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Despite rapid advances in immersive technologies (AR, VR, and MR), many digital experiences struggle to sustain user participation. Prior research emphasizes technological realism while overlooking how structured interactions shape meaning-making and motivation. Drawing on interaction ritual chains (IRC) theory, this study introduces ritual interaction (RI)-comprising contextual elements, ritual symbols, scripted processes, and shared emotion-to examine its impact on participation intention. Using PLS-SEM, results show that RI influences participation through a sequential psychological process: it enhances immersion, which strengthens presence, ultimately driving participation intention. Immersion plays a more proximal role than presence. Moderation analysis indicates that experience type strengthens the effect of RI on immersion in culture-based, but not nature-based, environments. By shifting focus from technological affordances to interactional structure, this study highlights how structured interaction can motivate participation and informs the design of immersive systems while contributing to human-computer interaction and mediated social behavior research.

Children with a wide range of impairments such as cerebral palsy and childhood apraxia of speech can benefit from augmentative and alternative communication (AAC). When AAC is provided, it frequently focuses on improving basic pragmatic skills such as requesting or on early semantic skills such as vocabulary acquisition. To address this issue, the primary goal of this study was to evaluate the effects of implementing the AAC Generative Language Intervention (AAC-GLI) program on the aided expressive grammar of preschoolers with relatively intact receptive language skills who could benefit from AAC. A randomized controlled trial was used to evaluate the results. A total of 40 children who required AAC participated in the control group, intervention group, or both groups. The families of both the control and intervention group participants received a half-day AAC workshop. The intervention group also received 28 play-based AAC-GLI sessions. Weighted mean length of utterance in symbols (W-MLUSym), which was developed specifically for aided communicators, was used to measure progress. The intervention group demonstrated superior effects on W-MLUSym compared with the control group. Additionally, growth modeling demonstrated that the intervention condition was a significant moderator of change over time, with children in the intervention condition having statistically significantly greater increases in W-MLUSym, while W-MLUSym for children in the control condition remained similar to baseline. AAC-GLI can be used to teach preschoolers with a range of impairments to improve their expressive grammar skills. Providing AAC intervention that focuses on grammatical growth is an important part of expressive language development for these young children.

Digital technologies have fundamentally transformed workplace interactions, yet our understanding of how these tools reshape relational social capital, specifically trust dynamics, remains incomplete. Drawing on signaling theory and social exchange theory, this study examines how digital tool usage intensity influences two distinct dimensions of social capital: employees' feeling of being trusted and their trust in others. Using two-wave time-lagged survey data from 428 employees in Chinese organizations, we find that digital tools function as a double-edged sword: they foster social capital through communication quality and psychological safety, while introducing "social risks" via perceived digital surveillance and technostress. Our findings advance social capital theory in the digital age by distinguishing feeling trusted and trusting others as parallel yet distinct outcomes, and by demonstrating that technology implementation choices carry powerful symbolic meanings that can either build or erode the organizational social fabric.

Disability monitoring in multiple sclerosis (MS) relies on EDSS and MRI lesion metrics that are often insensitive to cognitive dysfunction and fatigue. To test whether memory-guided saccade (MGS) performance relates to processing speed and fatigue independent of mood symptoms, EDSS, and MRI inflammatory activity. Forty-four MS patients completed MGS eye tracking. Error types and Total Task Error Rate were related to the Symbol Digit Modalities Test (SDMT), fatigue impact, mood scales, EDSS, and MRI lesion measures (including 5-year new T2 lesions) using age- and sex-adjusted partial correlations with mood sensitivity analyses. Mean Total Task Error Rate was 21.5% (SD 20.6); delay errors predominated. Lower SDMT scores correlated with more delay errors (r = -0.47, p = 0.002) and higher Total Task Error Rate (r = -0.40, p = 0.008). Greater fatigue correlated with more omissions (r = 0.36, p = 0.018) and higher Total Task Error Rate (r = 0.35, p = 0.022). Associations persisted after mood adjustment. No relationships were observed with EDSS or new T2 lesions (all p > 0.1). Preliminary, exploratory associations were observed between MGS metrics and measures of processing speed and fatigue in MS, independent of EDSS and MRI lesion activity. These findings should be regarded as hypothesis-generating and support further investigation of MGS as a candidate functional digital biomarker in larger, prospective, controlled studies with longitudinal follow-up and test-retest reliability assessment.

