Search Results (131)

Insufficient physical activity (PA) and problematic smartphone use (PSU) frequently co-occur during adolescence, but whether their prospective association reflects stable differences between adolescents or within-person fluctuations remains unclear. This three-wave longitudinal study examined reciprocal prospective associations between PA and PSU in 1015 Chinese adolescents aged 12–18 years across 12 months, with assessments separated by approximately six months. PA was assessed using the Physical Activity Rating Scale-3, and PSU was assessed using the Smartphone Addiction Scale–Short Version. A random-intercept cross-lagged panel model (RI-CLPM) was specified as the primary analysis, with a conventional cross-lagged panel model (CLPM) estimated secondarily for comparison with previous longitudinal research. In the RI-CLPM, the stable between-person components of PA and PSU were negatively associated (β = −0.681, p = 0.004). At the within-person level, higher-than-usual PA was prospectively associated with lower-than-usual PSU at the subsequent wave (β = −0.117 and −0.108), whereas higher-than-usual PSU was prospectively associated with lower-than-usual subsequent PA (β = −0.257 and −0.189); all four cross-lagged paths were statistically significant. The secondary CLPM showed reciprocal negative cross-lagged associations in the same directions. By separating stable between-person differences from within-person deviations, this study extends longitudinal evidence on the PA–PSU relationship and indicates that the two behaviors are prospectively coupled within adolescents over time. These findings provide a basis for future research and intervention trials that consider PA and problematic smartphone behavior jointly, while causal mechanisms remain to be established. Full article

The widespread adoption of in vitro fertilization (IVF) has profoundly transformed the management of infertility and established IVF as the most effective assisted reproductive technology for many clinical indications. Nevertheless, intrauterine insemination (IUI) remains widely used because of its lower invasiveness, reduced treatment burden, lower costs, and broader accessibility. The contemporary role of IUI in an IVF-dominated era remains a subject of ongoing debate. This narrative review aims to critically evaluate the current role of IUI in modern reproductive medicine by examining its clinical indications, effectiveness, limitations, cost-effectiveness, and patient-centered implications in comparison with IVF. A narrative review of the literature was conducted using PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. Relevant studies, systematic reviews, meta-analyses, randomized controlled trials, and international guidelines published primarily between 2010 and 2025 were identified and synthesized. Particular attention was given to recommendations from the European Society of Human Reproduction and Embryology (ESHRE) and the American Society for Reproductive Medicine (ASRM). Current evidence supports the use of IUI, particularly when combined with ovarian stimulation, as an appropriate first-line treatment in selected couples with unexplained infertility, mild male-factor infertility, and minimal-to-mild endometriosis. Although IVF generally provides higher live birth rates per treatment cycle and remains the preferred option for several infertility diagnoses, IUI continues to offer meaningful clinical benefits in appropriately selected patients. Beyond effectiveness, treatment decisions should also consider cost-effectiveness, accessibility, treatment burden, safety, and patient preferences. Recent evidence increasingly supports individualized and prognosis-based approaches to fertility treatment selection. Evidence also highlights the importance of female age, infertility duration, and ovarian reserve in determining the relative benefit of IUI versus IVF. Despite the clinical dominance of IVF, IUI remains an evidence-based and clinically relevant component of contemporary fertility care. Rather than being viewed as competing interventions, IUI and IVF should be considered complementary treatment options within a personalized infertility management strategy. Appropriate patient selection, particularly considering female reproductive prognosis, remains essential to maximize reproductive outcomes while minimizing treatment burden and healthcare costs. Full article

