Rapid automatized naming

Dyslexia is a neurodevelopmental disorder that presents a deficit in accuracy and/or fluency while reading or spelling that is not expected given the level of cognitive functioning. Research indicates brain structural changes mainly in the left hemisphere, comprising arcuate fasciculus (AF) and corona radiata (CR). The purpose of this systematic review is to better understand the possible methods for analyzing Diffusion Tensor Imaging (DTI) data while accounting for the characteristics of dyslexia in the last decade of the literature...

There is a growing interest in milk oligosaccharides (MOs) because of their numerous benefits for newborns' and long-term health. A large number of MO structures have been identified in mammalian milk. Mostly described in human milk, the oligosaccharide richness, although less broad, has also been reported for a wide range of mammalian species. The structure of MOs is particularly difficult to report as it results from the combination of 5 monosaccharides linked by various glycosidic bonds forming structurally diverse and complex matrices of linear and branched oligosaccharides...

PURPOSE: The purpose of the present study was to investigate the relationship between speechreading ability, phonological skills, and word reading ability in typically developing children. METHOD: Sixty-six typically developing children (6-7 years old) completed tasks measuring word reading, speechreading (words, sentences, and short stories), alliteration awareness, rhyme awareness, nonword reading, and rapid automatized naming (RAN). RESULTS: Speechreading ability was significantly correlated with rhyme and alliteration awareness, phonological error rate, nonword reading, and reading ability (medium effect sizes) and RAN (small effect size)...

OBJECTIVES: This study aimed to identify the effectiveness of treatment programs for children with reading (RD) or mathematics disorders (MD). Structured treatment programs were developed to improve phonological awareness and number sense among children and adolescents with RD or MD, respectively, and the effectiveness of the learning disorder treatment programs were evaluated. METHODS: We used standardized, objective diagnostic, and evaluation tools not only to recruit participants with RD, MD, or comorbid attention deficit and hyperactivity disorder, but also to assess the effectiveness of the treatments regarding both improved core neurocognitive deficits of RD or MD and academic achievement...

BACKGROUND: Language and the ability to communicate effectively are key factors in mental health and well-being. Despite this critical importance, research on language is limited by the lack of a scalable phenotyping toolkit. METHODS: Here, we describe and showcase Lingo - a flexible online battery of language and nonverbal reasoning skills based on seven widely used tasks (COWAT, picture narration, vocal rhythm entrainment, rapid automatized naming, following directions, sentence repetition, and nonverbal reasoning)...

The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quite challenging due to the complexity of their names and the frequent use of abbreviations. In this paper, we propose BioBBC, a deep learning (DL) model that utilizes multi-feature embeddings and is constructed based on the BERT-BiLSTM-CRF to address the BioNER task. BioBBC consists of three main layers; an embedding layer, a Long Short-Term Memory (Bi-LSTM) layer, and a Conditional Random Fields (CRF) layer...

The purpose of the current study was to examine the combined effect of word length and lexical frequency in a lexical decision task in second- and fifth-grade children with varying language skills. The participants, 47 second graders and 55 fifth graders, performed a lexical decision task in which word length and lexical frequency were manipulated orthogonally so that 32 words were short and frequent (e.g., fleur [flower]), 32 words were short and rare (e.g., navet [turnip]), 32 words were long and frequent (e...

The present study investigated how phonological awareness and rapid automatized naming (hereafter, RAN), simultaneously contributed to Chinese reading and arithmetic fluency. Specifically, we proposed a new hypothesized mechanism that processing speed would mediate the relations of RAN with Chinese reading and arithmetic fluency. One hundred and forty-five Chinese children at the fifth grade were administered with a battery of measures, including three phonological processing measures, character reading, and whole number computation, as well as nonverbal IQ, and vocabulary knowledge...

Action video-games (AVGs) could improve reading efficiency, enhancing not only visual attention but also phonological processing. Here we tested the AVG effects upon three consolidated language-based predictors of reading development in a sample of 79 pre-readers at-risk and 41 non-at-risk for developmental dyslexia. At-risk children were impaired in either phonemic awareness (i.e., phoneme discrimination task), phonological working memory (i.e., pseudoword repetition task) or rapid automatized naming (i.e...

In the field of drug discovery and pharmacology research, precise and rapid prediction of drug-target binding affinity (DTA) and drug-drug interaction (DDI) are essential for drug efficacy and safety. However, pharmacological data are often distributed across different institutions. Moreover, due to concerns regarding data privacy and intellectual property, the sharing of pharmacological data is often restricted. It is difficult for institutions to achieve the desired performance by solely utilizing their data...