This study examines path differences in abstract and figurative art comprehension between art and non-art majors among college students. Employing a phased mixed-methods approach, the qualitative phase utilized semi-structured interviews and thematic analysis to develop a "perception-emotion-context-reasoning/narrative-interpretation" comprehension model, which informed the creation of a quantitative scale. The quantitative phase employed this model as a framework for reliability and validity testing, alongside multi-group path analysis. It compared and refined the model across four scenarios ("abstract/concrete × art/non-art"). Results indicate that contextual factors play a pivotal "hub-and-spoke" role in artistic comprehension. Artistic groups leverage context to engage in abstract reasoning and narrative construction, producing symbolic and academic expressions. Non-artistic groups, however, are often emotion-driven or rely on subjective speculation, leading to everyday associations or comprehension barriers. Understanding abstract works relies on perception and emotion, which, through context, ascend to the symbolic level. Concrete works, supported by context, activate narrative and linguistic pathways. The study provides mutual validation across qualitative and quantitative dimensions, proposing pedagogical and exhibition insights such as tiered contextual cues, narrative scaffolding, and task-oriented observation. These approaches facilitate the transition from experiential to professional understanding, enriching cognitive processing theories of art comprehension and offering an actionable framework for aesthetic education and museum practice.

Adapting musical theater into film involves the mediation of performance language from stage to screen. While stage language depends on live singing, spatial ensemble, and performer-audience co-presence, screen language relies on framing, editing, and audiovisual control. Although musical theater film adaptation has attracted increasing scholarly attention, audience-based research on how this transformation is perceived remains limited, especially in Chinese and Anglo-American contexts. This study examines how stage language is transformed into screen language through four stage-to-screen cases: the musical theater Les Misérables, first staged in 1980, and its 2012 film adaptation; the musical theater Dear Evan Hansen, first staged in 2017, and its 2021 film adaptation; the original Chinese musical theater Jinsha, first staged in 2005, and its 2023 film adaptation; and the original Chinese musical theater The Long Night, first performed in 2021, and its 2022 screen version. Guided by the Cultural Adaptability Symbolic Stratification (CASS) model, the study adopts a mixed-methods approach combining case analysis, content analysis, questionnaires, and focus group discussions with 27 participants. The findings identify three pathways of transformation: Cinematic Translation, Direct Transplantation, and Fragmented Reconfiguration. Among them, Cinematic Translation generated the strongest audience engagement, especially in emotional immersion and narrative clarity. Direct Transplantation preserved visible stage conventions but often weakened narrative and emotional coherence. Fragmented Reconfiguration produced more variable responses, depending on viewers' interpretive expectations and familiarity with non-linear form. Some age-related tendencies also appeared within this sample, but these should be treated cautiously given the limited number of middle-aged and older participants. Overall, the study shows that successful adaptation depends less on preserving theatrical form than on cinematically reorganizing performance language. It also refines the application of the CASS model to performance analysis and offers practical insight into the adaptation of Chinese original musical theater works into musical theater film.

Identity is a multi-level integrative process involving coordinated development across affective, symbolic, and embodied systems-a process of progressive self-organization that is biologically paced, relationally embedded, and irreducibly enacted through lived experience. This paper proposes a three-level developmental framework-Emotional Validation, Conceptual Identity, and Integrated Identity-and examines the structural conditions under which symbolic development outpaces embodied integration. This dynamic arises across the full range of identity-reorganizing experiences: adolescence, migration, parenthood, career disruption, relational loss, and recovery from trauma, among others. Significant disruption to self-continuity, including trauma, provides high-contrast visibility of these processes, but the framework describes features of identity reconstruction that operate universally wherever substantial reorganization of self is required. Drawing on semiotic mediation theory, narrative identity research, and neurobiological integration frameworks, the paper introduces the concept of semiotic overextension to describe the premature consolidation of self-organization around symbolic coherence in the absence of behavioral reorganization. Contemporary environmental amplifiers-including digital tools and artificial intelligence-are addressed as current intensifiers of a structurally persistent developmental dynamic. The framework is situated within the broader tradition of cultural-developmental psychology and invites developmental and clinical scholars to reconsider assessment practices that conflate conceptual fluency with functional integration.