This exploratory case study assesses ecotourism adaptability across three zones within the proposed Southwest Karst National Park (Guangxi), where UNESCO-recognised geological heritage intertwines with diverse ethnic cultures. To fill the gap in zone-specific integrated assessment frameworks, we employed a two-stage entropy-weighted TOPSIS method—calibrated via Delphi-AHP adjustments within a Social-Ecological Systems framework—using 2023–2024 data, complemented by ethnographic observations. Preliminary results indicate divergent trajectories: the Tiankeng zone exhibits high geological uniqueness and market appeal (composite score 0.74); the Mulun zone shows relatively balanced social–ecological coupling (0.58); and the Underground River zone displays pronounced asymmetry between vulnerability and development potential (0.16). Accordingly, tentative daily visitor caps of 3000, 8000, and 14 persons, respectively, and a pilot adaptability alert threshold of 0.20 for this specific case are proposed. These findings reveal a “vulnerability–capacity inverse matching” dynamic, informing differentiated governance: high-adaptability zones may allow moderate tourism with real-time monitoring, whereas low-adaptability zones require strict conservation-first measures and phased institutional capacity-building prior to any development. This preliminary framework offers actionable insights for sustainable management, conceptually aligned with SDG 11.4 and SDG 15.9. Full article

Depressive symptoms and cognitive functioning are intertwined in later life, but it is unclear whether their time-ordered associations differ by grandparenthood status. Using SHARE (2006–2022) data from adults aged ≥50 with consecutive observations, we fit lagged linear mixed-effects models with person-specific random intercepts and autoregressive adjustment, controlling for sociodemographic and health covariates and the time between waves. Higher prior EURO-D scores predicted slightly lower subsequent cognitive performance, and higher prior cognition predicted fewer subsequent depressive symptoms; in both directions, cross-domain effects were small relative to within-domain stability. Domain-specific analyses indicated the most consistent prospective links for memory and orientation, with weaker evidence for numeracy. Grandparenthood (having grandchildren) was not associated with the cognitive composite but was associated with slightly lower depressive symptoms. As a secondary aim, interaction models tested whether grandparenthood moderated the lagged associations; interactions were small and sensitive to specification, suggesting modest heterogeneity (including a crossover pattern for cognition predicting depression) rather than a uniform “enrichment” effect. Overall, depressive symptoms and cognition show modest bidirectional prospective links, and grandparenthood status marks limited, non-causal differences in affect–cognition coupling within an observational design. Full article

Thoracic morphology is increasingly recognized as an important determinant of cardiopulmonary phenotype, influencing cardiovascular mechanics, respiratory physiology, and the interpretation of diagnostic imaging findings. Although the radiological Haller Index (HI) remains the reference standard for quantifying pectus excavatum severity, its dependence on computed tomography and ionizing radiation limits widespread clinical implementation, particularly in settings requiring serial evaluations. To overcome these limitations, the Modified Haller Index (MHI) was developed as a simple, non-invasive, radiation-free alternative that combines external thoracic anthropometry with echocardiographic assessment. Since its introduction, the MHI has undergone clinical validation and has progressively expanded beyond the assessment of chest wall deformities, demonstrating that thoracic conformation is not merely an anatomical characteristic but a clinically relevant determinant of cardiovascular and respiratory physiology. Growing evidence indicates that thoracic morphology influences cardiac chamber geometry, ventricular filling, stroke volume, myocardial deformation, ventricular–arterial coupling, exercise stress echocardiography findings, pulmonary function, and symptom perception across a broad spectrum of cardiovascular and respiratory diseases. Elevated MHI values identify individuals with a reduced antero-posterior thoracic diameter and a distinctive cardiopulmonary phenotype characterized by external cardiac compression, smaller cardiac chambers, restrictive ventilatory physiology, and apparent alterations in myocardial mechanics despite the absence of intrinsic myocardial disease. Building upon the clinical validation of the MHI, a novel patented anatomical measurement device was engineered to standardize thoracic morphometric assessment by enabling direct acquisition of both latero-lateral and antero-posterior thoracic diameters within a single measurement procedure. The device integrates dedicated anatomical reference elements, an innovative adjustable sternal pointer, movable measurement components, and a standardized acquisition workflow into a portable, low-cost, and radiation-free platform, thereby improving measurement reproducibility while simplifying bedside MHI determination. This narrative review summarizes the historical evolution of thoracic morphometry, the development and clinical validation of the MHI, the engineering rationale, structural architecture, and measurement workflow of the patented device, and the growing evidence supporting the clinical significance of thoracic conformation across cardiovascular and respiratory medicine. Together, the MHI and the proposed anatomical measurement device establish a practical platform for standardized, radiation-free thoracic morphometry that may facilitate routine bedside phenotyping. Future integration with digital technologies, artificial intelligence, and advanced imaging systems may further enable next-generation digital thoracic phenotyping for personalized cardiovascular and respiratory characterization, risk stratification, and precision medicine. Full article

