Popular Trend Research Articles

How effective is ketogenic diet in sleep disorders ?

IntroductionSleep disorders vary widely and its treatment are based on a combination of life style changes and pharmacological therapy adapted to the primer health issue. Ketogenic diet has shown not only its efficacy in different health conditions, but it is also becoming a popular health trend. Could the therapeutic spectrum of ketogenic diet cover sleep disturbances ?ObjectivesThe aim of our study is to evaluate the effect of ketogenic diet on sleep disordersMethodsTo identify relevant studies ,our literature review was based on the Pubmed interface and adapted for 2 databases : science direct and google scholar. We used the following key words ( ketogenic diet [meSH terms]) and (sleep disorders [meSH terms]).ResultsOur research revealed 14 articles published between 2012 and 2022. We selected 8 which corresponded to the purpose of our review. The ketogenic diet affects sleep hemostasis indirectly. In fact, this diet is associated with weight loss and therefore reduction of metabolic and cardiovascular complications disturbing sleep quality. From a neurobiological perspective, this regimen based on limited carbohydrates is associated with a low Tryptophan intake which is the precursor of melatonin. But on the other hand, Ketone bodies trigger adenosine activity which promotes melatonin liberation, the sleep inducing hormone.ConclusionsKetogenic diet modulates melatonin activity therefore affects sleep architecture. Meanwhile, Its impact on sleep disorders is still controversed due to the variation of its pathophysiological mechanisms.Disclosure of InterestNone Declared

DRGAT: Dual-relational graph attention networks for aspect-based sentiment classification

Aspect-based sentiment classification has become a popular topic in natural language processing. Exploiting dependency syntactic information with graph neural networks has recently become a popular trend. Despite their success, methods that rely heavily on a dependency tree face major challenges. This concerns the alignment of aspects and their word sentiments due to the richness of the language and the fact that a dependency tree might produce noisy signals from unrelated associations. This paper introduces a Dual-Relational Graph Attention Network (DRGAT) that fully exploits syntactic structural information and then the sentiment-aware context (e.g., phrase segmentation and hierarchical structure) of the constituent tree of a sentence. Additional constituency and dependency attention mechanisms provide comprehensive syntactic information across words, thereby enabling an accurate connection between aspect words and corresponding sentiment words. Considering that the original parsed constituency tree may have a large depth, this could lead to words being far apart increasing the computational overhead. The constituency tree of each sentence is dynamically reconstructed by determining the importance of each relational node. Extensive experimental results on six English datasets demonstrated that fully exploiting syntactic information can achieve excellent sentiment classification results.

Exploring the Unknown: Evaluating ChatGPT's Performance in Uncovering Novel Aspects of Plastic Surgery and Identifying Areas for Future Innovation

BackgroundArtificial intelligence (AI) has emerged as a powerful tool in various medical fields, including plastic surgery. This study aims to evaluate the performance of ChatGPT, an AI language model, in elucidating historical aspects of plastic surgery and identifying potential avenues for innovation.MethodsA comprehensive analysis of ChatGPT's responses to a diverse range of plastic surgery-related inquiries was performed. The quality of the AI-generated responses was assessed based on their relevance, accuracy, and novelty. Additionally, the study examined the AI's ability to recognize gaps in existing knowledge and propose innovative solutions. ChatGPT’s responses were analysed by specialist plastic surgeons with extensive research experience, and quantitatively analysed with a Likert scale.ResultsChatGPT demonstrated a high degree of proficiency in addressing a wide array of plastic surgery-related topics. The AI-generated responses were found to be relevant and accurate in most cases. However, it demonstrated convergent thinking and failed to generate genuinely novel ideas to revolutionize plastic surgery. Instead, it suggested currently popular trends that demonstrate great potential for further advancements. Some of the references presented were also erroneous as they cannot be validated against the existing literature.ConclusionAlthough ChatGPT requires major improvements, this study highlights its potential as an effective tool for uncovering novel aspects of plastic surgery and identifying areas for future innovation. By leveraging the capabilities of AI language models, plastic surgeons may drive advancements in the field. Further studies are needed to cautiously explore the integration of AI-driven insights into clinical practice and to evaluate their impact on patient outcomes.Level of Evidence VThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266

