Grammar

PURPOSE: This study examined the early efficacy of a new theory-driven principle of grammar intervention, graduated input type variation (GITV). METHOD: Three Cantonese-speaking children, aged between 4;01 and 5;10, with oral language difficulties participated in this single baseline within-participant single case experimental study. The children received a total of 300 teaching episodes of the target serial verb construction via focused stimulation and recast over 10 30- to 45-minute sessions...

To help non-native English speakers quickly master English vocabulary, and improve reading, writing, listening and speaking skills, and communication skills, this study designs, constructs, and improves an English vocabulary learning model that integrates Spiking Neural Network (SNN) and Convolutional Long Short-Term Memory (Conv LSTM) algorithms. The fusion of SNN and Conv LSTM algorithm can fully utilize the advantages of SNN in processing temporal information and Conv LSTM in sequence data modeling, and implement a fusion model that performs well in English vocabulary learning...

Children achieve better long-term language outcomes than adults. However, it remains unclear whether children actually learn language more quickly than adults during real-time exposure to input-indicative of true superior language learning abilities-or whether this advantage stems from other factors. To examine this issue, we compared the rate at which children (8-10 years) and adults extracted a novel, hidden linguistic rule, in which novel articles probabilistically predicted the animacy of associated nouns (e...

Procedural circuit Deficit Hypothesis (PDH) of Developmental Language Disorder (DLD) predicts problems with learning and retention of grammar. Twenty 7- to 9-year-old Cantonese-speaking children with DLD and their typically developing (TD) age peers participated in a syntactic priming task that was given in two sessions one week apart. Production of Indirect Object Relative Clause (IORC) was tested using a probe test before and after the priming task, and one week later. The study involved two cycles of learning and retention, and two levels of prior knowledge...

Standard computational models of language acquisition treat acquiring a language as a process of inducing a set of string-generating rules from a collection of linguistic data assumed to be generated by these very rules. In this paper I give theoretical and empirical arguments that such a model is radically unlike what a human language learner must do to acquire their native language. Most centrally, I argue that such models presuppose that linguistic data is directly a product of a grammar, ignoring the myriad non-grammatical systems involved in the use of language...

We demonstrate a transcriptional regulatory design algorithm that can boost expression in yeast and mammalian cell lines. The system consists of a simplified transcriptional architecture composed of a minimal core promoter and a synthetic upstream regulatory region (sURS) composed of up to three motifs selected from a list of 41 motifs conserved in the eukaryotic lineage. The sURS system was first characterized using an oligo-library containing 189,990 variants. We validate the resultant expression model using a set of 43 unseen sURS designs...

PURPOSE: To evaluate trends associated with email communication from potentially predatory publishers to faculty in ophthalmology. DESIGN: Cross sectional study METHODS: Ophthalmologists (n=14) from various subspecialties and institutions were recruited to participate. Participants identified unsolicited emails they had received originating from publishers in May 2021. Information collected included details on email contents and publisher organizations. Trends in communications from predatory publishers were evaluated...

RNA modification plays a crucial role in cellular regulation. However, traditional high-throughput sequencing methods for elucidating their functional mechanisms are time-consuming and labor-intensive, despite extensive research. Moreover, existing methods often limit their focus to specific species, neglecting the simultaneous exploration of RNA modifications across diverse species. Therefore, a versatile computational approach is necessary for interpretable analysis of RNA modifications across species. A multi-scale biological language-based deep learning model is proposed for interpretable, sequential-level prediction of diverse RNA modifications...

Solid waste management in low- and middle-income countries like India faces significant challenges due to the increasing waste generation that surpasses the current capacity. Therefore, the informal waste sector (IWS) is more vital than ever in handling consumer waste alongside municipal solid waste management (SWM) systems. However, the integration of the IWS into formal waste management systems remains unresolved due to adverse social and economic conditions. This study focuses on identifying the root causes that hinder the integration of the IWS in India's waste management system, using the city of Chennai as a case study...

BACKGROUND: Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta's biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses...

Small non-coding RNAs can be secreted through a variety of mechanisms, including exosomal sorting, in small extracellular vesicles, and within lipoprotein complexes. However, the mechanisms that govern their sorting and secretion are not well understood. Here, we present ExoGRU, a machine learning model that predicts small RNA secretion probabilities from primary RNA sequences. We experimentally validated the performance of this model through ExoGRU-guided mutagenesis and synthetic RNA sequence analysis. Additionally, we used ExoGRU to reveal cis and trans factors that underlie small RNA secretion, including known and novel RNA-binding proteins (RBPs), e...

