Search Results (25)

Controllable symbolic music generation must preserve a reference melody while remaining responsive to style prompts. Existing hierarchical diffusion systems typically reuse a shared condition vector across harmony, rhythm, and timbre stages, which can entangle stylistic factors and weaken melody preservation. We present HCDMG++, a hierarchical diffusion framework that addresses these two limitations through stage-aware style routing and differentiable melody regularization. The routing module uses a residual multi-layer perceptron (MLP) with zero-initialized scalar gates to project text-derived style embeddings into harmony-, rhythm-, and timbre-specific subspaces, whereas the regularization branch aligns soft pitch histograms and contour trajectories with the conditioning melody during training without breaking the differentiable computation graph. We evaluate the integrated system on a 384-sample benchmark covering four melodies, eight styles, four random seeds, and three denoising budgets, supplemented by a matched legacy-compatible reference and inference-time component ablation that contrasts legacy behavior, silenced gates, an automated uniform gamma routing sweep, and the full forward pass. HCDMG++ produces valid four-track outputs in all 384 runs, reaches a peak pitch histogram similarity score of 0.508 under a 64-step budget, and improves pitch histogram alignment over Legacy-HCDMG by roughly two orders of magnitude on the matched slice, while attaining a positive Fisher-style style separability score where the legacy benchmark is too sparse to support one. These results indicate that stage-specific conditioning and differentiable structural guidance jointly improve controllability in symbolic music diffusion, while also exposing the remaining limitations in long-form generalization and perceptual validation, which motivate the future work outlined at the end of this paper. Full article

To evaluate the psycho-behavioral interaction during Ro-Ro ship evacuations, this paper proposes a coupled simulation model integrating psychological stress with behavior. The model quantifies stress through a function of local density, dwelling time, exit distance, and lifejacket retrieval waiting time, specifically accounting for the bottleneck effects during the donning phase. Using a psychological stress factor to dynamically adjust weight coefficients in the exit choice cost function, the study utilizes the AnyLogic platform to compare five scenes: shortest distance (S1), stress-induced acceleration (S2), perceptual-decay herding (S3), dynamic congestion avoidance (S4), and without retrieving lifejackets (S5). Results indicate: (1) S4 improves evacuation efficiency by 7.58% over S3 by maintaining perceptual intensity, while stress-driven acceleration (S2) shows limited effectiveness. (2) Early preparation exerts critical feedback; S4 enhances lifejacket retrieval efficiency by 14.31% over S3, alleviating initial stress and its cross-stage negative impacts. (3) Dynamic avoidance improves system resilience, keeping stressed passengers within 8.5% and breaking the “congestion-stress” vicious cycle. This study demonstrates that moderate stress must be coupled with rational exit choices. S4 effectively intervenes in stress accumulation, and S5 verified the necessity of the simulation process for retrieving lifejackets, providing a quantitative basis for resilient and robust Ro-Ro ship emergency planning and crew guidance. Full article

This work presents a hierarchical deep reinforcement learning (DRL) framework based on Soft Actor–Critic (SAC) for the autonomy of rock-breaking machinery in surface mining comminution processes. The proposed approach explicitly integrates mobile navigation and hydraulic manipulation as coupled subprocesses within a unified decision-making architecture, designed to operate under the unstructured and highly uncertain conditions characteristic of open-pit mining operations. The system employs a hysteresis-based switching mechanism between specialized SAC subagents, incorporating automatic entropy tuning to balance exploration and exploitation, twin critics to mitigate value overestimation, and curriculum learning to manage the progressive complexity of the task. Two coupled subsystems are considered, namely: (i) a tracked mobile machine with a differential drive, whose continuous control enables safe navigation, and (ii) a hydraulic manipulator equipped with an impact hammer, responsible for the fragmentation and dismantling of rock piles through continuous joint torque actuation. Environmental perception is modeled using processed perceptual variables obtained from point clouds generated by an overhead depth camera, complemented with state variables of the machinery. System performance is evaluated in unstructured and uncertain simulated environments using process-oriented metrics, including operational safety, task effectiveness, control smoothness, and energy consumption. The results show that the proposed framework yields robust, stable policies that achieve superior overall process performance compared to equivalent hierarchical configurations and ablation variants, thereby supporting its potential applicability to DRL-based mining automation systems. Full article