Stationary human–structure interaction (HSI) can significantly modify the vibration characteristics of lightweight structures, yet it remains unclear whether a human model identified for an individual can be extended consistently to crowd conditions. This study investigates this issue through sweep-frequency tests on a single-degree-of-freedom (SDOF) rig under single-person standing, single-person seated and two- to five-person standing group conditions. The measured acceleration frequency response functions (FRFs) were fitted using a two-degree-of-freedom (2DOF) integrated HSI model to identify equivalent human/crowd and structural parameters. The experimental program involved 20 participants and 180 tests, yielding 40 averaged individual datasets and 50 averaged group-combination datasets. Clear double-peak FRF characteristics were observed under all occupied conditions, indicating coupled 2DOF behavior rather than a simple added-mass effect. Compared with seated occupants, standing occupants showed a slightly higher equivalent human natural frequency (6.76 Hz versus 6.45 Hz), but lower human damping ratio (23.37% versus 31.73%) and body mass ratio (BMR) (0.621 versus 0.729). For standing groups, the equivalent crowd damping ratio increased from 24.60% for the two-person group to 29.10% for the five-person group, and BMR increased from 0.66 to 0.80, whereas the equivalent crowd natural frequency remained within 6.74–7.02 Hz. These results support a unified but parameter-dependent 2DOF framework for stationary individuals and crowds, provided that posture- and crowd-dependent parameters are identified from the overall coupled-system FRF rather than obtained by direct averaging of individual properties. Full article

Recently introduced affect-driven UAV controllers model behavioral sensitivity (α) as a static personality-dependent parameter, overlooking the cumulative influence of prolonged operational context. The Pull–Push Engine (PPE) regulates behavioral responses through bounded temporal integration; however, its effective sensitivity remains fixed during execution, limiting adaptive evolution under cumulative operational exposure. To overcome this limitation, this paper introduces the Digital Hormone Layer (DHL), a bounded neuroendocrine-inspired regulatory mechanism that dynamically modulates the PPE’s effective sensitivity α_eff. In DHL, three scalar hormones inspired by cortisol-, dopamine-, and oxytocin-regulatory motifs accumulate operational context on a medium timescale. In the evaluated scenarios, the behavioral effect is primarily stress-driven, while reward and operator-engagement channels remain architecturally defined but contribute less prominently. Modulation is constrained within a personality envelope by coefficient construction (Personality Preservation Budget (PPB) ρ = 0.20). On emergency events, the DHL-augmented controller responds up to 1.91× faster under multi-stressor exposure relative to the activation-selectivity (EI-Low, α = 0.495) control (95% bootstrap confidence interval [1.70×, 2.14×]). This indicates the advantage arises from the bounded adaptive DHL trajectory, not from a low steady-state α-value. This interpretation is consistent with the implemented per-step hormone-to-sensitivity coupling, observed as an inverse correlation between accumulated stress and effective sensitivity. Mission-final and total in-flight battery consumption are comparable across the single-agent controllers; no battery-efficiency advantage is claimed. A single-equation multi-agent extension shows that increasing the coupling coefficient reduces inter-agent sensitivity distance from 0.00502 (uncoupled, γ = 0) to 0.00243 at γ = 0.50 (95% CI [0.00225, 0.00261]; a 51.6% reduction; one-way ANOVA F = 82.5, p < 0.0001) while both agents remain within the personality envelope, as evidence of bounded inter-agent coupling; system-level multi-agent properties remain to be evaluated. Full article

