Search Results (15)

Bilingual children commonly mix languages. Their language mixing generally adheres to grammatical constraints, yet it may impose processing and production costs. This study examined how 4-to-7-year-old English-, Polish-, and Turkish-Dutch bilingual children processed and repeated mixed-language sentences. It aimed to (a) determine whether they struggle with mixed-language sentences, (b) study whether shared word order in either the main or subordinate clause facilitates repetition, (c) compare the effects of different types of mixing, i.e., insertion and alternation, and (d) link error rates to daily mixing experience. Fifty-seven children participated in a mixed sentence repetition task. Mixed Dutch sentences with embedded elements from other languages in the task enable the examination of the role of clause and mixing type across four types of sentences: (1) main clause insertion, (2) subordinate clause insertion, (3) main clause alternation, and (4) subordinate clause alternation. In addition, monolingual Dutch sentences with main and subordinate clauses allow investigation of the effects of processing mixed sentences. The results of the generalized linear mixed-effects models with error rates as the outcome variable suggest that mixing may play a limited role. We also found no evidence of a relation between task performance and daily mixing experience. These results provide no support for processing and production costs associated with language mixing. We discuss these results in light of theories on language mixing, previous research and methodological considerations. Full article

Infected URLs are always regarded as a serious threat to cybersecurity, serving as pathways to phishing, maliciousness, and other offenses. Although transformer-based models have demonstrated good performance in malicious URL detection, their high computational cost and latency make them impractical for deployment in real-time or resource-constrained systems. Allocated on the basis of knowledge distillation (KD), lightweight models tend to be efficient but are commonly not sufficiently discriminative to distinguish between malicious and benign URLs with non-cataclysmic lexical overlaps, particularly when dealing with an imbalanced dataset. In order to address these issues, we propose Contra-KD, a lightweight transformer model that incorporates contrastive learning (CL) and KD. This proposed framework imposes structured embedding matching, allowing the student model to learn more meaningful and generalized depictions. Contra-KD uses a compact 6-layer student transformer architecture based on ELECTRA to scale parameters up and can achieve more than 90% computational fidelity with a high accuracy. In this scheme, CL improves the feature of discrimination by semantically clustering similar URLs and separating different URLs. This tendency serves to limit confusion, especially when a common lexical trait is held between two words and/or in the presence of adversarial obfuscation. Through a large-scale publicly available Kaggle dataset of 651,191 URLs in imbalanced scenarios, the proposed Contra-KD can achieve 99.05% accuracy, 99.96% ROC-AUC, and 98.18% MCC which are superior to their counterparts including lightweight models and transformer-based ones. To summarize, Contra-KD proposes an efficient transformer architecture that is both small and effective in computation while delivering stable detection performance. Full article

Natural language processing is the technology used to interact with computers using human languages. An overlapping technology is Information Retrieval (IR), in which a user searches for the demanded or required documents from among a number of documents that are already stored. The required document is retrieved according to the relevance of the query of the user, and the results are presented in descending order. Many of the languages have their own IR systems, whereas a dedicated IR system for Sindhi still needs attention. Various approaches to effective information retrieval have been proposed. As Sindhi is an old language with a rich history and literature, it needs IR. For the development of Sindhi IR, a document database is required so that the documents can be retrieved accordingly. Many Sindhi documents were identified and collected from various sources, such as books, journal, magazines, and newspapers. These documents were identified as having potential for use in indexing and other forms of processing. Probabilistic modeling and pattern discovery were used to find patterns and for effective retrieval and relevancy. The results for Sindhi Information Retrieval systems are promising and presented more than 90% relevancy. The time elapsed was recorded as ranging from 0.2 to 4.8 s for a single word and 4.6 s with a Sindhi sentence, with the same starting time of 0.2 s. The IR system for Sindhi can be fine-tuned and utilized for other languages with the same characteristics, which adopt Arabic script. Full article