Objectives: To evaluate the feasibility and efficacy of a brief, scaffolded virtual reality (VR)-based perceptual-learning protocol to improve stereovision in adults without measurable baseline global stereopsis. Methods: Prospective interventional pilot study with a normal-vision reference group. Fourteen adults were enrolled; nine with nil global stereoacuity formed the intervention group and five with normal binocular vision served as controls. Intervention participants completed 8–10 VR sessions (~30 min each over two weeks) using a disparity-driven depth-matching task with individualized thresholds, virtual prism compensation, and interocular contrast balancing. Primary outcomes were changes in clinical stereoacuity (local and global) and Binocular Function (BF). Secondary outcomes included positive fusional vergence (PFV), binocular imbalance (inter-ocular contrast ratio), and in-game depth discrimination error (arcseconds). Results: Global stereoacuity improved with four of nine participants who initially showed no measurable global stereopsis achieving measurable thresholds after training (post: 861.11 ± 537.08 arcsec, IQR = 800.00; p = 0.06). Local stereoacuity improved near (pre: 616.67 ± 532.68 arcsec, IQR = 1100.00; post: 361.67 ± 537.11, IQR = 200.00; p = 0.03) and at a distance (pre: 715.11 ± 573.54 arcsec, IQR = 1114.00; post: 437.11 ± 510.41, IQR = 405.00; p = 0.03). BF score improved from 4.33 ± 0.50 (IQR = 1.00) to 3.51 ± 1.14 (IQR = 1.30) (p = 0.03). PFV break at distance increased (pre: 17.83 ± 17.53Δ, IQR = 23.50; post: 24.50 ± 17.12Δ, IQR = 28.50; p = 0.04), and the binocular imbalance showed a nonsignificant trend towards improvement (p = 0.09). In-game depth error decreased from 752.11 ± 384.50 arcsec (IQR = 553.00) to 221.78 ± 79.12 (IQR = 105.00) (p < 0.01). Control participants achieved a mean depth error of 43.00 ± 10.30 arcsec after three sessions. Conclusions: A short-dose, individualized VR protocol yielded gains in stereoacuity and binocular function in adults with severe stereodeficiency, with transfer from in-game learning to standard clinical measures. While the sample size was limited, the approach proved feasible and was well tolerated, showing encouraging efficiency versus prior high-dose regimens. Full article

Background/Objectives: Differentiating adductor spasmodic dysphonia (AdSD) from muscle tension dysphonia (MTD) is challenging because their auditory–perceptual features often overlap. We examined whether high-speed videolaryngoscopy (HSV) combined with two-dimensional digital kymography (2D-DKG) and line DKG yields qualitative signs and quantitative metrics that distinguish AdSD from MTD. Methods: We analyzed vocal fold vibration in eight patients with AdSD, eight with primary MTD, and eleven vocally healthy controls using a multifunctional system integrating HSV, 2D-DKG, and line DKG. Qualitative features (glottal closure, mucosal wave, phase and amplitude symmetry, oscillatory breaks, and supraglottic hyperfunction) and quantitative indices (closed quotient [CQ], speed quotient [SQ], phase symmetry index [PSI], amplitude symmetry index [ASI]) were assessed. Group differences were tested with one-way ANOVA and Scheffé post hoc comparisons. Results: Oscillatory breaks were observed in 75% of AdSD cases and in 0% of MTD and controls, whereas supraglottic hyperfunction occurred in 100% of MTD and in 0% of AdSD and controls. Quantitatively, CQ, SQ, PSI, and ASI differed between dysphonic groups and controls (p < 0.05), but no quantitative index discriminated against AdSD from MTD. Conclusions: HSV with 2D-/line-DKG provides complementary, objective information on vibratory patterns and supraglottic behavior, supporting targeted qualitative assessment in the clinical differentiation between AdSD and MTD, and highlighting the need for its incorporation into clinical practice as a procedure to assist in the complex diagnostic distinction between these conditions. Full article

