Search Results (105)

Traditional time-frequency diagnostics for high-speed bearings face an entrenched trade-off between resolution and real-time feasibility. We present a fast Dual-Phase Short-Time Root-MUSIC pipeline that exploits Hankel structure via FFT-accelerated Lanczos bidiagonalization and Sliding-window Singular Value Decomposition to deliver sub-Hz super-resolution under millisecond budgets. Validated on the Politecnico di Torino aerospace dataset (seven fault classes, three severities), fDSTrM detects 150 μm inner-race and rolling-element defects with 98% and 95% probability, respectively, at signal-to-noise ratio down to −3 dB (78% detection), while Short-Time Fourier Transform and Wavelet Packet Decomposition fail under identical settings. Against classical Root-MUSIC, the approach sustains approximately 200 times speedup with less than ${10}^{-11}$ relative frequency error in offline scaling, and achieves 1.85 milliseconds per 4096-sample frame on embedded-class hardware in streaming tests. Subspace order pre-estimation with adaptive correction preserves closely spaced components; Kalman tracking formalizes uncertainty and yields 95% confidence bands. The resulting early warning margin extends maintenance lead-time by 24–72 h under industrial interferences (Gaussian, impulsive, and Variable Frequency Drive harmonics), enabling field-deployable super-resolution previously constrained to offline analysis. Full article

The study of fractals has a long history in mathematics and signal analysis, providing formal tools to describe self-similar structures and scale-invariant phenomena. In recent years, cognitive science has developed a set of powerful theoretical and experimental tools capable of probing the representations that enable humans to extend hierarchical structures beyond given input and to generate fractal-like patterns across multiple domains, including language, music, vision, and action. These paradigms target recursive hierarchical embedding (RHE), a generative capacity that supports the production and recognition of self-similar structures at multiple scales. This article reviews the theoretical framework of RHE, surveys empirical methods for measuring it across behavioral and neural domains, and highlights their potential for cross-domain comparisons and developmental research. It also examines applications in linguistic, musical, visual, and motor domains, summarizing key findings and their theoretical implications. Despite these advances, the computational and biological mechanisms underlying RHE remain poorly understood. Addressing this gap will require linking cognitive models with algorithmic architectures and leveraging the large-scale behavioral and neuroimaging datasets generated by these paradigms for fractal analyses. Integrating theory, empirical tools, and computational modelling offers a roadmap for uncovering the mechanisms that give rise to recursive generativity in the human mind. Full article

This study explores how Philip Glass’s post-minimalist techniques in the film score of The Hours interact with the film’s non-linear narrative structure. By integrating musicological analysis and film narrative theory, the paper examines the use of micro-variations, additive processes, and repetitive harmonic structures in Glass’s score. These techniques are shown to not only intensify the emotional resonance of the film but also reinforce its fragmented temporal flow across three interwoven storylines. Case studies of specific scenes illustrate how the music’s subtle evolution parallels the narrative’s thematic continuity and psychological depth. This research contributes to the understanding of post-minimalist film scoring, emphasizing the aesthetic and structural synergies between music and moving image. Full article

Music education offers well-documented benefits for student learning; however, generalist teachers often report low confidence in integrating music into their lessons. This study applies Universal Design for Learning (UDL) principles to develop teaching resources that address teacher barriers to music integration. Using framework analysis, data collected from semi-structured interviews with ten trainee primary teachers in United Arab Emirates (UAE) British curriculum schools were mapped against UDL’s three core principles: engagement, representation, and action and expression. Despite recognising music’s holistic educational value in cognitive enhancement, memory retention, and student expression, participants reported significant barriers to integrating the subject into their lessons. These barriers included performance anxiety, a perceived lack of subject knowledge, and fear of student judgement. The barriers were most pronounced when faced with the prospect of teaching upper-primary students. Framework analysis revealed how these challenges align with the UDL’s core principles. These findings led to the development of five-step music resources, categorised into beginner and intermediate levels. Each step of the resources is designed to systematically address these identified barriers through UDL’s proactive and intentional design criteria. This demonstrates how teacher education can move beyond identifying barriers to creating structured solutions that support inclusive music integration while maintaining pedagogical authenticity. Full article

