Search Results (192)

Cognitive impairment is a prevalent and disabling feature of multiple sclerosis (MS), significantly impacting patients’ quality of life (QoL) and psychological well-being. Despite its clinical relevance, there are currently no approved pharmacological treatments for cognitive deficits in MS, highlighting the need for effective non-pharmacological interventions. This narrative review explores evidence from studies evaluating the efficacy of cognitive re-education (CR) approaches (including traditional, group-based, computer-assisted, virtual reality, and innovative methods such as music therapy) on cognitive and QoL outcomes in people with MS. The findings demonstrate that while CR consistently influences cognitive domains such as memory, attention, and executive function, its effects on QoL are more variable and often depend on intervention type, duration, and individual patient characteristics. Notably, integrative approaches like virtual reality and music therapy show promising results in enhancing both cognitive performance and psychosocial well-being. Several studies report that cognitive gains are accompanied by improvements in mental health and functional QoL, particularly when interventions are tailored to individual needs and delivered within multidisciplinary frameworks. However, some interventions yield only limited or transient QoL benefits, underlining the importance of personalized, goal-oriented strategies that address both cognitive and psychosocial dimensions. Further research is needed to optimize intervention strategies and clarify the mechanisms linking cognitive and QoL outcomes. Full article

In the field of music notation recognition, while the recognition technology for common notation systems such as staff notation has become quite mature, the recognition techniques for traditional Chinese notation systems like guqin tablature (jianzipu) and Kunqu opera gongchepu remain relatively underdeveloped. As an important carrier of China’s thousand-year musical culture, the digital preservation and inheritance of Kunqu opera’s Gongche notation hold significant cultural value and practical significance. By addressing the unique characteristics of Gongche notation, this study overcomes the limitations of Western staff notation recognition technologies. By constructing a deep learning model adapted to the morphology of Chinese character-style notation symbols, it provides technical support for establishing an intelligent processing system for Chinese musical documents, thereby promoting the innovative development and inheritance of traditional music in the era of artificial intelligence. This paper has constructed the LGRC2024 (Gong-che notation based on Lilu Qu Pu) dataset. It has also employed data augmentation operations such as image translation, rotation, and noise processing to enhance the diversity of the dataset. For the recognition of Gong-che notation, the YOLOv8 model was adopted, and the network performances of its lightweight (n) and medium-weight (m) versions were compared and analyzed. The superior-performing YOLOv8m was selected as the basic model. To further improve the model’s performance, SimAM, Triplet Attention, and Multi-scale Convolutional Attention Module (MSCAM) were introduced to optimize the model. The experimental results show that the accuracy of the basic YOLOv8m model increased from 65.9% to 78.2%. The improved models based on YOLOv8m achieved recognition accuracies of 80.4%, 81.8%, and 83.6%, respectively. Among them, the improved model with the MSCAM module demonstrated the best performance in all aspects. Full article

Cinematic aesthetic values have not been studied as thoroughly as those in music and the visual arts. Three hypotheses for these values are that they are like those of artistic paintings, that they emphasize the spatial coherence of the optical flow, and that they are temporally smooth. Here, we test these hypotheses and investigate other candidate aesthetic values by comparing the statistics of narrative movies and those obtained spontaneously. We perform these tests by using narrative movies from the early stages of cinematic history because these films are simple. We statistically compare these films with spontaneous movies of scenes from daily life. These statistical comparisons do not support the first hypothesis for early movies. The comparisons show that symmetry, balance, and image complexity (normalized Shannon entropy) are not different in early and spontaneous movies. For similar reasons, our data do not support the spatial coherence of early-movie optical flows as having cinematic aesthetic functions. However, in support of the third hypothesis, the temporal smoothness of luminance, but not of motions, appears to have cinematic aesthetic value. The data also uncovered two other cinematic aesthetic value candidates in both statistical surprise and spatial and temporal complexities. We discuss these candidates, pointing out similarities to music and the importance of film editing. Full article