STRATEGI PENYAMPAIAN PESAN DAKWAH PADA MEDIA SOSIAL

The Da'wah message is the message that the da'i wants to convey to the mad'u which is an important element in da'wah activities. Various media can be used to carry out da'wah, such as Tik Tok. One of the platforms that is widely used by people today. One of them is Husain Basyaiban with the Tik Tok account @kadamsidik00, which discusses Islamic values ​​and da'wah messages packaged in a way that is easy to understand. This research uses qualitative research. Researchers used content analysis on the @kadamsidik00 account. These data are processed and analyzed to identify strategies for delivering da'wah messages and supporting and inhibiting factors that influence the effectiveness of the da'wah message strategies delivered. Based on the results of this research, it was found that the @kadamsidik00 account used various strategies in conveying da'wah messages on Tik Tok. One of them is the use of creative content that attracts attention, as well as the ability to follow popular trends on Tik Tok to maximize audience reach. Apart from that, interaction with followers through comments and responses is also an important part of this account's strategy. Researchers also found several significant supporting factors in the strategy of conveying da'wah messages on Tik Tok social media by the account @kadamsidik00. These factors include the ability to create creative and attention-grabbing content, adaptation to popular trends, active interaction with followers, and the popularity of accounts that can expand the reach of preaching messages. However, there are also inhibiting factors that need to be considered. Limits on the duration of content on Tik Tok, competition with other viral content, and the risk of the da'wah message being distorted can become obstacles in conveying the da'wah message effectively. Apart from that, the importance of understanding the target audience more precisely and the risk of exposure to negative content also needs to be considered.

Anti-corruption Policy Analysis: Indonesian Open Government Study

The central role of the Indonesian government in campaigning for open government is not in line with the findings of corruption cases in Indonesia. This research aims to analyze anti-corruption open government bibliometrics and the content of Indonesia’s open government anti-corruption policies. This research uses a qualitative approach with bibliometric analysis and content analysis methods. This study analyzes 200 papers on the Google Scholar database published in the 2018–2022 period and analyzes Indonesia’s open government anti-corruption policies. This research found 4587 citations, h-index 37, g-index 57, 172 keywords, 22 clusters, 2531 total link strengths, and 784 occurrences in open government anti-corruption papers. Anticorruption, data disclosure, open data, open government, e-government, information disclosure, transparency, open government data, public procurement, and beneficial ownership are the most popular open government anti-corruption trends. In the same time period, the Indonesian government established 10 anti-corruption policies covering public procurement, beneficial ownership, and elections. This research concludes that although the Indonesian government’s corruption index is unsatisfactory, anticorruption policies in Indonesia are in line with global anti-corruption trends, especially in several popular policies such as open data, transparency, information disclosure, public procurement, and beneficial ownership.
 Keywords: anti-corruption, open government Indonesia, bibliometric analysis, content analysis

Content Analysis of STEM-Oriented Studies in Science Education: 2017-2021

Recently, the number of studies oriented to multidisciplinary science education is becoming more widespread with the increasing prevalence of 21 century-based applications. It is necessary to determine the subjects that are focused on educational research and the subjects that are studied frequently or rarely in order to draw a framework. Identifying science, technology, engineering, and mathematic (STEM) -oriented studies in science education with systematic content analysis accelerates researchers working in this field and gives them clarity about the subjects, samples, and a variety of variables. Therefore, the aim of this study is to examine STEM-oriented studies in science education between 2017 and 2021 with systematic content analysis in terms of different variables in Turkey. The study was conducted according to certain criteria. Scopus, Web of Science, and Google Scholar databases and indexes were examined. the number of publications made in Turkish is greater than the number of publications in English. One of the striking findings in the data obtained is that the number of publications with two authors is the highest compared with the distribution of the number of other authors. The journal that has published the most articles is Science Activities-Projects and Curriculum Ideas. The most used sample is composed of secondary school students, and the most preferred range as the sample type is between 11 and 30. There is an almost equal ratio between the research methods (quantitative and qualitative) used in the studies. It is seen that the tools classified as alternative evaluations are used the most in the studies, whereas concept maps are the least used data collection tool. It is thought that the study will guide researchers who will conduct STEM-oriented studies in science education and will help with popular trend topics that have been widely discussed recently in Turkey.

Wide Field of View Under-Panel Optical Lens Design for Fingerprint Recognition of Smartphone.