Cultural and religious diversity has become a defining feature of societies worldwide. Although religious music serves as a powerful medium for fostering intercultural understanding, it remains underexamined in educational research. This systematic review analyzes studies published between 2016 and 2025, identified through comprehensive searches of SCOPUS, Web of Science, and ERIC databases. Eleven peer-reviewed studies meeting thematic criteria were selected for in-depth analysis. Findings revealed persistent challenges in religious music education, including policy ambiguity, teacher identity constraints, and limited resources. The review identifies a shift from traditional knowledge transmission to experiential pedagogies, leading to outcomes such as emotional resonance, intercultural understanding, moral self-regulation, and student agency. It also highlights structural gaps in longitudinal research and a significant underrepresentation of religious music traditions from Eastern Europe and other non-Anglophone regions. A practice–outcome heatmap developed in this study uncovered unexplored links, particularly regarding student agency. Future research should investigate these underexplored pedagogical–outcome pathways and address current geographic and cultural imbalances by incorporating regional traditions—such as Eastern European choral and sacred music—into global academic discourse. Full article

Background: The increasing demand for care in hospital settings, often at a high intensity, requires organizing work according to 24 h shifts. Nevertheless, shift work (SW), especially at night, alters the circadian rhythm, negatively affecting the psychophysical health of nurses, compromising their quality of life, and jeopardizing patient safety. Shift-work-related diseases (SWDs) can arise from these disruptions. Methods: This systematic review aims to evaluate the effects of several types of medical, psychotherapeutic, and educational interventions and strategies on shift-work-related diseases (SWDs). The databases PubMed, Embase, Web of Science, and Cochrane were searched using the MESH terms “shift work” and “nurses” from January 2015 to March 2025. A total of 43 articles were included in the final analysis. Results: Quantitative findings from the studies showed, for example, improvements in sleep quality scores ranging from 15% to 40% with optimized shift planning, reductions in fatigue scores by 20–35% through strategic napping, and moderate effect sizes for light therapy interventions. Physical activity and relaxation techniques were associated with a 10–25% improvement in subjective well-being indices, while meal timing interventions led to reductions in gastrointestinal symptom prevalence by up to 18%. The selected articles were discussed by dividing them according to the type of intervention applied to shift nurses, namely improvement of shift planning, light and temperature modulation, introduction of napping, supplementation, meal management, psychotherapy, sleep education, physical activity, relaxation techniques and yoga, music therapy, and aromatherapy. This categorization was performed to highlight the range of strategies tested and their relative quantitative impact. Conclusions: There is evidence that SWDs can be mitigated through targeted interventions and strategies. The limitations of the studies examined include small sample sizes, extreme heterogeneity of follow-up, the few numbers of randomized controlled trials, and the prevalence of female or Intensive Care Unit nurses in study samples. Further research should focus on large-scale randomized controlled trials, multicenter longitudinal studies, and the evaluation of the most promising interventions—particularly light therapy, optimized shift scheduling, and structured napping protocols—to assess their long-term efficacy and generalizability. Full article