This study investigates the relationship between gender and global media consumption habits, platform preferences, and engagement types. Prior research suggests that gender significantly influences media preferences, with men being traditionally engaged with news, action-oriented content, and competitive media, and women with entertainment, lifestyle, and social media-driven content. The current primary quantitative research is based on a questionnaire that was distributed online and answered by 292 respondents, equally distributed between men and women. The research findings showed that men are more likely to consume news, video games, and discussion-based media. On the other hand, women showed higher engagement with entertainment content, music, and listening-based media. Pearson’s correlation analysis, conducted using SPSS (v23), further confirmed these gendered preferences. Despite the persistence of traditional gendered media patterns, this research also identified the areas in which digital platforms seem to facilitate more balanced engagement across the two genders. Full article

High-precision Direction-of-Arrival (DOA) estimation leveraging multi-sensor array architectures represents a frontier research domain in advanced array signal processing systems. Compared to traditional model-driven estimation methods like MUSIC and ESPRIT, data-driven approaches offer advantages such as higher estimation accuracy and simpler structures. Convolutional neural networks (CNNs) currently dominate deep learning approaches for DOA estimation. However, traditional CNNs suffer from limitations in capturing global features of covariance matrices due to their restricted local receptive fields, alongside challenges such as noise sensitivity and poor interpretability. To address these issues, we propose a novel Discrete Fourier Transform (DFT)-based deep learning framework for DOA estimation called DFNeT, leveraging the advantages of Fourier transform-enhanced networks in global modeling, computational efficiency, and noise robustness. Specifically, our approach introduces a DFT-based deep feature fusion network to denoise covariance matrices by integrating spatial and frequency-domain information. Subsequently, a series of DFT modules are designed to extract discriminative frequency-domain features, enabling accurate and robust DOA estimation. This method effectively mitigates noise interference while enhancing the interpretability of feature extraction through explicit frequency-domain operations. The simulation results demonstrate the effectiveness of the proposed method. Full article

Background/Objectives: The mechanisms underlying the positive association between reading and rhythmic skills remain unclear. Our goal was to systematically test between two major explanations: the Temporal Sampling Framework (TSF), which highlights the relation between rhythm and speech encoding, and a competing explanation based on rhythm’s role in enhancing prediction within visual and auditory sequences. Methods: We compared beat versus duration perception for their associations with encoding and sequence learning (prediction-related) tasks, using both visual and auditory sequences. We also compared these associations for Portuguese vs. Greek participants, since Portuguese stress-timed rhythm is more compatible with music-like beats lasting around 500 ms, in contrast to the syllable-timed rhythm of Greek. If rhythm acts via speech encoding, its effects should be more salient in Portuguese. Results: Consistent with the TSF’s predictions, we found a significant association between beat perception and auditory encoding in Portuguese but not in Greek participants. Correlations between time perception and sequence learning in both modalities were either null or insufficiently supported in both groups. Conclusions: Altogether, the evidence supported the TSF-related predictions in detriment of the Rhythm-as-Predictor (RaP) hypothesis. Full article

This study investigates the influence of experiential programs (EPs) on enhancing consumer experience offerings at luxury resorts. EPs encompass a variety of activities, amenities, and services designed to immerse consumers in the local culture, scenery, and authenticity. The research focuses explicitly on EPs related to fitness, evening entertainment, children’s activities, and personalized experiences. By analyzing data from 30 resorts, significant trends and typologies within each category of EP emerged, highlighting the diverse ways in which resorts meet consumers’ desires for immersive and status-enhancing experiences. Valuable insights were gained through semi-structured interviews with two hoteliers, providing a deeper understanding of the strategic integration of EPs. Fitness EPs highlight activities, including hiking and yoga, whereas evening entertainment encompasses experiences like mixology, music, and astronomy education. For children, EPs prioritize cultural immersion through hands-on experiences, while personalized EPs—including romance packages and private dining—allow for consumer exclusivity. The research underscores how these EPs align with contemporary trends in conspicuous consumption, where luxury resorts leverage unique, high-quality, and culturally rich experiences to reinforce affluence and societal standing. The findings emphasize that EPs are a vital strategy for luxury resorts to differentiate themselves in a competitive market, enhancing consumer satisfaction, loyalty, and positive self-image. Full article