Medical laboratories are perhaps the largest measurement industry in the world. The metrology terminology is relevant for effective and efficient communication, particularly where metrology activities are carried out by operators with different metrology skills. The World Association of Societies of Pathology and Laboratory Medicine (WASPaLM) and SIPMeL have had some opportunities to propose changes to the documents in preparation for the Clinical and Laboratory Standards Institute (CLSI) and the ISO/TC 212 in order to harmonize the terminology with the Metrology Vocabulary (VIM) of the Joint Committee for Guides in Metrology (JCGM). Many proposals have been accepted. Here, we summarize some particularly critical points for metrological terms. The main terms discussed are the following: measuring, measuring range, examination, pre-examination, post-examination, manufacturer, measuring instrument, quantitative, qualitative, semi-quantitative, processing, measurement error, maximum permissible error of measurement, total error of measurement, monitoring, variability, performance, reliability, influence, interference, selectivity, sensitivity, detection limit, reliability, comparability, compatibility, control material. Despite all the efforts to coordinate terminologies, it is inevitable that overlapping and inconsistent terminologies will continue to be used because documents and policies are produced in different contexts. In some ISO/TC 212 and CLSI documents, the phenomenon of magnetic attraction toward common words (such as “analysis” and derivatives), without any consideration of the true metrological meaning, is noted. The ISO/TC 212 and CLSI working groups show, alongside moments of openness, phenomena of true self-referential conservatism. Full article

In clinical practice, heart failure (HF) and osteoporosis (OP) are commonly paired conditions. This association is particularly relevant in patients over the age of 50, among whom its prevalence increases dramatically with every decade of life. This can be especially impactful since patient prognosis when facing both conditions is poorer than that of each disease alone. Clinical studies suggest that prior fractures increase the risk for heart failure hospitalization and, conversely, an episode of heart failure increases the risk of subsequent fractures. In other words, the relationship between osteoporosis and heart failure seems to be two-way, meaning that each condition may influence or contribute to the development of the other. However, the details of the pathophysiological relationship between HF and OP have yet to be revealed. The two conditions share multiple pathological mechanisms that seem to be intertwined. Patients affected by OP are more prone to develop HF because of vitamin D deficiency, elevation of parathyroid hormone (PTH) plasma levels, and increased Fibroblast Growth Factor 23 (FGF-23) activity. On the other hand, HF patients are more prone to develop OP and pathological fractures because of low vitamin D level, high PTH, chronic renal failure, alteration of renin–angiotensin–aldosterone system, reduced testosterone level, and metabolic effects derived from commonly used medications. Considering the increasingly aging worldwide population, clinicians can expect to see more often an overlap between these two conditions. Thus, it becomes crucial to recognize how HF and OP mutually influence the patient’s clinical condition. Clinicians attending these patients should utilize an integrated approach and, in order to improve prognosis, aim for early diagnosis and treatment initiation. The aim of this paper is to perform a review of the common pathophysiological mechanisms of OP and HF and identify potentially new treatment targets. Full article

This study examines whether Differential Object Marking (DOM) realization and word order in relative clauses (RCs) in Spanish affect processing and interpretation among monolinguals and highly proficient Catalan–Spanish bilinguals. RCs are parallel in Catalan and Spanish, but DOM is much more restricted in Catalan than in Spanish, and, interestingly, the distinction between subject and object RCs relies mainly on the presence/absence of DOM. To examine DOM optionality, we concentrate on the top portion of the animacy scale and test the human/non-human contrast. Exploring these two populations allows us to test whether they resort to different strategies for the following three reasons: (1) bilingualism places an increased burden on memory processes); (2) the partial overlap between both DOM systems might lead to the influence from Catalan into Spanish); and (3) optionality has been proposed to characterize bilingual grammars). Findings from a word-by-word non-cumulative self-paced reading task showed that DOM modulates RC processing. With [+human] obligatorily marked objects, both monolinguals and bilinguals read subject RCs faster than object RCs, suggesting a strategy favoring subject RCs. However, monolinguals solved the interpretation early while processing but bilinguals, despite the more restricted DOM character of Catalan, are sensitive to DOM albeit displaying delayed spill-over effects. With [−human] optionally marked objects, bilinguals performed faster than monolinguals. We suggest that the uneven experience with DOM in Catalan, particularly with the non-standard variety that frequently displays DOM and that our bilinguals also speak in everyday conversations, facilitates bilinguals’ adaptation to the optional marking of non-human objects in Spanish, much in the same manner that they accommodate the presence or absence of DOM with both human and non-human objects in other native language. Full article