Fingerprint recognition is a widely used biometric authentication method in LED-backlight smartphones. Due to the increasing demand for full-screen smartphones, under-display fingerprint recognition has become a popular trend. In this paper, we propose a design of an optical fingerprint recognition lens for under-display smartphones. The lens is composed of three plastic aspheric lenses, with an effective focal length (EFL) of 0.61 mm, a field of view (FOV) of 126°, and a total track length (TTL) of 2.54 mm. The image quality of the lens meets the target specifications, with MTF over 80% in the center FOV and over 70% in the 0.7 FOV, distortion less than 8% at an image height of 1.0 mm, and relative illumination (RI) greater than 25% at an image height of 1.0 mm. The lens also meets the current industry standards in terms of tolerance sensitivity and Monte Carlo analysis.

Public interest trends for COVID-19 and pandemic trajectory: A time-series analysis of US state-level data.

Google Trends provides spatiotemporal data for user-specific terms scaled from less than 1 (lowest relative popularity) to 100 (highest relative popularity) as a proxy for the public interest. Here we use US state-level data for COVID-19 to examine popularity trends during the pandemic evolution. We used "coronavirus" and "covid" search terms and set the period up from January 1st, 2020, to November 12, 2022. We measured the agreement on web rankings between states using the nonparametric Kendall's W (0 for no concordance to 1 for perfect agreement). We compiled state-level weekly data on COVID-19 incidence and mortality and scaled state curves from 0 to 100 through a min-max normalization process. We used a dynamic time-warping algorithm to calculate similarities between the popularity, mortality, and incidence of COVID-19. The methodology is a pattern recognition process between time series by distance optimization. The similarity was mapped from 0 to 1, with 1 indicating perfect similarity and 0 indicating no similarity. The peak in popularity was in March 2020, succeeded by a decline and a prolonged period of fluctuation around 20%. Public interest rose briefly at the end of 2021, to fall to a low activity of around 10%. This pattern was remarkably consistent across states (Kendal's W 0.94, p < 0.001). Web search trends were an impression of contagion growth: Overall, popularity-mortality trajectories yielded higher similarity indices (median 0.78; interquartile range 0.75-0.82) compared to popularity-incidence trajectories (median 0.74; interquartile range 0.72-0.76, Wilcoxon's exact p<0.001). The popularity-mortality trajectories had a very strong similarity (>0.80) in 19/51 (37%) regions, as opposed to only 4/51 (8%) for popularity-incidence trajectories. State-level data show a fading public concern about COVID-19, and web-search popularity patterns may reflect the COVID-19 trajectory in terms of cases and mortality.

CSR Motivations in Voluntary Non-Financial Disclosures: The Preparers’ Voice

CSR reports are communication tools, appropriate for informing stakeholders of the CSR practices conducted by organizations. This article aims to explore the reasons why complex organizations have adopted on purpose the CSR report to meet their needs and to discover why they have chosen to adopt the integrated report as an alternative to the sustainability report. This study is based on an explanatory case study of two healthcare organizations that have exactly implemented Integrated Reporting (IR), instead of Sustainability Reporting. The research method used is the field study. This work points out how organizations create and use CSR reports, even if they are not mandatory. If the IR looks like a &amp;ldquo;managerial innovation&amp;rdquo;, there is always a risk that the diffusion of these tools could simply be the latest popular trend, followed by internal or external proponents, rather than a rational decision-making process. The study has implications for the policymakers, the organizations, and their integrated report. The policymakers can understand if this tool can be useful for the organizations, to promote internal CSR. The study contributes to literature about the willingness to publish CSR reports, as an expression of the internal and external factors that influence voluntary reporting choices.

Deep Learning Based Underwater Acoustic Target Recognition: Introduce a Recent Temporal 2D Modeling Method.

In recent years, the application of deep learning models for underwater target recognition has become a popular trend. Most of these are pure 1D models used for processing time-domain signals or pure 2D models used for processing time-frequency spectra. In this paper, a recent temporal 2D modeling method is introduced into the construction of ship radiation noise classification models, combining 1D and 2D. This method is based on the periodic characteristics of time-domain signals, shaping them into 2D signals and discovering long-term correlations between sampling points through 2D convolution to compensate for the limitations of 1D convolution. Integrating this method with the current state-of-the-art model structure and using samples from the Deepship database for network training and testing, it was found that this method could further improve the accuracy (0.9%) and reduce the parameter count (30%), providing a new option for model construction and optimization. Meanwhile, the effectiveness of training models using time-domain signals or time-frequency representations has been compared, finding that the model based on time-domain signals is more sensitive and has a smaller storage footprint (reduced to 30%), whereas the model based on time-frequency representation can achieve higher accuracy (1-2%).