Rapid and reliable identification of large vessel occlusions and critical stenoses is essential for guiding treatment in acute ischemic stroke. Conventional MR angiography (MRA) and PET protocols are constrained by trade-offs among acquisition time, spatial resolution, and motion tolerance. A multimodal MR–PET angiography reconstruction framework is introduced that integrates joint Hankel-structured sparsity with topology-preserving multitask learning to overcome these limitations. High-resolution time-of-flight MRA and perfusion-sensitive PET volumes are reconstructed from undersampled data using a cross-modal low-rank Hankel prior coupled to a super-resolution generator optimized with adversarial, perceptual, and pixel-wise losses. Vesselness filtering and centerline continuity terms enforce preservation of fine arterial topology, while learned k-space and sinogram sampling concentrate measurements within vascular territories. Motion correction, blind deblurring, and modality-specific denoising are embedded to improve robustness under clinical conditions. A multitask output head estimates occlusion probability, stenosis localization, and collateral flow, with hypoperfusion mapping generated for dynamic PET. Evaluation on clinical and synthetically undersampled MR–PET studies demonstrated consistent improvements over MR-only, PET-only, and conventional fusion methods. The framework achieved higher image quality (MRA PSNR gains up to 3.7 dB and SSIM improvements of 0.042), reduced vascular topology breaks by over 20%, and improved large vessel occlusion detection by nearly 10% in AUROC, while maintaining at least a 40% reduction in sampling. These findings demonstrate that embedding vascular-aware priors within a joint Hankel–sparse MR–PET framework enables accelerated acquisition with clinically relevant benefits for early stroke assessment. Full article

Background: Cochlear implants (CIs) are transformative neuroprosthetics that restore speech perception for individuals with severe-to-profound hearing loss. However, temporal envelope cues are well-represented within the signal processing, while spectral envelope cues are poorly accessed by CI users, resulting in substantial deficits compared to normal-hearing individuals. This profoundly impairs the perception of complex auditory stimuli like music and vocal prosody, significantly impacting users’ quality of life, social engagement, and artistic expression. Methods: This narrative review synthesizes research on CI signal-processing limitations, perceptual and production challenges in music and singing, the role of the auditory–motor feedback loop, and strategies for improvement, including rehabilitation, technology, and the influence of neuroplasticity and sensitive developmental periods. Results: The degraded signal causes marked deficits in pitch, timbre, and vocal emotion perception. Critically, this impoverished input functionally breaks the high-fidelity auditory–motor feedback loop essential for vocal control, transforming it from a precise fine-tuner into a gross error detector sensitive only to massive pitch shifts (~6 semitones). This neurophysiological breakdown directly causes pervasive pitch inaccuracies and melodic distortion in singing. Despite these challenges, improvements are possible through advanced sound-processing strategies, targeted auditory–motor training that leverages neuroplasticity, and capitalizing on sensitive periods for auditory development. Conclusions: The standard CI signal creates a fundamental neurophysiological barrier to singing. Overcoming this requires a paradigm shift toward holistic, patient-centered care that moves beyond speech-centric goals. Integrating personalized, music-based rehabilitation with advanced CI programming is essential for improving vocal production, fostering musical engagement, and ultimately enhancing the overall quality of life for CI users. Full article