With the development of the Internet, vast amounts of text information are being generated constantly. Methods for extracting the valuable parts from this information have become an important research field. Relation extraction aims to identify entities and the relations between them from text, helping computers better understand textual information. Currently, the field of relation extraction faces various challenges, particularly in addressing the relation overlapping problem. The main difficulties are as follows: (1) Traditional methods of relation extraction have limitations and lack the ability to handle the relation overlapping problem, requiring a redesign. (2) Relation extraction models are easily disturbed by noise from words with weak relevance to the relation extraction task, leading to difficulties in correctly identifying entities and their relations. In this paper, we propose the Relation extraction method based on the Entity Attention network and Cascade binary Tagging framework (REACT). We decompose the relation extraction task into two subtasks: head entity identification and tail entity and relation identification. REACT first identifies the head entity and then identifies all possible tail entities that can be paired with the head entity, as well as all possible relations. With this architecture, the model can handle the relation overlapping problem. In order to reduce the interference of words in the text that are not related to the head entity or relation extraction task and improve the accuracy of identifying the tail entities and relations, we designed an entity attention network. To demonstrate the effectiveness of REACT, we construct a high-quality Chinese dataset and conduct a large number of experiments on this dataset. The experimental results fully confirm the effectiveness of REACT, showing its significant advantages in handling the relation overlapping problem compared to current other methods. Full article

This paper presents a new approach called EmbedHDP, which aims to enhance the evaluation models utilized for assessing sentence suggestions in nursing care record applications. The primary objective is to determine the alignment of the proposed evaluation metric with human evaluators who are caregivers. It is crucial due to the direct relevance of the provided provided to the health or condition of the elderly. The motivation for this proposal arises from challenges observed in previous models. Our analysis examines the mechanisms of current evaluation metrics such as BERTScore, cosine similarity, ROUGE, and BLEU to achieve reliable metrics evaluation. Several limitations were identified. In some cases, BERTScore encountered difficulties in effectively evaluating the nursing care record domain and consistently providing quality assessments of generated sentence suggestions above 60%. Cosine similarity is a widely used method, but it has limitations regarding word order. This can lead to potential misjudgments of semantic differences within similar word sets. Another technique, ROUGE, relies on lexical overlap but tends to ignore semantic accuracy. Additionally, while BLEU is helpful, it may not fully capture semantic coherence in its evaluations. After calculating the correlation coefficient, it was found that EmbedHDP is effective in evaluating nurse care records due to its ability to handle a variety of sentence structures and medical terminology, providing differentiated and contextually relevant assessments. Additionally, this research used a dataset comprising 320 pairs of sentences with correspondingly equivalent lengths. The results revealed that EmbedHDP outperformed other evaluation models, achieving a coefficient score of 61%, followed by cosine similarity, with a score of 59%, and BERTScore, with 58%. This shows the effectiveness of our proposed approach in improving the evaluation of sentence suggestions in nursing care record applications. Full article

Some poor readers show little or no progress in literacy interventions as their susceptibility to the concreteness and neighborhood effect is not accounted for during intervention. This study aims to develop a resource for poor readers by revising the Dolch list to account for the concreteness and neighborhood (orthographic, phonological and semantic) effect. Psycholinguistic techniques were employed to recategorize 220 Dolch list words according to concreteness via function and content word categories, and include the associated orthographic, phonological and semantic neighbors of each word into a new High Frequency List with Neighbors (HFLN). One-way analysis of variance (ANOVA), Bonferroni post hoc test and Levene’s test of variance homogeneity were carried out as measures of statistical significance and variability. The HFLN contains a total of 220 words with 1057 neighbors across five function and content word categories. Both measures of statistical significance and variability show that grade categories in the Dolch list contain greater mean concreteness values with overlapping similarities and higher variability. Conversely, the HFLN effectively delineates concreteness value clusters between categories with lower variability. The HFLN aids in targeted intervention of poor readers by presenting the available orthographic, phonological and semantic neighbors according to the descending order of concreteness. Full article

