous Language in the Teaching Operating Room

Teaching and training surgeons work hard in the OR to understand each other, yet miscommunication is an important cause of preventable adverse events in surgery. Our objective was to perform a formal semantic analysis of language in authentic teaching surgical cases, identify the prevalence and typology of ambiguous or potentially ambiguous language, and describe their potential for miscommunication. In this secondary analysis of qualitative data, we collaborated with a semanticist, categorizing linguistic phenomena often associated with miscommunication. We defined an ambiguous phenomenon as a string of language that could be reasonably interpreted in more than one way. We analyzed transcripts of 319 minutes of surgery, coding for 14 linguistic categories.Cohen's kappa was calculated.We determined the prevalence and rate of each linguistic category and chose illustrative examples. Six surgical attendings, four fellows, and six residents, ranging from PGY1 to PGY4, at the University of Pittsburgh Medical Center, a tertiary medical center in Pittsburgh, Pennsylvania. We found 3912 examples of potentially ambiguous language, 12.3 per minute. Percentage agreement between two expert raters was 76.3%. The most common phenomena were deixis (3.1 per minute), directional (2.6), anaphora (1.3), implicit instruction (1.3), and degree modifiers (0.7). Restatements/reframing occurred 1.4 times per minute. We identified 131 near misses associated with potentially ambiguous language. Cohen's kappa was 0.70 among expert semanticists. Potentially ambiguous language is common and has the potential to jeopardize safe teaching surgery. We postulate that the high amount of potentially ambiguous language use in the operating room places a burden on the training surgeon to comprehend surgical instruction.

Parallel Hyperedge Replacement String Languages

There are many open questions surrounding the characterisation of groups with context-sensitive word problem. Only in 2018 was it shown that all finitely generated virtually Abelian groups have multiple context-free word problems, and it is a long-standing open question as to where to place the word problems of hyperbolic groups in the formal language hierarchy. In this paper, we introduce a new language class called the parallel hyperedge replacement string languages, show that it contains all multiple context-free and ET0L languages, and lay down the foundations for future work that may be able to place the word problems of many hyperbolic groups in this class.

A Bio-Inspired Model of Picture Array Generating P System with Restricted Insertion Rules

In the bio-inspired area of membrane computing, a novel computing model with a generic name of P system was introduced around the year 2000. Among its several variants, string or array language generating P systems involving rewriting rules have been considered. A new picture array model of array generating P system with a restricted type of picture insertion rules and picture array objects in its regions, is introduced here. The generative power of such a system is investigated by comparing with the generative power of certain related picture array grammar models introduced and studied in two-dimensional picture language theory. It is shown that this new model of array P system can generate picture array languages which cannot be generated by many other array grammar models. The theoretical model developed is for handling the application problem of generation of patterns encoded as picture arrays over a finite set of symbols. As an application, certain floor-design patterns are generated using such an array P system.

Computational power of dynamic threshold neural P systems for generating string languages

Inspired from spiking and dynamic mechanisms of neurons, dynamic threshold neural P systems (DTNP systems) have been developed and their computational completeness as number-generating/accepting devices and function computing devices has been investigated. However, a universality result of DTNP systems as language generators has not been established so far. This paper discusses computational power of DTNP systems as language generators. We first discuss the relationship between the languages generated by DTNP systems and finite languages, and then prove that regular languages can be generated by finite DTNP systems. Moreover, we prove that recursively enumerable languages can be characterized by projections of inverse-morphic images of the languages generated by DTNP systems.

Operator precedence temporal logic and model checking

In the last decades much research effort has been devoted to extending the success of model checking from the traditional field of finite state machines and various versions of temporal logics to suitable subclasses of context-free languages and appropriate extensions of temporal logics. To the best of our knowledge such attempts only covered structured languages, i.e. languages whose structure is immediately “visible” in their sentences, such as tree-languages or visibly pushdown ones. In this paper we present a new temporal logic suitable to express and automatically verify properties of operator precedence languages. This “historical” language family has been recently proved to enjoy fundamental algebraic and logic properties that make it suitable for model checking applications yet breaking the barrier of visible-structure languages (in fact the original motivation of its inventor Floyd was just to support efficient parsing, i.e. building the “hidden syntax tree” of language sentences). We prove that our logic is at least as expressive as analogous logics defined for visible pushdown languages yet covering a much more powerful family; we design a procedure that, given a formula in our logic builds an automaton recognizing the sentences satisfying the formula, whose size is at most exponential in the length of the formula. Our results cover both finite and infinite string languages.

Generation of cycle picture languages using sequential spiking neural P system

Spiking Neural P Systems (SN P Systems) is a bio-inspired computing model, abstracting the model of brain in processing information using spikes and neurons. The theoretical study of the model has proved that it can compute sets of positive numbers, Boolean functions and string languages. Cycle picture language is a set of pictures obtained using cycle grammar and chain code representation. In this paper we aim to compute the cycle picture languages using a variant of SN P system namely, Sequential SN P System using neurons and spiking rules. We compute the cycle picture language of sequence of chains.

Static Analysis for ECMAScript String Manipulation Programs

In recent years, dynamic languages, such as JavaScript or Python, have been increasingly used in a wide range of fields and applications. Their tricky and misunderstood behaviors pose a great challenge for static analysis of these languages. A key aspect of any dynamic language program is the multiple usage of strings, since they can be implicitly converted to another type value, transformed by string-to-code primitives or used to access an object-property. Unfortunately, string analyses for dynamic languages still lack precision and do not take into account some important string features. In this scenario, more precise string analyses become a necessity. The goal of this paper is to place a first step for precisely handling dynamic language string features. In particular, we propose a new abstract domain approximating strings as finite state automata and an abstract interpretation-based static analysis for the most common string manipulating operations provided by the ECMAScript specification. The proposed analysis comes with a prototype static analyzer implementation for an imperative string manipulating language, allowing us to show and evaluate the improved precision of the proposed analysis.

Perceiving the Materiality of Language in Teaching English Language Arts

As language is the medium of an art or a configuration of arts focused on communication, it is indispensable to realize the materiality of language with its potential to interpret the numerous phenomena in the environment. Our individual microcosms filled with messages on various complex situations received through our sensory channels exist in terms of strings of verbal language that help to re-create them for communication in whatever fashion we want. We experience language in meaningful utterances that function in singles or clusters to represent the life world in numerous registers. Our expressions inspired by our experiences of the life world are communicated through words orchestrated in grammatically patterned sentences. Like in other forms of art, in English language arts, teachers and learners can behave with confidence, when they realize the substance they deal with as oral sounds that gradually evolve into syllables, morphemes, signs, symbols, metaphors, and images, which creatively represent the life world. Against this background, I intend to demonstrate here the relevance of perceiving the materiality of language under the framework of a multifaceted unity of several disciplines, namely, phonology, morphology, semiotics, rhetoric, and stylistics that altogether contribute to a holistic approach to language. A concrete perception of language achieved in this manner helps to recover the learning process not only from inhibition and anxiety but also from fossilization and ephemerality.