Deciphering the structural hierarchy of musical compositions is indispensable for a range of music analysis applications, encompassing feature extraction, data compression, interpretation, and visualization. In this paper, we introduce a quantitative model grounded in fractal theory to evaluate the significance of individual notes within a musical piece. To analyze the quantized note importance, we adopt a rhythm-based approach and propose a series of detection operators informed by fundamental rhythmic combinations. Employing the Mamba model, we carry out recursive detection operations that offer a hierarchic understanding of musical structures. By organizing the composition into a tree data structure, we achieve an ordered layer traversal that highlights the music piece’s multi-dimensional features. Musical compositions often exhibit intrinsic symmetry in their temporal organization, manifested through repetition, variation, and self-similar patterns across scales. Among these symmetry properties, fractality stands out as a prominent characteristic, reflecting recursive structures both rhythmically and melodically. Our model effectively captures this property, providing insights into the fractal-like regularities within music. It also proves effective in musical phrase boundary detection tasks, enhancing the clarity and visualization of musical information. The findings illustrate the model’s potential to advance the quantitative analysis of music hierarchy, promoting novel methodologies in musicological research. Full article

Many publications on early house and techno music have the character of documentation and include (auto-)biographical statements from contemporaries of the scene. This literature has led to many statements, hypotheses, and conclusions. The weaknesses of such sources are their selective and subjective nature, and the danger of unclear memories, romanticization, and constructive memory. Consequently, a validation through content-based, quantitative music analyses is desirable. For this purpose, the HOuse and Techno music from Germany and AMErica (HOTGAME) corpus was built. Metrics from the field of data quality control show that the corpus is representative and explanatory for house and techno music from Germany and the United States of America between 1984 and 1994. HOTGAME can serve as a reliable source for the analysis of early house and techno music using big data methods, like inferential statistics and machine learning. Full article

This paper integrates concepts from neurobiology, marketing and musicology to propose a causal model of music appreciation and exploratory listening, using directed acyclic graphs (DAGs) and structural equation models (SEMs). The key concepts are music appreciation (measured on a scale from 1 to 10), evaluations, experiences and the qualities of musical features, which the listeners explore and describe from a first-person perspective. The qualities are understood in terms of a satisfaction or dissatisfaction rating of operational features. The development of the causal model is based on a reiterative methodology involving surveys. Applying the causal model to a large survey of 800 listeners reveals that listeners adopt a slightly different causal pathway for their appreciation of liked versus disliked music. When listeners dislike music, the source of their dissatisfaction is more consistently attributed to the perceived or missed musical qualities rather than to their personal experiences. The iterative methodology and causal modeling offer a foundation for further investigation and refinement in various listening contexts. Full article

Exploratory listening encompasses the various ways, contexts, and levels of attention with which listeners engage with their sonic environment. This paper presents findings from qualitative research conducted with audience members during the Stardew Valley: Festival of Seasons concert tour. During these events, attendees encountered music from the widely successful indie video game, reorchestrated in a new context. Just as the game encourages exploration through open-ended gameplay, the concerts prompt listeners to explore how the rearranged music refers to and diverges from its use in the game. Findings suggest that attendees deployed their attention to divergent aspects of the music. While some attendees focused on specific musical aspects like recognizable melodies and instrumentation, others focused on the broader audiovisual and community aspects of the performance. Results also indicate that highly immersed listeners experience diverse thoughts, including those not directly about the immediate musical content. Positioning music-evoked imaginings as a way listeners become immersed in musical experiences, we report on how exploratory listening shapes the dynamics of attention, immersion, and enjoyment within musical and audiovisual contexts. Full article