Early successes in controlling the COVID-19 pandemic have prevented Republic of Korea from implementing a prompt, large-scale vaccine rollout to the public. The influence of traditional media on public opinion remains critical and substantial in Republic of Korea, and there have been heated debates about vaccination in traditional media reports in Korea. Effective and efficient public health communication is integral in managing public health challenges. This study explored media reports on the COVID-19 vaccines during the pandemic in Republic of Korea. 12,399 media news reports from May 2020 to September 2021 were collected. An LDA topic model was applied in order to analyze and compare the topics drawn from each study phase using words from the unstructured text data. Although media reports from before the national vaccination implementation focused on the development and rollout of COVID-19 vaccines, diverse topics were reported without any overlap. After the vaccination rollout, the biggest concern was the side effects of the COVID-19 vaccine. In sum, Republic of Korea’s major media outlets reported on diverse topics rather than generating a common discourse about topics related to COVID-19 vaccination. Full article

In order to ensure the continuity of the DC-side inductor current, current source converter (CSC) needs to add overlap time between the drive signals, but the overlap time will introduce low order (mainly fifth and seventh) harmonics to the grid current, which seriously degrade the harmonic performance of grid current. At present, some research has been conducted to theoretically analyze and mitigate the overlap-time effect in CSC, including the use of positive-slope sawtooth wave or negative-slope sawtooth wave as the carrier wave, turning on the switch early or delaying turning it off, and eliminating the deviation effect by compensation algorithms, etc. However, existing overlap-time suppression schemes takes the nearest three vector synthesis reference vector scheme as the object of study, in other words, the effect of overlap time on the non-nearest three-vector synthesis reference vector scheme has not been considered. To address these issues, this paper takes the non-nearest three-vector synthesis reference vector scheme as the object of study to analyze the effect of overlap time on the driving signal and establishes the quantitative relationship between the current harmonics introduced in the grid current and overlap time through Fourier decomposition. Then, the design process of the proposed improved space vector modulation by constructing freewheeling channels to replace the overlap time is presented in detail. Finally, simulation and experimental results verify that the overlap-time suppression effect of the proposed scheme is about 100%. Full article

The sustainable functioning of the transport system requires solving the problems of identifying and classifying road users in order to predict the likelihood of accidents and prevent abnormal or emergency situations. The emergence of unmanned vehicles on urban highways significantly increases the risks of such events. To improve road safety, intelligent transport systems, embedded computer vision systems, video surveillance systems, and photo radar systems are used. The main problem is the recognition and classification of objects and critical events in difficult weather conditions. For example, water drops, snow, dust, and dirt on camera lenses make images less accurate in object identification, license plate recognition, vehicle trajectory detection, etc. Part of the image is overlapped, distorted, or blurred. The article proposes a way to improve the accuracy of object identification by using the Canny operator to exclude the damaged areas of the image from consideration by capturing the clear parts of objects and ignoring the blurry ones. Only those parts of the image where this operator has detected the boundaries of the objects are subjected to further processing. To classify images by the remaining whole parts, we propose using a combined approach that includes the histogram-oriented gradient (HOG) method, a bag-of-visual-words (BoVW), and a back propagation neural network (BPNN). For the binary classification of the images of the damaged objects, this method showed a significant advantage over the classical method of convolutional neural networks (CNNs) (79 and 65% accuracies, respectively). The article also presents the results of a multiclass classification of the recognition objects on the basis of the damaged images, with an accuracy spread of 71 to 86%. Full article