Comparative analysis of classical naming in Chinese and Russian

The subject of the study is the producing motivational bases of nominees in the Chinese and Russian languages. The object of the study is naming in two cultures. The author examines in detail such aspects of the topic as the theory of nomination and its unique features in relation to Chinese and Russian linguistic cultures; the concept of naming and the process of creating onyms in two languages under the influence of historical background. Particular attention is paid to the Chinese tone, which influences the creation of ononyms, as well as a comparative study of onoms in the Chinese and Russian languages. The study was based on provisions formulated by linguists who study issues related to naming and nomination theory: Y.Y. Huang, A.K.K. Chan, V. Mathesius and others. Research methods: systematization and generalization, etymological analysis, conceptual analysis, linguocultural analysis. The main conclusions of the study are the provisions formulated based on the results of the comparative analysis: in Chinese culture, names are chosen to convey certain meanings and connotations. Chinese proper names often consist of two or three characters, with the surname coming first. Surnames are usually passed down through generations and carry with them a deep sense of tradition and origin. Names are often chosen to reflect virtues or values that parents hope to embody in their child. Names can also be chosen based on elements of Chinese astrology, such as the five elements and 12 animal signs. In Russian culture, names also have important meaning and are chosen based on many factors. They usually consist of a first name, a patronymic (derived from the father's name) and a last name. Surnames are usually inherited and reflect the ethnic or regional origin of the family. Names may be chosen based on religious significance, family traditions, or popular trends. The author’s special contribution to the study of the topic is that the article summarizes the main similarities and differences in Russian and Chinese naming. The novelty of the study lies in the fact that for the first time, based on etymological analysis, it established the relevant features of naming in the Chinese and Russian languages, which are also presented in a comparative aspect.

Analysis of Music Features and Song Popularity Trends on Spotify Using K-Means and CRISP-DM

Analysis of Music Features and Song Popularity Trends on Spotify Using K-Means and CRISP-DM

Research on the Effectiveness of Metaverse-Based Learning in Business Courses: A Systematic Review

Metaverse-based learning has emerged as an increasingly popular trend in higher education. However, previous studies on the efficiency of business education within the framework of Metaverse-based Learning is insufficient, despite its profound importance in higher education. To address this problem, the PRISMA methodology are employed to examine recent studies conducted over the last five years. The search encompassed two major databases, namely Scopus and Web of Science, supplemented by the inclusion of Google Scholar as a supporting database. A systematic exploration of the literature yielded a total of 14 articles. The review of these articles indicates that the integration of Metaverse technologies in business education offers enhancements in students' learning experiences and practical skills. Furthermore, the majority of students exhibit a positive attitude towards this educational approach. But there still exit some challenges cannot be ignored.

The role of the Kazakh intelligentsia in the reconstruction of conventional society

Relevance. The relevance of the research lies in the fact that at this stage, post-Soviet Kazakhstan often refers to the beginning of the 20th century, when the intelligentsia fought for independence, modernisation of the consciousness of conventional society so the study of this experience will allow answering many challenges of the current time. Purpose. The purpose of the study is to identify the role of the intelligentsia in the transformation and modernisation of society at the beginning of the 20th century. The paper is devoted to the study of how the Kazakh intelligentsia managed to introduce new elements into the conventional society and form a special identity of the Kazakhs. Methodology. The leading approach is the historical approach, which allows considering the specific features of the political context within the framework of the existence of the Russian Empire. The main methods are the method of analysis, comparative, problem method, which allows identifying the features of the development of the intelligentsia in this period. Results. The paper examines the specific features of the development of the Kazakh intelligentsia, the problem of choosing a direction, analyses changes in the political, economic, educational, cultural spheres. The influence of the popular trend of Jadidism in Central Asia on the views of the intelligentsia is highlighted. The study delved into the multifaceted evolution of the intelligentsia and its profound impact on reshaping conventional society. The research yielded valuable insights into the profound impact of the intelligentsia on societal modernization and consciousness. Conclusions. The Kazakh intelligentsia played a crucial role in preserving the Kazakh nation, preventing complete assimilation by colonial authorities despite numerous decrees and repressive actions aimed at suppressing dissent. The Kazakh intelligentsia succeeded not only in preserving and advancing the concept of Kazakh identity but also in influencing many societal spheres. Keywords: development of the Kazakh intelligentsia; development of public education; Jadidism; pre-revolutionary period; modernisation