This article offers a descriptive analysis of a specific form (uṣūl) of prophetic eulogy (ṣalawāt) as vocally performed within Sufi orders such as the Rifāʿiyya, Qādiriyya, and Jarrahiyya of today’s Türkiye. It combines a music–theoretical and music–sociological as well as ritual–theoretical perspective to examine how the structured performance of these chants functions both as a spiritual practice and as a means of social formation. Drawing on this dual perspective, the article analyses the underlying musical structures and elements of the ṣalawāt chant, such as melody, rhythm, harmony, modal frameworks, and dynamics. By examining how these formal aspects shape the aesthetic experience, emotional resonance, and theological significance of the eulogy, the study aims to highlight its performative and affective potential within Sufi devotional practice. Within the ritual framework of Sufi orders (ṭarīqa), this rhythmic and collective performance acts as a practice of tazkiya an-nafs (self-purification), cultivating attentiveness, moral refinement, and communal belonging through synchronized voice, breath, and bodily presence. The repeated invocation of the Prophet Muḥammad, venerated as the perfect human (al-insān al-kāmil), thus becomes a means of fostering inner transformation and spiritual proximity. In this way, ṣalawāt chanting mediates religious meaning not only through text but through embodied experience and performative devotion. Full article

In the digital age, social media significantly shapes public attitudes and emotional responses towards health interventions, such as HPV vaccination, which is critical in developing countries. This study employed a deep learning model to identify fine-grained emotions of 38,615 HPV-related tweets from 2016 to 2024, revealing significant shifts in public emotions. Notably, skepticism about vaccine commercialization motives heightened anger, while university outreach initiatives fostered positive emotions. Structural entropy analysis highlighted polarized emotional communication networks: the network of joy exhibited lower entropy with centralized information flow, whereas other emotions displayed higher entropy, fragmented dissemination, and enhanced cross-community communication efficiency. New communicators, such as campus accounts and music bloggers, played pivotal roles in spreading positive emotions, while individual bloggers in specific fields amplified negative emotions like anger, particularly in closed networks. This research underscores the intricate dynamics of online health communication and the need for targeted interventions to address stigma and enhance public awareness of HPV vaccination, providing valuable insights for future public health policy. Full article

Sensory heritage encompasses culturally valued practices, rituals, and everyday activities experienced through the senses. While sight often dominates, hearing and smelling are generally more immersive and pervasive. Soundscape research is a well-established field within urban studies; however, smellscape remains insufficiently recognised. This study is part of Multimodal Hong Kong, a project aimed at documenting sensory cultural heritage across the city by capturing the complex interplay between soundscape, smellscape, urban experiences, everyday activities, and memory. We investigated the multisensory environment at Wong Tai Sin Temple through acoustic measurements and perceptual ratings of soundscape and smellscape across 197 locations within and around the site. Additionally, semi-structured interviews were conducted with visitors (N = 54, 15,015 words of transcript), which were analysed using content analysis and natural language processing. The results indicate that elevated noise levels mainly arise from human voices and pipe music within the temple compound, as well as traffic noise in the surrounding area. The smell of incense dominates near the temple altars, whereas natural, grassy odours prevail in the adjacent park. Interview responses confirm that incense burning constitutes a traditional religious practice forming a distinctive olfactory marker for Chinese temples, but it is also perceived as having adverse health implications. This study contributes to the growing body of sensory heritage research, underscoring the importance of both soundscape and smellscape in fostering culturally inclusive, vibrant, and sustainable urban environments. Full article

In this paper, a set of digital signal processing (DSP) procedures tailored for the analysis of complex musical tones with prominent inharmonicity is presented. These procedures are implemented within a MATLAB-based application and organized into three submodules. The application follows a structured DSP chain: basic signal manipulation; spectral content analysis; estimation of the inharmonicity coefficient and the number of prominent partials; design of a dedicated filter bank; signal decomposition into subchannels; subchannel analysis and envelope extraction; and, finally, recombination of the subchannels into a wideband signal. Each stage in the chain is described in detail, and the overall process is demonstrated through representative examples. The concept and the accompanying application are initially intended for rapid post-processing of recorded signals, offering a tool for enhanced signal annotation. Additionally, the built-in features for subchannel manipulation and recombination enable the preparation of stimuli for perceptual listening tests. The procedures have been tested on a set of recorded tones from various string instruments, including those with pronounced inharmonicity, such as the piano, harp, and harpsichord. Full article