Forensic scientists, though crucial, are often overlooked in the "essential worker" discourse. This Perspective argues for their formal recognition as essential government personnel, aligning with federal definitions of essential and critical infrastructure workers. Their contributions are vital for timely criminal investigations, successful prosecutions, and protecting the innocent. Despite this, they operate within a "captive profession" under policing, lacking parity in pay, benefits, overtime, and furlough protections compared to sworn officers. The COVID-19 pandemic underscored these issues. While forensic laboratories were mandated to continue operations as part of the justice system's critical infrastructure, forensic staff often face budget cuts and hazardous work conditions while not being acknowledged for doing so. This highlights a systemic undervaluing of forensic science in public safety, where "life and limb" policing often overshadows scientific knowledge and methods that ensure accurate investigations, prevent wrongful convictions, reduce backlogs, and improve long-term public safety. Granting essential worker status to forensic scientists offers significant benefits for attracting and retaining professional personnel leading to sustainable staffing. Beyond mere symbolism, this acknowledgment is fundamental for establishing a sustainable, science-driven public safety infrastructure that values the contributions of technology and science as front-line and essential.

Hydration fluctuations affect brain structure, function, and cognition, but underlying neurobiological mechanisms remain unclear. This RCT investigated dose-dependent effects of water intake on multimodal MRI metrics and cognitive performance in young adults after 12-h water restriction. 64 healthy university students (18-23 years) underwent 12-h water restriction and were randomized to high (500 mL), medium (200 mL), low (100 mL) water intake, or control (no water). Urine osmolality was measured pre- and post-intervention. Multimodal neuroimaging included resting-state functional MRI (fALFF, ReHo) and structural MRI (VBM), plus cognitive assessments. Baseline measures post-restriction showed no group differences in hydration status, with 57.8% dehydrated. Post-intervention, the control group had highest urine osmolality, with significant differences among groups. The high-intake group showed most notable fALFF changes across multiple gyri vs. all groups, and higher ReHo signals in right orbitofrontal gyrus vs. low-intake/control groups. This group also had lower cerebrospinal fluid density in limbic lobe vs. medium-intake/control groups. The medium-intake group demonstrated higher gray matter VBM values in hippocampus, superior frontal gyrus, and putamen vs. high-/low-intake groups. No significant between-group cognitive differences emerged. However, within-group comparisons revealed improved symbol search across all intake groups, increased mental arithmetic span for high-/medium-intake groups, and enhanced mental arithmetic scores specifically in the high-intake group. This study preliminarily demonstrates that water intake following 12-h water restriction may improve hydration status to some extent in young adults, with observed changes in localized multimodal MRI metrics in specific brain regions and in select cognitive test scores compared with pre-intervention values; however, the correlations among these changes require further analytical validation. https://www.chictr.org.cn/showproj.html?proj=19279, identifier: ChiCTR-IOR-17011568.

Hydrogen is a promising energy carrier, yet its practical deployment is limited by the lack of storage materials that simultaneously achieve high storage capacity (w) and practical equilibrium pressure at room temperature (P eq,RT). Interstitial metal hydrides offer fast kinetics and favorable thermodynamics (high P eq,RT) but suffer from intrinsically low w. Here, we establish a physically interpretable, data-driven framework to uncover descriptor-property relationships in interstitial hydrides using a curated database of pressure-composition-temperature measurements (Digital Hydrogen Platform, DigHyd) and white-box symbolic regression. Strikingly, the analysis reveals a clear separation of governing mechanisms, in which w is governed by geometric and lattice conditions, captured by the average atomic radius (〈r M〉) and average thermal conductivity (〈κ〉), with an optimal regime of 〈r M〉 ∼ 1.47 Å and relatively low 〈κ〉. In contrast, P eq,RT is governed by elastic properties, captured by the average shear modulus (〈G〉) and average Poisson's ratio (〈ν〉), reflecting the role of lattice rigidity and mechanical compliance. These relationships are translated into compositional optimization pathways that follow the descriptor trends above, enabling the design of candidate materials with enhanced w under practical equilibrium conditions (P eq,RT ∼ 0.1 MPa). This work establishes a general, interpretable strategy for physics-informed design of energy materials systems.