Kewirausahaan Pembuatan Piscok Mini Lumer Dalam Kegiatan One Day Enterpreneur Di Universitas Dehasen Bengkulu

In this increasingly modern era, culinary trends continue to develop rapidly. One of the latest trends that is currently popular is melted mini piscok. Piscok mini melt is a variant of banana chocolate which has a smaller size and delicious filling. In 2023, melted mini piscok is predicted to become increasingly popular and become one of people's favorite foods. In 2023, melted mini piscok will experience various innovations and taste improvements that will make it even more contemporary. Various new flavors such as chocolate cheese, matcha chocolate and strawberry chocolate are a special attraction for sweet food lovers. Apart from that, the variety of shapes and appearances is also increasingly attractive with toppings such as nuts, Oreos and sprinkles which make it even more beautiful and appetizing. In facing the melted mini piscok trend in 2023, producers and sellers must be able to keep up with developments and maintain product quality they. This needs to be done to maintain consumer satisfaction and win competition with other competitors. In facing this challenge, producers must continue to carry out research and development to create new innovations that can follow consumer tastes and trends. In conclusion, piscok mini melted will become one of the popular culinary trends in 2023. Innovation and improving taste are factors main role in maintaining the popularity of this food. Apart from that, the unique and modern concept in presentation is also its own attraction. With innovation and quality improvements, it is hoped that mini melted piscok will continue to be popular and become one of the favorite foods in the years to come.

A second-order tolerance analysis approach to statistical virtual assembly for rigid parts

Virtual assembly has become a popular trend in recent years and is used for various purposes, including selective assembly and adaptive tooling. Monte Carlo approaches based on Finite Element Method (FEM) simulations are commonly used for production applications. However, during the design phase, when testing different configurations and design options, a variational method is more suitable. This paper aims to test different implementations of the Method of System Moments applied to the second-order tolerance analysis method when actual distributions, which are non-centered and non-normal, are used as input for the simulation. The study reveals that the simulation results can significantly vary depending on the simulation settings in some cases. As a result, a series of best practices are highlighted to improve the accuracy and reliability of the simulation outcomes.

Japanese Perception of Organ Donation and Implications for New Medical Technologies: Quantitative and Qualitative Social Media Analyses.

The Rapid Autopsy Program (RAP) is a valuable procedure for studying human biology and diseases such as cancer. However, implementing the RAP in Japan necessitates a thorough understanding of concepts such as good death and the integration of sociocultural aspects. By revising perceptions of organ donation on social media, we bring attention to the challenges associated with implementing new medical research procedures such as the RAP. This study aims to examine YouTube and Twitter/X to identify stakeholders, evaluate the quality of organ donation communication, and analyze sociocultural aspects associated with organ donation. Based on our findings, we propose recommendations for the implementation of new medical research procedures. Using the term "" (organ donation), we collected data from YouTube and Twitter/X, categorizing them into 5 dimensions: time, individuality, place, activity, and relationships. We utilized a scale to evaluate the quality of organ donation information and categorized YouTube videos into 3 groups to analyze their differences using statistical methods. Additionally, we conducted a text-based analysis to explore narratives associated with organ donation. Most YouTube videos were uploaded in 2021 (189/638, 29.6%) and 2022 (165/638, 25.9%), while tweets about organ donation peaked between 2019 and 2022. Citizens (184/770, 23.9%), media (170/770, 22.0%), and unknown actors (121/770, 15.7%) were the primary uploaders of videos on organ donation. In a sample of average retweeted and liked tweets, citizens accounted for the majority of identified users (64/91, 70%, and 65/95, 68%, respectively). Regarding Japanese regions, there were numerous information videos about organ donation in Hokkaido (F2.46,147.74=-5.28, P=.005) and Kyushu and Okinawa (F2.46,147.74=-5.28, P=.005). On Twitter/X, Japan and China were the most frequently mentioned countries in relation to organ donation discussions. Information videos often focused on themes such as borrowed life and calls to register as donors, whereas videos categorized as no information and misinformation frequently included accusations of organ trafficking, often propagated by Chinese-American media. Tweets primarily centered around statements of donation intention and discussions about family consent. The majority of video hyperlinks directed users to YouTube and Twitter/X platforms, while Twitter/X hyperlinks predominantly led to news reports from Japanese media outlets. There is significant potential to implement new medical research procedures such as the RAP in Japan. Recommendations include conceptualizing research data as borrowed data, implementing horizontally diversified management of donation programs, and addressing issues related to science misinformation and popular culture trends.

