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The article raises the issue regarding the possibilities of using musical noise instruments in the process of mass art education. The relevance of the topic is predetermined by these facts: a) insufficient attention of representatives of musical education to the use of musical noise instruments; b) the growing importance of this type of instrument in academic and popular music; c) increasing interest of modern youth in instrumental music making; b) the low degree of development of the theory and methodology of playing musical noise instruments. The goal of the work is to consider the phenomenon of musical noise instruments from the education viewpoint as well as to determine their pedagogical potential. The content of the article. Based on the analysis of special literature, the classification concept “musical noise instruments” has been specified. Their mechanical, acoustic, plastic, cultural and educational properties have been characterised. The features of musical noise instruments that determine the possibility and expediency of their use in the practice of musical education have been determined. The results of the study. It is proposed to understand “musical noise instruments” as acoustic mechanical devices that allow creating more or less plastic broadband and colour noises. It has been established that musical noise instruments have an important educational value, which can be explained by a number of factors: a) these instruments belong to the oldest sound generation devices in the history of mankind, familiarity with them serves to expand cultural knowledge and gnostic motivation for art education; b) mastery of them opens the way for developing traditions of the native national art and the wealth of other national cultures; c) musical noise instruments primarily serve to reproduce the musical rhythm in all its expressiveness and structural complexity; involvement of schoolchildren in playing music with musical noise instruments promotes the development of their musical and rhythmic abilities, perceptions and skills; d) since the role of musical noise instruments today has significantly increased in the practice of classical, jazz and popular music, the acquaintance of students with these instruments should be considered as one of the ways to master the poetics and artistic language of modern music in its various style and genre manifestations; e) musical noise instruments have a high potential in attracting preschool children and primary school pupils to active ensemble music playing. Modern pedagogy of higher education should study and develop the didactic capabilities of musical noise instruments in training future teachers of musical art: the formation of their sense of rhythm, texture, architectonics, timbre palette, intonational expressiveness; arranging skills, expanding musical and cultural experience. These tasks require an appropriate technique, the development of which is the author’s further task.

Previous neuroimaging studies on arithmetic development have mainly focused on functional activation or functional connectivity between brain regions. It remains largely unknown how brain structures support arithmetic development. The present study investigated whether early gray matter structural covariance contributes to later gain in arithmetic ability in children. We used a public longitudinal sample comprising 63 typically developing children. The participants received structural magnetic resonance imaging scanning when they were 11 years old and were tested with a multiplication task at 11 years old (time 1) and 13 years old (time 2), respectively. Mean gray matter volumes were extracted from eight brain regions of interest to anchor salience network (SN), frontal-parietal network (FPN), motor network (MN), and default mode network (DMN) at time 1. We found that longitudinal gain in arithmetic ability was associated with stronger structural covariance of the SN seed with frontal and parietal regions and stronger structural covariance of the FPN seed with insula, but weaker structural covariance of the FPN seed with motor and temporal regions, weaker structural covariance of the MN seed with frontal and motor regions, and weaker structural covariance of the DMN seed with temporal region. However, we did not detect correlation between longitudinal gain in arithmetic ability and behavioral measure or regional gray matter volume at time 1. Our study provides novel evidence for a specific contribution of gray matter structural covariance to longitudinal gain in arithmetic ability in childhood. [ABSTRACT FROM AUTHOR]

Lipiodol chemotherapeutic emulsions remain one of the main choices for the treatment of unresectable hepatocellular carcinoma (HCC) via transarterial chemoembolization (TACE). However, the limited stability of Lipiodol chemotherapeutic emulsions would lead to rapid drug diffusion, which would reduce the therapeutic benefit and cause systemic toxicity of administrated chemotherapeutics. Therefore, the development of enhanced Lipiodol-based formulations is of great significance to enable effective and safe TACE treatment. Herein, a stable water-in-oil Lipiodol Pickering emulsion (LPE) stabilized by pH-dissociable calcium carbonate nanoparticles and hemin is prepared and utilized for efficient encapsulation of lipoxygenase (LOX). The obtained LOX-loaded CaCO3&hemin-stabilized LPE (LHCa-LPE) showing greatly improved emulsion stability could work as a pH-responsive and self-fueling microreactor to convert polyunsaturated fatty acids (PUFAs), a main component of Lipiodol, to cytotoxic lipid radicals through the cascading catalytic reaction driven by LOX and hemin, thus inducing ferroptosis of cancer cells. As a result, such LHCa-LPE upon transcatheter embolization can effectively suppress the progression of orthotopic N1S1 HCC in rats. This study highlights a concise strategy to prepare pH-responsive and stable LPE-based self-fueling microreactors, which could serve as bifunctional embolic and ferroptosis-inducing agents to enable proof-of-concept transarterial ferro-embolization therapy of HCC. [ABSTRACT FROM AUTHOR]

Accurate and efficient COVID-19 diagnosis is crucial in clinical settings. However, the limited availability of labeled data poses a challenge for traditional machine learning algorithms. To address this issue, we propose Turning Point (TP), a few-shot learning (FSL) approach that leverages high-level turning point mappings to build sophisticated representations across previously labeled data. Unlike existing FSL models, TP learns using quasi-configured topological spaces and efficiently combines the outputs of diverse TP learners. We evaluated TPFSL using three COVID-19 datasets and compared it with seven different benchmarks. Results show that TPFSL outperformed the top-performing benchmark models in both one-shot and five-shot tasks, with an average improvement of 4.50% and 4.43%, respectively. Additionally, TPFSL significantly outperformed the ProtoNet benchmark by 12.966% and 11.033% in one-shot and five-shot classification problems across all datasets. Ablation experiments were also conducted to analyze the impact of variables such as TP density, network topology, distance measure, and TP placement. Overall, TPFSL has the potential to improve the accuracy and speed of diagnoses for COVID-19 in clinical settings and can be a valuable tool for medical professionals. [ABSTRACT FROM AUTHOR]