BACKGROUND: Depression is the most prevalent affective syndrome in old age. Delirium is a common and serious adverse event in elderly patients and is associated with significant cognitive and functional decline and early institutionalisation. Both disorders have shared symptoms and signs. Recent studies suggest that depression is an independent risk factor for delirium, and depression symptoms may also represent sequels of delirium. It is important to identify patients at risk of delirium, in order to apply preventive strategies and to address the consequences of incident delirium. In this narrative review we discuss the complex relationship between depression and delirium in old age. METHODS: A literature search was conducted using following databases: PsycINFO, Embase, PubMed, Google scolar, Web of science and AgeLine using key words “delirium”, “depression”, “overlap" and "risk factor”. MAIN FINDINGS: Delirium and depression are complex psychiatric syndromes that are common in old age and associated with poor outcomes. This study gives a general overview about the relationship between depression and delirium. Prior depression is not a rare finding in patients suffering from delirium, and depressive symptoms are frequently observed as sequel of delirium. If delirium occurs, differential diagnosis may be particularly challenging in people with depression. Studies suggest similar pathophysiology, such as disturbances in inflammatory and stress responses. Accurate detection of depression and delirium is a key target to achieve improvement of outcomes and to provide optimal healthcare. CONCLUSION: The literature suggests an inter-relationship between depression and delirium. Symptoms of depression may contribute an increased risk of delirium and delirium may be a predictor of depression. However, the relationships between the two conditions regarding common underlying pathomechanisms and clinical aspects remain imprecisely defined and requires more study. Full article

By chunking continuous streams of action into ordered, discrete, and meaningful units, event segmentation facilitates motor learning. While expertise in the observed repertoire reduces the frequency of event borders, generalization of this effect to unfamiliar genres of dance and among other sensorimotor experts (musicians, athletes) remains unknown, and was the first aim of this study. Due to significant overlap in visuomotor, language, and memory processing brain networks, the second aim of this study was to investigate whether visually priming expert motor schemas improves memory for words related to one’s expertise. A total of 112 participants in six groups (ballet, Bharatanatyam, and “other” dancers, athletes, musicians, and non-experts) segmented a ballet dance, a Bharatanatyam dance, and a non-dance control sequence. To test verbal memory, participants performed a retrieval-induced forgetting task between segmentation blocks. Dance, instrument, and sport word categories were included to probe the second study aim. Results of the event segmentation paradigm clarify that previously-established expert segmentation effects are specific to familiar genres of dance, and do not transfer between different types of experts or to non-dance sequences. Greater recall of dance category words among ballet and Bharatanatyam dancers provides novel evidence for improved verbal memory primed by activating familiar sensorimotor representations. Full article

An innovative design of a magnetic coupler for shaft speed amplification is proposed and verified by experiments. The structure of the proposed magnetic coupler is similar to an infinite-stage gearbox. In addition, the mathematical model of flux density is derived to look into the equation of adjustable gear ratio and effect of speed amplification. Moreover, two sets of experiments, namely verification of gear ratio and observation of stall phenomenon, are built up to examine the capabilities and drawbacks of the proposed variable-gear-ratio magnetic coupler. Three types of gear ratios are presented by theoretical analysis at first and then examined by experiments. The gear ratios for these three specific types between the input and output rotors are 4.75, 5.75 and 10.5, respectively. That is, the rotational speed of the output rotor can be precisely and realistically amplified. Besides, in order to reduce the torque inertia of the outer rotor, a ferrite bush is inserted to the inner side of the core rotor to decrease the flux density in the air gap. On the other hand, the overlapped depth of permanent magnets, which are attached onto the inner rotor and outer rotor, has to be appropriately chosen. The smaller the overlapped depth, the weaker is the magnetic attractive force in the air gap. As long as these two modifications (an inserted ferrite bush and the aforesaid overlapped depth) are validated, the torque inertia of the outer rotor can be significantly reduced. Accordingly, the required power to rotate the outer rotor can be greatly reduced if the overlapped depth is shortened. However, insufficient overlapped depth between the high-speed rotor and low-speed rotor will bring about a stall phenomenon caused by the magnetic attractive force between the high-speed rotor and the low-speed rotor being weaker than the start-up torque inertia. In other words, the reduced overlapped depth can also reduce the start-up torque inertia but stall phenomenon may easily occur. Full article