Analysis of Whether Parent-child Family Travel Can Become Alternative Tourism Type to Complement Major Gambling Industry in Macau

Due to COVID-19 and restrictive policies on the gambling industry, Macau's economy, which is dominated by the gambling industry, has shown a negative growth trend in the last two years. In order to help Macau's economic recovery, finding new methods is an essential stage, and parent-child family travel as a popular trend, is undoubtedly a measure worth considering. This report will analyze the characteristics of Macau's tourism industry and the introduction of parent-child family travel, and analyze whether parent-child family travel can become an alternative tourism type to complement the major gaming industry in Macau from the perspective of SWOT, and finally present a plan about parent-child family travel in Macau.

The effectiveness of online group mindfulness-based cognitive therapy for outpatients with depression in China

ObjectivesWith the development of online technology and the increase in real-world needs, conducting psychotherapy on online platforms has become a popular trend. The present study followed the schedule and content of Mindfulness-based Cognitive Therapy (MBCT), and only changed the treatment format (from offline to online) to investigate the effectiveness of online group MBCT for Chinese outpatients with depression. MethodsThe study used before-and-after controlled design, and included 88 depressed outpatients, of which 75 formally underwent a 10-week online group MBCT. The 24-item Hamilton Depression Scale (HAMD-24), Hamilton Anxiety Scale (HAMA), Self-Depression Rating Scale (SDS), Mindful Attention Awareness Scale (MAAS), and Self-Acceptance Questionnaire (SAQ) were administered to patients one week prior to treatment, the fifth week of treatment, and the tenth week of treatment. Repeated-measures data were processed using linear mixed-effects models. Results75 patients (85.23 %) attended >4 sessions, 44 of whom were taking psychotropic medication during treatment. HAMD-24 and HAMA scores decreased significantly in both medicated and unmedicated patients (w10 < w1, p < 0.05). HAMD-24 and HAMA scores declined more rapidly in patients taking medication, with significant decreases in the fifth week (w5 < w1, p < 0.05). The remarkable effectiveness of treatment (HAMD-24 score reduction >50 %) was >30 %, but there were no significant changes in patients' SDS, MAAS, or SAQ scores. ConclusionsThis study supports the effectiveness of online group MBCT for outpatients with depression and the adherence of depressed patients to participate in online group MBCT was high.

(IN)SUFFICIENT RESEARCH ON MUSIC AND ITS MANAGEMENT

Guy de Maupassant has said: A strange art – music – the most poetic and the precise of all forms of arts, vague as a dream and precise as algebra. An attempt to describe and carry out research in the field of music often seems like a description of a scent – music simply exists, it exists on its own – seems that it evades the rational thinking processes. Still music and its consumption is affected by the possibility of its technical reproduction, visualisation, virtuality, differentiated lifestyles, economisation of spheres of life and commercialization. Music research opens possibilities in terms of attention and experience. The same applies to the use of music in advertising, sponsoring, audio brand management. Shifts in the domain of music management in terms of space, format and environment is a challenge. The research methods applicable in management are many-sided: model of conductor and orchestra creating a management model, role of jazz mindset or jazz thinking of a nowadays manager. Music offers a wide range of possibilities in terms of its value research. Especially in economic, symbolic, and social viewpoint. The currently popular trend of city planning is working with the sound of the city in forming a creative environment. Comparing music to literature, painting and cinema has several advantages. Especially unifying is the musical experience obtained in a publicly performed concert, where many people are fully engaged in the same participation. This subject deserves deeper research.