Whether individual-level cognitive trajectories in Parkinson's disease are predictable remains unresolved. Here, we provide convergent evidence that measurement fidelity, rather than model complexity, governs the prediction ceiling. We evaluated ten machine learning paradigm families across 26 configurations in two independent cohorts-the Parkinson's Progression Markers Initiative (PPMI, N = 1018) and the National Alzheimer's Coordinating Center (NACC, N = 523). Motor subtype classification succeeded as a positive control (AUROC = 0.869), while cognitive trajectory prediction from the Montreal Cognitive Assessment remained uninformative (AUROC = 0.581) across all methods, including 42 genetic features. Synthetic experiments confirmed that models recover trajectories at high signal-to-noise ratios but collapse uniformly at levels present in clinical screening data. Replacing coarse screening with detailed neuropsychological tests improved prediction in both cohorts (PPMI: Symbol Digit Modalities Test AUROC = 0.725 vs. MoCA 0.596; NACC: Logical Memory AUROC = 0.684 vs. MMSE 0.648). Within-patient trajectory R² = 0.20 for MoCA domains confirmed that approximately 80% of score variance represents non-signal variance. These findings redirect the clinical AI agenda from algorithm development toward measurement innovation: higher-frequency, higher-fidelity cognitive instruments are necessary before individual-level prediction becomes feasible.

Studies have shown that non-symbolic numerosity processing can consistently predict arithmetic performance. Visual form perception has been assumed to be fundamental for both processing, but little empirical evidence has been found for the involvement of visual form perception in numerosity processing and arithmetic performance. The current investigation will examine whether individual dependence on visual properties in numerosity processing can account for substantial variation in arithmetic performance. A total of 6329 participants aged 6 to 87 years old were recruited and divided into nine age groups. The results showed that the total contour/perimeter dominates the numerosity processing for participants in each of the nine age groups. At the individual level, the dependence of total contour/perimeter in numerosity processing indexed by the regression coefficient was larger than the dependence of other visual properties. Importantly, the dependence of total contour/perimeter consistently contributed to the arithmetic performance in each age group. The score for figure matching fully accounted for the contribution of the dependence of total contour/perimeter to arithmetic performance. The findings convergently suggest that the extraction of contour information in dot arrays is fundamental for both numerosity processing and arithmetic performance, which may stem from the shared visual form processing.

This study evaluated the feasibility of smartphone-based ecological momentary assessment (EMA) to test middle-aged and older adults' cognition - via tasks of processing speed and cognitive control -with and without depression history. Participants aged 55-79 (n = 79; 31 with depression history, 48 never-depressed controls) completed a 14-day EMA protocol with three daily assessments. The relevant tasks were Symbol Match Task (SMT; processing speed) and Go/No-Go task (GNG; cognitive control). Feasibility was evaluated through completion rates and missingness. Generalized additive modeling was used to evaluate associations between depression and cognitive performance, including trajectories, controlling for age, sex, and education. Of the 3318 possible response sessions, 2181 GNG and 2311 SMT were completed, nearly 70%. Controls demonstrated higher daily completion (GNG: 2.15 vs. 1.69 sessions, p = 0.035) and lower missingness (28% vs. 44%, p = 0.035) than depressed participants. Across tasks, depression history was associated with slower response times, less accuracy, and reduced efficiency. Controls averaged 2071 ms on SMT versus 2342 ms for depressed participants. Both groups showed performance improvements over time, suggesting learning effects, with parallel trajectories indicating a model consistent with depression's stable impact on cognitive functioning. While adherence challenges do exist, especially for those with a history of depression, smartphone-based EMA appears feasible for cognitive assessment in older adults. Depression impacts processing speed and cognitive control in this these real-world settings, and deficits persist regardless of current presence of symptoms. These findings support EMA's ecological validity for evaluating cognitive function and its potential for informing targeted interventions in late-life depression.