Jazz music has long been a subject of interest in the field of generative music. Traditional jazz chord progressions follow established patterns that contribute to the genre’s distinct sound. However, the demand for more innovative and diverse harmonic structures has led to the exploration of alternative approaches in music generation. This paper addresses the challenge of generating novel and engaging jazz chord sequences that go beyond traditional chord progressions. It proposes an unconventional statistical approach, leveraging a corpus of 1382 jazz standards, which includes key information, song structure, and chord sequences by section. The proposed method generates chord sequences based on statistical patterns extracted from the corpus, considering a tonal context while introducing a degree of unpredictability that enhances the results with elements of surprise and interest. The goal is to move beyond conventional and well-known jazz chord progressions, exploring new and inspiring harmonic possibilities. The evaluation of the generated dataset, which matches the size of the learning corpus, demonstrates a strong statistical alignment between distributions across multiple analysis parameters while also revealing opportunities for further exploration of novel harmonic pathways. Full article

In deep learning, Long Short-Term Memory (LSTM) is a well-established and widely used approach for music generation. Nevertheless, creating musical compositions that match the quality of those created by human composers remains a formidable challenge. The intricate nature of musical components, including pitch, intensity, rhythm, notes, chords, and more, necessitates the extraction of these elements from extensive datasets, making the preliminary work arduous. To address this, we employed various tools to deconstruct the musical structure, conduct step-by-step learning, and then reconstruct it. This article primarily presents the techniques for dissecting musical components in the preliminary phase. Subsequently, it introduces the use of LSTM to build a deep learning network architecture, enabling the learning of musical features and temporal coherence. Finally, through in-depth analysis and comparative studies, this paper validates the efficacy of the proposed research methodology, demonstrating its ability to capture musical coherence and generate compositions with similar styles. 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

Theaters in ancient Pompeii played a vital role in Roman entertainment, shaping the auditory experiences of spectators. This study examines the acoustic properties of the Amphitheater, the Grand Theater, and the Odeon using impulse response (IR) analysis to reconstruct their soundscapes. Next, the study considers the impact of typical musical instruments, vocal performances, and ambient sounds—such as gladiatorial combat—on these spaces’ acoustics. Findings reveal significant differences in reverberation times, sound clarity, and spatial characteristics, shaped by each theater’s design. These sites, preserved after the eruption of Mount Vesuvius, provide a unique opportunity to analyze how architecture influenced sound propagation. The Amphitheater, with its vast open structure, enhanced large-scale events, while the Grand Theater’s semi-enclosed design balanced musical and theatrical performances. The Odeon, the most intimate of the three, prioritized speech clarity. These insights highlight how Roman architects engineered performance spaces to accommodate diverse entertainment forms. By combining acoustic measurements with historical context, this research offers a deeper understanding of ancient Pompeii’s soundscapes and the auditory experiences of its inhabitants and offers insights for composition and soundscape creations that take inspiration from these prominent historical architectural and cultural icons whilst exploring its potential within contemporary immersive listening practices. Full article

Understanding tonal structures in Renaissance music has been a long-standing musicological problem. Computational analysis on a large scale could shed new light on this. Encoded scores provide easy access to pitch content, but the availability of such data is low. This paper addresses this shortage of data by exploring the potential of audio recordings. Analysing audio, however, is challenging due to the presence of harmonics, reverb and noise, which may obscure the pitch content. We test several multiple pitch estimation models on audio recordings, using encoded scores from the Josquin Research Project (JRP) as a benchmark for evaluation. We present a dataset of multiple pitch estimations from 611 compositions in the JRP. We use the pitch estimations to create pitch profiles and pitch class profiles, and to estimate the lowest final pitch of each recording. Our findings indicate that the Multif0 model yields pitch profiles, pitch class profiles and finals most closely aligned with symbolic encodings. Furthermore, we found no effect of year of recording, number of voices and ensemble composition on the accuracy of pitch estimations. Finally, we demonstrate how these models can be applied to gain insight into tonal structures in early polyphony. Full article