SUMMARY: Shu is a visualization tool that integrates diverse data types into a metabolic map, with a focus on supporting multiple conditions and visualizing distributions. The goal is to provide a unified platform for handling the growing volume of multi-omics data, leveraging the metabolic maps developed by the metabolic modeling community. Additionally, shu offers a streamlined python API, based on the Grammar of Graphics, for easy integration with data pipelines. AVAILABILITY AND IMPLEMENTATION: Freely available at https://github...

Australian Mandarin-English bilingual preschoolers must acquire linguistic structures that occur only in the community language (e.g., English inflectional grammar). This study investigated how they acquire such structures and any relationship between linguistic knowledge and language experience on their performance. Twenty 4-6-year-olds showed known monolingual acquisition patterns with good performance for producing the progressive, developing ability for plurals, but only emerging ability for past and present tense...

In higher eukaryotes, the nucleolus harbors at least three sub-phases that facilitate multiple functionalities including ribosome biogenesis. The three prominent coexisting sub-phases are the fibrillar center (FC), the dense fibrillar component (DFC), and the granular component (GC). Here, we review recent efforts in profiling sub-phase compositions that shed light on the types of physicochemical properties that emerge from compositional biases and territorial organization of specific types of macromolecules...

Interpreting single-cell chromatin accessibility data is crucial for understanding intercellular heterogeneity regulation. Despite the progress in computational methods for analyzing this data, there is still a lack of a comprehensive analytical framework and a user-friendly online analysis tool. To fill this gap, we developed a pre-trained deep learning-based framework, single-cell auto-correlation transformers (scAuto), to overcome the challenge. Following DNABERT's methodology of pre-training and fine-tuning, scAuto learns a general understanding of DNA sequence's grammar by being pre-trained on unlabeled human genome via self-supervision; it is then transferred to the single-cell chromatin accessibility analysis task of scATAC-seq data for supervised fine-tuning...

The starting-small effect is a cognitive advantage in language acquisition when learners begin by generalizing on regularities from structurally simple and shorter tokens in a skewed input distribution. Our study explored this effect as a potential explanation for the biased learning of opaque and transparent vowel harmony. In opaque vowel harmony, feature agreement occurs strictly between adjacent vowels, and an intervening "neutral vowel" blocks long-distance vowel harmony. Thus, opaque vowel harmony could be acquired even if learners start with structurally simpler and more frequent disyllabic tokens...

The identification of neonicotinoid insecticides bearing novel scaffolds is of great importance for pesticide discovery. Here, artificial intelligence-based tools and virtual screening strategy were integrated to discover potential leads of neonicotinoid insecticides. A deep generative model was successfully constructed using a recurrent neural network combined with transfer learning. The model evaluation showed that the pretrained model could accurately grasp the SMILES grammar of drug-like molecules and generate potential neonicotinoid compounds after transfer learning...

PURPOSE: We examined the properties of mean length of utterance (MLU) in Czech, a morphologically complex Slavic language. We compared the scores of MLU calculated in different units and based on different sample lengths and assessed its validity against another transcript and test-based measures. METHOD: One hundred nine children were recorded during free-play at 2;6 and 3;11 (years;months). We compared MLU in syllables, morphemes, and words (MLUw ) in transcripts of different lengths (50, 75, 100, and all available utterances)...

How do children learn to connect expressions (e.g., "that red apple") to the real-world objects they refer to? The dominant view in developmental psychology is that children rely on descriptive information, "red" and "apple." In contrast, linguistic theories of the adult language attribute primacy to grammatical elements: words such as "that" or "another" first establish the status of potential referents within the discourse context (old or new) before descriptions can factor in. These theories predict that reference can succeed even when the description does not match the referent...

A molecular grammar governing low-complexity prion-like domains phase separation (PS) has been proposed based on mutagenesis experiments that identified tyrosine and arginine as primary drivers of phase separation via aromatic-aromatic and aromatic-arginine interactions. Here we show that additional residues make direct favorable contacts that contribute to phase separation, highlighting the need to account for these contributions in PS theories and models. We find that tyrosine and arginine make important contacts beyond only tyrosine-tyrosine and tyrosine-arginine, including arginine-arginine contacts...