The myth of racial democracy has contributed to the invisibility of racism as a determinant of social and health inequalities in Brazil. Despite the influence of racism on illness and mortality, there are still few studies that address it as a social determinant of health, and it is often treated as a secondary factor. This study conducted a scoping review to identify racism theories that explain its effects on the health of the Brazilian population. Four theories that position racism as a social determinant were identified: structural, institutional, vicarious, and anti-Black racism. These theories operate through historical, social, and symbolic processes that structure inequalities in interpersonal and institutional relationships. The findings show that racism negatively impacts the health of the Black population and reinforce the need for scientific production and formulation of public policies that address racial inequities, promote equity, and ensure human rights in the field of health. No Brasil, o mito da democracia racial contribuiu para a invisibilização do racismo como determinante das desigualdades sociais e de saúde no Brasil. Apesar da influência do racismo em adoecimentos e mortalidade, ainda são escassos os estudos que o abordam como determinante social da saúde, sendo frequentemente tratado como fator secundário. Este estudo realizou uma revisão de escopo com o objetivo de identificar teorias do racismo que expliquem seus efeitos sobre a saúde da população brasileira. Foram identificadas quatro teorias que posicionam o racismo como determinante social: racismo estrutural, institucional, vicário e antinegro. Tais teorias operam por meio de processos históricos, sociais e simbólicos que estruturam desigualdades nas relações interpessoais e institucionais. Os achados evidenciam que o racismo impacta negativamente a saúde da população negra e reforçam a necessidade de produção científica e formulação de políticas públicas que enfrentem as iniquidades raciais, promovam a equidade e assegurem os direitos humanos no campo da saúde. En Brasil, el mito de la democracia racial contribuyó a la invisibilidad del racismo como determinante de las desigualdades sociales y de salud en Brasil. A pesar de la influencia del racismo en la enfermedad y la mortalidad, todavía hay pocos estudios que lo aborden como determinante social de la salud y a menudo se le trata como un factor secundario. Este estudio realizó una revisión exploratoria con el objetivo de identificar teorías del racismo que expliquen sus efectos sobre la salud de la población brasileña. Se identificaron cuatro teorías que posicionan al racismo como un determinante social: el racismo estructural, el institucional, el vicario y el anti-negro. Estas teorías operan a través de procesos históricos, sociales y simbólicos que estructuran las desigualdades en las relaciones interpersonales e institucionales. Los hallazgos muestran que el racismo impacta negativamente la salud de la población negra y refuerzan la necesidad de producción científica y formulación de políticas públicas que aborden las inequidades raciales, promuevan la equidad y garanticen los derechos humanos en el campo de la salud.

Integrating spatial histology with multi-slide, multi-omics data is essential for deciphering tissue architecture and cellular dynamics at high resolution. However, incomplete modality overlap across sections hinders coherent integration and cross-condition analysis. Here, we present stMixer, an unsupervised framework that (i) employs self-looped cross-attention to jointly encode histological, molecular, and spatial features; (ii) implements a multi-modal metric learning module to achieve biologically coherent integration across sections; and (iii) uses a graph-guided, cluster-level voting algorithm to enable anatomically faithful label propagation. Benchmarking across six spatial modalities demonstrates that stMixer achieves superior scalability and accuracy in dimensionality reduction, batch correction, and label transfer. The framework accommodates large, heterogeneous datasets across tissues, species, and technologies. We further showcase its versatility in mosaic integration, pseudo-time inference, and cross-tissue knowledge transfer. Notably, stMixer uncovers transient thymic states overlooked by competing methods, resolves fine-grained cortical microstructures, and corrects anatomical mis-annotations through integration with single-cell reference. stMixer is available at https://github.com/YQX-code/stMixer/.

This dataset was collected during on-site fieldwork conducted in the district of Chinchero, located in the province of Urubamba, Cusco, Peru, a region internationally recognized for its rich Andean textile tradition rooted in Inca Culture heritage. The dataset comprises high-quality Photographic images of traditional handwoven Andean textile iconographies produced by local artisan communities. These images were captured directly at textile centers where the fabrics are woven, dyed and finished using ancestral techniques measuring authentic representation of colors, textures, and symbolic patterns under natural and controlled conditions. The dataset consists of 1358 images organized into 28 distinct classes, each corresponding to a specific textile iconography characteristic of the Chinchero tradition. The images are provided in a processed and curated format, facilitating organization enables systematic analysis of visual motifs that are often challenging to distinguish due to their intricate geometric patterns and cultural symbolism. The primary reuse potential of this dataset lies in its application to Artificial Intelligence (AI) and Machine Learning (ML) research focused on image classification, pattern recognition, and cultural heritage preservation. Researchers can leverage the dataset to develop and evaluate models capable of identifying and differentiating traditional Andean textile iconographies, addressing the growing difficulty faced by younger generations, local communities, and visitors in recognizing the cultural expressions. Additionally, the dataset supports interdisciplinary research in digital humanities, ethnography, textile studies, and cultural informatics contributing to the documentation and preservation of intangible cultural heritage. By making this dataset publicly available, this work aims to support the development of AI-driven tools for cultural preservation, educational applications, and heritage awareness, while fostering collaboration between researchers, technologists, and local artisan communities to safeguard ancestral knowledge for future generations.