BACKGROUND: This study explored the effects of attention shifting on Chinese children's word reading. OBJECTIVE: The sample consisted of 87 fourth-grade children from Shaoxing City, China. METHODS: The students completed measures of the attention shifting task, reading accuracy test, reading fluency test, and rapid automatized naming test. RESULTS: The results showed that reading fluency was significantly correlated with attention shifting scores, specifically with tag1 and tag6 (ps < 0...

There has been much debate on whether color categories affect how we perceive color. Recent theories have put emphasis on the role of top-down influence on color perception that the original continuous color space in the visual cortex may be transformed into categorical encoding due to top-down modulation. To test the influence of color categories on color perception, we adopted an RSVP paradigm, where color stimuli were presented at a fast speed of 100 ms per stimulus and were forward and backward masked by the preceding and following stimuli...

As a key glycolytic metabolite, lactate has a central role in diverse physiological and pathological processes. However, comprehensive multiscale analysis of lactate metabolic dynamics in vitro and in vivo has remained an unsolved problem until now owing to the lack of a high-performance tool. We recently developed a series of genetically encoded fluorescent sensors for lactate, named FiLa, which illuminate lactate metabolism in cells, subcellular organelles, animals, and human serum and urine. In this protocol, we first describe the FiLa sensor-based strategies for real-time subcellular bioenergetic flux analysis by profiling the lactate metabolic response to different nutritional and pharmacological conditions, which provides a systematic-level view of cellular metabolic function at the subcellular scale for the first time...

An automatic, rapid and non-targeted detection method for multi-pesticides in plant-derived foods was developed by gas chromatography-mass spectrometry and chemometrics. In this method, a novel algorithm named moving window iterative target transformation factor analysis was proposed. Although there are challenges of peak overlapping and background interference, the retention time and corrected mass spectra of unknown pesticides can be automatically obtained through iteration calculation in the 'moving window' with reference to the pesticide mass spectral library...

In recent years, X-band phase array dual polarization weather radar technology has matured. The cooperative networking data from X-band phase array dual polarization weather radar have many advantages compared with traditional methods, namely, high spatial and temporal resolution (approximately 70 seconds in one scan, 30 m in radial distance resolution), wide coverages that can compensate for the observation blind spots, and data fusion technology that is used in the observation overlap area to ensure that the observed precipitation data have spatial continuity...

With the rapid growth and widespread application of electronic health records (EHRs), similar patient retrieval has become an important task for downstream clinical decision support such as diagnostic reference, treatment planning, etc. However, the high dimensionality, large volume, and heterogeneity of EHRs pose challenges to the efficient and accurate retrieval of patients with similar medical conditions to the current case. Several previous studies have attempted to alleviate these issues by using hash coding techniques, improving retrieval efficiency but merely exploring underlying characteristics among instances to preserve retrieval accuracy...

Nurses, often considered the backbone of global health services, are disproportionately vulnerable to COVID-19 due to their front-line roles. They conduct essential patient tests, including blood pressure, temperature, and complete blood counts. The pandemic-induced loss of nursing staff has resulted in critical shortages. To address this, robotic solutions offer promising avenues. To solve this problem, we developed an ensemble deep learning (DL) model that uses seven different models to detect patients. Detected images are then used as input for the soft robot, which performs basic assessment tests...

INTRODUCTION: There are some inherent problems with the use of observation methods in the ergonomic assessment of working posture, namely the stability and precision of the measurements. This study aims to use a machine learning (ML) approach to avoid the subjectivity bias of observational methods in ergonomic assessments and further identify risk patterns for work-related musculoskeletal disorders (WMSDs) among sewing machine operators. METHODS: We proposed a decision tree analysis scheme for ergonomic assessment in working postures (DTAS-EAWP)...

Emergent literacy skills are vital for children's reading and writing development. While touchscreen devices have been linked to enhanced emergent literacy in developed countries, their impact in low- and middle-income countries (LMICs), with limited access to quality apps, is underexplored. Thailand, classified as an upper-middle-income country, presents a unique context with its specific challenges in educational technology, which have not been extensively studied. This study examined the relationship between touchscreen device usage and emergent literacy development in Thai preschool children...

Drug repurposing (DR) based on knowledge graphs (KGs) is challenging, which uses knowledge graph reasoning models to predict new therapeutic pathways for existing drugs. With the rapid development of computing technology and the growing availability of validated biomedical data, various knowledge graph-based methods have been widely used to analyze and process complex and novel data to discover new indications for given drugs. However, existing methods need to be improved in extracting semantic information from contextual triples of biomedical entities...