In high-density built environments, perceived density (PD)—shaped by physical, socio-cultural, and perceptual factors—often induces sensations of crowding, stress, and spatial oppression. Although green spaces are recognised for their stress-reducing effects, the influence of built-environment characteristics on public sentiment under stringent mobility restrictions remains inadequately explored. This study takes Chongqing, a representative mountainous metropolis in China, as a case to examine how natural and built environmental elements modulate emotional valence across varying PD levels. Using housing data (n = 4865) and geotagged Weibo posts (n = 120,319) collected during the 2022 lockdown, we constructed a PD-sensitive sentiment dictionary and applied Python’s Jieba package and natural language processing (NLP) techniques to analyse emotional scores related to PD. Spatial and bivariate autocorrelation analyses revealed clustered patterns of sentiment distribution and their association with physical density. Using entropy weighting, building density and floor area ratio were integrated to classify residential built environments (RBEs) into five tiers based on natural breaks. Key factors influencing positive sentiment across PD groups were identified through Pearson correlation heatmaps and OLS regression. Three main findings emerged: (1) Although higher-PD areas yielded a greater volume of positive sentiment expressions, they exhibited lower diversity and intensity compared to low-PD areas, suggesting inferior emotional quality; (2) Environmental and socio-cultural factors showed limited effects on sentiment in low-PD areas, whereas medium- and high-PD areas benefited from a significantly enhanced cumulative effect through the integration of socio-cultural amenities and transportation facilities—however, this positive correlation reversed at the highest level (RBE 5); (3) The model explained 20.3% of the variance in positive sentiment, with spatial autocorrelation effectively controlled. These findings offer nuanced insights into the nonlinear mechanisms linking urban form and emotional well-being in high-density mountainous settings, providing theoretical and practical guidance for emotion-sensitive urban planning. Full article

While poetry has long relied on musical and visual elements for its communicative power, numerous contemporary poets are drawing so dramatically on the resources of the visual arts and on elements of musical scoring that their poems become inter-arts hybrids. The interdisciplinary character of environmental writing and its attachment to material conditions of planetary life particularly invite the use of visual and/or audio technologies as documentation or as prompts toward multisensory attention that may shift readers’ perceptions of the more-than-human world. This essay examines four recent works of ecopoetry from the US to explore some of the diverse ways in which, by integrating into volumes of poetry their own visual and musical art, poets are expanding the environmental imagination and enhancing their environmental messaging. The visual and musical elements, I argue, offer fresh perceptual lenses that help break down cognitive habits bolstering separations of Western humans from more-than-human realms or dampening awareness of social and cultural norms that foster environmental degradation and violations of environmental justice. The multi-modal works discussed are Jennifer Scappettone’s The Republic of Exit 43, JJJJJerome Ellis’s Aster of Ceremonies, Danielle Vogel’s Edges & Fray, and Jonathan Skinner’s “Blackbird Stanzas.” Full article

In the context of cultural tourism integration, tourists’ spatial perception intention is an important carrier of spatial evaluation. In historic cultural districts represented by Jinan Mingfu City, tourists’ perceptual depth remains underexplored, leading to a misalignment between cultural tourism development and spatial quality needs. Taking Jinan Mingfu City as a representative case of a historic cultural district, while the living heritage model has revitalized local economies, the absence of a tourist perspective has resulted in misalignment between cultural tourism development and spatial quality requirements. This study establishes a technical framework encompassing “data crawling-factor aggregation-human-machine collaborative optimization”. It integrates Python web crawlers, SnowNLP sentiment analysis, and TF-IDF text mining technologies to extract physical elements; constructs a three-dimensional evaluation framework of “visual perception-spatial comfort-cultural experience” through SPSS principal component analysis; and quantifies physical element indicators such as green vision rate and signboard clutter index through street view semantic segmentation (OneFormer framework). A synergistic mechanism of machine scoring and manual double-blind scoring is adopted for correlation analysis to determine the impact degree of indicators and optimization strategies. This study identified that indicators such as green vision rate, shading facility coverage, and street enclosure ratio significantly influence tourist evaluations, with a severe deficiency in cultural spaces. Accordingly, it proposes targeted strategies, including visual landscape optimization, facility layout adjustment, and cultural scenario implementation. By breaking away from traditional qualitative evaluation paradigms, this study provides data-based support for the spatial quality enhancement of historic districts, thereby enabling the transformation of these areas from experience-oriented protection to data-driven intelligent renewal and promoting the sustainable development of cultural tourism. Full article