This study uses a critical intellectual history perspective to examine letters between Renato Ferraz Kehl and Antonio Mendes Correia, who were active in eugenic discourse in Brazil and Portugal. This correspondence serves as a vehicle of scientific consecration, revealing a transatlantic field of asymmetric exchanges marked by disputes for prestige, editorial strategies and epistemic authority. Based on the categories of habitus and symbolic capital, the letters are seen as performative artifacts of eugenic rationality, located between the intimate and the institutional. Our analysis reveals not only the contents but also the silences and frustrations within this relationship, showing how eugenics was negotiated and instrumentalized in the Atlantic Luso-Brazilian Atlantic context. Este estudo analisa, sob uma perspectiva crítica da história intelectual, o intercâmbio epistolar entre Renato Ferraz Kehl e António Mendes Correia, protagonistas dos discursos eugênicos no Brasil e em Portugal. As cartas são tratadas como dispositivos de consagração científica, revelando um campo transatlântico de trocas assimétricas marcadas por disputas de prestígio, estratégias editoriais e autoridade epistêmica. Com base nas categorias de habitus e capital simbólico (Bourdieu), argumenta-se que essas correspondências funcionam como artefatos performativos da racionalidade eugênica, situando-se entre o íntimo e o institucional. A análise ilumina conteúdos explícitos, mas também silêncios e frustrações que permeiam essa relação, revelando como a eugenia foi negociada e instrumentalizada no contexto atlântico luso-brasileiro.

Structural MRI differences between late-onset multiple sclerosis (LOMS; onset&#x2009;&#x2265;&#x2009;50&#xa0;years) and adult-onset MS (AOMS) patients remain incompletely characterized, particularly regarding tissue damage distribution and relationship with clinical and cognitive outcomes. To compare the structural MRI profile of LOMS and AOMS patients within a multiparametric framework including age-matched healthy control (HC) groups, and to examine MRI-clinical associations. Forty LOMS patients, 195 sex- and disease duration (DD)-matched AOMS patients, and 175 age-matched HC (HC-LO&#x2009;=&#x2009;50; HC-AO&#x2009;=&#x2009;125) underwent 3&#xa0;T MRI and clinical-cognitive assessment. Analyses included white matter (WM) lesion volume (T2-LV) and distribution, volumetric measures, tract-based spatial statistics, and voxel-based morphometry. Voxel-wise analyses assessed group differences and associations with DD, Expanded Disability Status Scale (EDSS), and Symbol Digit Modalities Test (SDMT) (p&#x2009;<&#x2009;0.05, FWE-corrected). Both MS groups showed higher T2-LV, widespread WM microstructural abnormalities. and lower total, gray matter (GM), and deep GM volumes than age-matched HC (pFDR&#x2009;&#x2264;&#x2009;0.015). LOMS patients showed higher lesion frequency in the left superior longitudinal fasciculus (SLF) than AOMS patients (pFWE&#x2009;=&#x2009;0.003). Onset category&#x2009;&#xd7;&#x2009;disease status interaction revealed higher T2-LV (pFDR&#x2009;=&#x2009;0.005) and more pronounced regional GM atrophy in motor-insular-subcortical regions in the LOMS versus AOMS groups (pFWE&#x2009;&#x2264;&#x2009;0.040). In LOMS patients, longer DD correlated with higher lesion frequency in the left SLF and mean diffusivity in several WM tracts (pFWE&#x2009;<&#x2009;0.05). In AOMS patients, higher EDSS and lower SDMT scores related to higher lesion frequency in commissural tracts and thalamic-hippocampal atrophy (pFWE&#x2009;&#x2264;&#x2009;0.040). LOMS patients exhibit higher T2-hyperintense WM lesion burden and more pronounced regional GM atrophy than AOMS patients, despite similar DD and no detectable global GM differences, potentially reflecting combined MS-related damage and age-related processes shaping a more severe structural MRI profile.

Machine learning (ML) has emerged as a promising technique for nonlinear equalization in coherent optical communication systems. However, conventional ML-based equalization schemes typically rely on fixed network architectures and parameters, limiting the adaptability to dynamic link states such as varying launch powers and transmission distances. In this Letter, we propose a pre-monitoring-assisted deep cascaded network (DCN) for nonlinear equalization. A lightweight convolutional neural network (CNN) performs pre-monitoring by analyzing the received signal spectrum to identify link states, thereby selecting the optimal deep neural network (DNN) model for nonlinear equalization. Experimental demonstrations in a 28-GBaud PDM-16QAM system show that, at the optimum launch power for 250&#x2009;km transmission, the proposed scheme achieves a Q-factor gain of 2.01&#x2009;dB over linear equalization, with a computational complexity of 2885 real multiplications per symbol (RMpS).