Aggressive behaviour in pigs poses significant challenges to animal welfare, production efficiency, and economic performance in the pork industry. This review explores the multifaceted causes of pig aggression, focusing on genetic, environmental, and physiological factors. Aggression in pigs is categorized into social, maternal, fear-induced, play, and redirected aggression, with early-life hierarchies and environmental stressors playing critical roles. Physiological markers, such as elevated cortisol and reduced serotonin levels, are closely linked to aggressive behaviour, while dietary interventions, including tryptophan supplementation, have shown promise in mitigating aggression. Environmental factors, such as overcrowding, noise, and heat stress, exacerbate aggressive tendencies, whereas enrichment strategies, like music and improved housing conditions, can reduce stress and aggression. Genome-wide analyses have pinpointed specific polymorphisms in neurotransmitter genes (DRD2, SLC6A4, MAOA) and stress-response loci (RYR1) as significant predictors of porcine aggression. Advances in genomic technologies, including genome-wide association studies (GWASs) and transcriptomic analyses, have further elucidated the genetic and epigenetic underpinnings of aggressive behaviour. Practical application in breeding programmes remains challenging due to aggression polygenic nature and industry hesitancy toward genomic approaches. Future research should focus on integrating genetic markers into breeding programmes, developing multitrait selection indices, and exploring epigenetic modifications to improve animal welfare and production efficiency. By addressing these challenges, the pork industry can enhance both the well-being of pigs and the sustainability of production systems. Full article

This paper addresses the issue of distinguishing commercially played songs from non-music audio in radio broadcasts, where automatic song identification systems are commonly employed for reporting purposes. Service call costs increase because these systems need to remain continuously active, even when music is not being broadcast. Our solution serves as a preliminary filter to determine whether an audio segment constitutes “music” and thus warrants a subsequent service call to an identifier. We collected 139 h of non-consecutive 5 s audio samples from various radio broadcasts, labeling segments from talk shows or advertisements as “non-music”. We implemented multiple data augmentation strategies, including FM-like pre-processing, trained a custom Convolutional Neural Network, and then built a live inference platform capable of continuously monitoring web radio streams. This platform was validated using 1360 newly collected audio samples, evaluating performance on both 5 s chunks and 15 s buffers. The system demonstrated consistently high performance on previously unseen stations, achieving an average accuracy of 96% and a maximum of 98.23%. The intensive pre-processing contributed to these performances with the benefit of making the system inherently suitable for FM radio. This solution has been incorporated into a commercial product currently utilized by Italian clients for royalty calculation and reporting purposes. Full article

The Korean popular music (K-pop) industry, with its global popularity and increasing multilingual orientation, serves as a suitable context for exploring language perceptions. This research examines the metalinguistic commentary on K-pop idols’ English accents on YouTube. Specifically, we investigate how online users evaluate the idols’ English accents and how their metalinguistic comments communicate linguistic ideologies that favor a “native” way of speaking. Our dataset consists of 602 metalinguistic comments drawn from four popular YouTube videos featuring the evaluation of K-pop idols’ accents. We employ content analysis to first categorize comments into positive, negative, and neutral evaluations, then focus on aspects being evaluated in the users’ comments (e.g., social attractiveness and (non-)nativeness). The results indicate that a vast majority of comments (88.1%) convey positive evaluations, largely associating the idols’ accents with social appeal and native-like accents. Although a few neutral and negative evaluations exist, our result shows a dominant preference for inner circle accents and complex attitudes toward accented speech in digital spaces. We conclude by highlighting the influence of digital platforms in shaping language perceptions and the implications for linguistic stereotyping in the context of K-pop culture. Full article

(1) Background: People with intellectual disabilities and blindness tend to be withdrawn and sedentary. This study was carried out to assess a new technology system to enable seven of these people to collect boxes containing different sets of objects from a storage room and transport them to the appropriate destination rooms. (2) Methods: The technology system used for the study involved tags with radio frequency identification codes, a tag reader, a smartphone, and mini speakers. At the start of a session, the participants were called by the system to take a box from the storage room. Once they collected a box, the system identified the tags attached to the box, called the participants to the room where the box was to be transported and delivered, and provided them with preferred music stimulation. The same process was followed for each of the other boxes available in the session. (3) Results: During baseline sessions without the system, the mean frequency of boxes handled correctly (collected, transported, and put away without research assistants’ guidance) was zero or virtually zero. During the intervention sessions with the system, the participants’ mean frequency of boxes handled correctly increased to between about 10 and 15 per session. (4) Conclusions: These findings suggest that the new technology system might be helpful for people like the participants of this study. Full article