While Jacques Rancière’s concept of the political, democracy, emancipation, equality and aesthetic have significantly (re)shaped many recent debates, his notion of dis-agreement—in its French formulation of ‘mésentente’, meaning the fact of not hearing, and/or of not understanding—has received relatively little attention. This article argues that if politics, as Rancière suggests, arise from a novel perceptual universe and if dis-agreement entails not-hearing and/or not-understanding, then “speaking politics”—the very act of breaking away from the dominant configuration of the police order—might be perceived as a noisy sound rather than as coherent and intelligible words. Drawing on Rancière’s concept of mésentente, this article examines the noisy, and largely unintelligible, protests sparked by the violent femicide of Giulia Cecchettin which occurred in Italy in 2023. Ultimately, it raises the following questions: which words are intelligible? Does intelligibility depend on the voice of the speaking subjects? Or does it hinge on the (un)familiarity of the vision they project? How can acts of politics be recognized if the words used are unintelligible? Full article

The group cohesion effect refers to individuals’ identification with the group’s viewpoint, resulting from behavioral and cognitive changes during interactions, and is crucial for group development. However, individual differences in intrinsic characteristics lead to varied group behaviors and cohesion. This paper uses a mathematical model based on viewpoint dynamics to explore how these differences shape group cohesion. The primary consideration is the potential power inherent in individual characteristics, which can be understood as symmetry-breaking concepts. In the model, individuals are classified into two types, each supporting one of two viewpoints. The potential power reflects the individuals’ degree of firmness regarding their viewpoint and their perceptual range. Differences in the potential power, both within and between types, drive shifts in viewpoints and behaviors, generating diverse cohesion effects. Additionally, the model also incorporates the influence of group size and external factors, such as individuals with no viewpoints and those holding public opinion viewpoints. The results indicate that group size has no significant effect on group cohesion, while individuals with no viewpoints contribute to stabilizing it, whereas individuals with public opinions weaken it. These findings highlight the complex relationship between individual differences in potential power and group cohesion, suggesting that symmetry-breaking dynamics can effectively explain group cohesion effects. Full article

The early detection of breast cancer is essential for improving treatment outcomes, and recent advancements in artificial intelligence (AI), combined with image processing techniques, have shown great potential in enhancing diagnostic accuracy. This study explores the effects of various image processing methods and AI models on the performance of early breast cancer diagnostic systems. By focusing on techniques such as Wiener filtering and total variation filtering, we aim to improve image quality and diagnostic precision. The novelty of this study lies in the comprehensive evaluation of these techniques across multiple medical imaging datasets, including a DCE-MRI dataset for breast-tumor image segmentation and classification (BreastDM) and the Breast Ultrasound Image (BUSI), Mammographic Image Analysis Society (MIAS), Breast Cancer Histopathological Image (BreakHis), and Digital Database for Screening Mammography (DDSM) datasets. The integration of advanced AI models, such as the vision transformer (ViT) and the U-KAN model—a U-Net structure combined with Kolmogorov–Arnold Networks (KANs)—is another key aspect, offering new insights into the efficacy of these approaches in different imaging contexts. Experiments revealed that Wiener filtering significantly improved image quality, achieving a peak signal-to-noise ratio (PSNR) of 23.06 dB and a structural similarity index measure (SSIM) of 0.79 using the BreastDM dataset and a PSNR of 20.09 dB with an SSIM of 0.35 using the BUSI dataset. When combined filtering techniques were applied, the results varied, with the MIAS dataset showing a decrease in SSIM and an increase in the mean squared error (MSE), while the BUSI dataset exhibited enhanced perceptual quality and structural preservation. The vision transformer (ViT) framework excelled in processing complex image data, particularly with the BreastDM and BUSI datasets. Notably, the Wiener filter using the BreastDM dataset resulted in an accuracy of 96.9% and a recall of 96.7%, while the combined filtering approach further enhanced these metrics to 99.3% accuracy and 98.3% recall. In the BUSI dataset, the Wiener filter achieved an accuracy of 98.0% and a specificity of 98.5%. Additionally, the U-KAN model demonstrated superior performance in breast cancer lesion segmentation, outperforming traditional models like U-Net and U-Net++ across datasets, with an accuracy of 93.3% and a sensitivity of 97.4% in the BUSI dataset. These findings highlight the importance of dataset-specific preprocessing techniques and the potential of advanced AI models like ViT and U-KAN to significantly improve the accuracy of early breast cancer diagnostics. Full article

The aim of the study was to verify changes in peak power output (PPO), acid-base balance, blood lactate (La⁻) accumulation, and oxygen uptake (VO₂) whilst applying a 7.5% and 10% load of the participant’s body mass in a cycling sprint interval exercise (SIE) (two series consisting of 3 × 10 s efforts “all-out” separated by a 30 s active break). Twelve healthy, physically active men with maximal oxygen uptake (VO₂max = 52.4 ± 7.8 mL∙kg⁻¹∙min⁻¹) were included in the study and performed two cross-over SIE sessions, with a load of 7.5% of the participant’s body mass (SIE_7.5%) and 10% of the participant’s body mass applied (SIE_10%). The physiological, mechanical, and perceptual responses were assessed during and after each session. After SIE_10%, a 10.3% higher and 25.5% faster PPO time was obtained, with no significant differences in La⁻, a lower physiological cost (mean oxygen uptake and mean heart rate), faster restitution of VO₂ and heart rate, and a lower rate of perceived exertion. Therefore, a 10% load of the participant’s body mass during 10 s effort induced greater physiological adaptations and mechanical responses, which may promote the use of a higher workload in sprint interval training to improve physical performance. Full article

Optimizing accessibility to urban riverfront spaces plays a pivotal role in enhancing the spatial vitality of urban regions and promoting the high-quality development of such areas. The degree of riverfront space accessibility can be assessed through the connectivity of urban roads, which directly impacts the spatial vitality of these areas. This study constructs an axial and segmental model of the urban road network based on the space syntax theory. Through the Geographic Information System (GIS), kernel density analysis is performed on the Points of Interest (POI) and Depthmap data of Songxi County to comprehensively examine the reasonableness of the segmental network model and its visual representation. Quantitative evaluation of the accessibility of riverfront space in Songxi County from three dimensions, namely topological accessibility, geometrical accessibility, and perceptual accessibility, is conducted. The results show that (1) the accessibility of high-value area of riverfront space in Songxi County’s central city exhibits an unbalanced distribution, with a concentration in the central area. (2) A certain degree of mismatch exists between the distribution area of high accessibility in urban space and that of the waterfront space, highlighting the need for improved traffic planning in the riverfront area. (3) Weak spatial connections are shown between the north and south riverfronts, with areas of high accessibility values showing a clear break at the riverbank. Based on the results of the quantitative analysis, the proposed approach involves optimizing the spatial layout of urban roads and riverfront spaces through several key strategies. These strategies encompass enhancing the layout of the transport network, strengthening the coupling links between the two sides of the river, enriching the functions of the riverfront space, and conducting simulations to test the feasibility of these measures. The simulation results revealed a noteworthy enhancement in the integration and choice value of urban roads and riverfront spaces. Therefore, the optimization strategy employed in this study significantly improved the connectivity and accessibility of the overall transport network, leading to a more balanced distribution of high accessibility value areas within the city and riverfront space. This paper centers on the interaction between individuals and the river, to enhance the restoration of riverfront vitality. As a result, it is anticipated to provide valuable insights into the sustainable development of riverfront spaces. Full article