In recent decades, low birth rates, delayed parenthood, and a decline in the average number of children per couple have become prevalent issues, sparking growing scientific interest in understanding their causes. While cultural, social, and gender-related factors have been widely examined, work-related dimensions remain underexplored within work and organizational psychology. This qualitative study explores how individuals make sense of the interplay between perceived work-related factors (specifically, working conditions, organizational culture, the work-family interface, and career ambitions) and declared fertility intentions. Semi-structured interviews were conducted with 33 participants (22 women; 19 without children, 14 with one child; aged 24–45). A subtle realist positioning was adopted, and template analysis was employed to examine the data. The findings highlight how participants interpret multiple work-related dimensions as relevant to their fertility intentions, including high job demands, job insecurity, and family-unfriendly organizational cultures. Concerns about work-family conflict also emerged as central. At the personal level, career ambitions and self-efficacy were identified as key dimensions. Notably, the perception of career-parenthood interference is often associated with limited or postponed decisions about having children. This study contributes to a better understanding of the work-related dimensions that can contribute to shaping fertility intentions and offers practical recommendations for interventions. Full article

Background/Objectives: Persons living with dementia (PLwD) receive informal care services from loved ones, commonly referred to as care partners (CPs). While the symptoms (e.g., depressive affect, cognitive impairment) experienced by PLwD are recognized to influence CP wellbeing, longitudinal investigations into the association of CP QoL and PLwD symptoms have yet to be fully explored. The present study sought to address this gap and highlight how CP QoL and PLwD symptoms systematically covary over time. Methods: Participants were composed of 33 dyads (PLwD and their CP) who partook in the Voices in Motion project, a social-cognitive intervention for dementia. CP QoL (WHOQOL-BREF), PLwD depressive symptomology (Patient Health Questionnaire-9) and PLwD global cognitive functioning (Mini-Mental State Examination) were assessed every three to four weeks in an intensive repeated-measures design. Time-varying covariation models using multilevel modeling examined systematic covariation between CP QoL and PLwD symptoms between and within dyads. Results: Increased CP psychological and social QoL were both associated with increased PLwD global cognitive functioning between dyads and vice versa (p < 0.05). Within dyads, increased CP social QoL was associated with improved PLwD depressive symptoms (p < 0.05), while increased CP environmental QoL was associated with increased depressive symptoms (p < 0.05). Conclusions: Significant coupling associations were observed both between and within dyads. Such results highlight the association between CP QoL and the symptoms experienced by their care recipient and provide important, novel longitudinal contributions to the literature. Full article

Melanoma is the most aggressive type of skin cancer, driven by early invasion, phenotypic plasticity, and frequent resistance to targeted therapies. Although genomic profiling informs treatment selection, genotype alone often fails to predict therapeutic response, underscoring the need for rapid and physiologically relevant functional testing platforms. Here, we present a three-dimensional melanoma–skin organoid (mSO) model that integrates primary skin cells with melanoma cell lines in a self-assembling, high-throughput format. The spherical mSOs recapitulate native human skin architecture, including a stratified epidermis and a dermal–hypodermal core, while supporting melanoma growth within an appropriate tissue microenvironment. In this niche, melanoma cells display epidermal spreading in radial growth-like patterns, outward invasion, and transcriptional shifts toward a pro-invasive phenotype. Using live confocal imaging coupled with a custom automated image analysis pipeline, we quantitatively measured tumor growth, migration beyond the organoid boundary, and interactions between melanoma cells and normal melanocytes. The mSOs also captured genotype-specific drug responses: BRAF-mutant melanoma cells were sensitive to BRAF and MEK inhibition, whereas NRAS-mutant, BRAF–wild-type cells were resistant to BRAF inhibition but remained responsive to MEK inhibition. Altogether, our mSO platform combines architectural and functional complexity with experimental scalability, providing a robust framework for modeling melanoma progression and evaluating targeted therapeutic responses within a relevant skin microenvironment. In the future, adaptation of this system to include patient-derived tumor cells could support personalized therapeutic decision-making in melanoma. Full article

Various industry organisations point to a pressing need for future employees to master a variety of soft skills. These include skills such as communication, empathy, active listening, flexibility, and so on. As higher education institutions have noted this industry need, they are dedicating more attention to integrating the development of these skills throughout their curricula. However, they are faced with several organisational challenges in doing so. Immersive virtual reality has been identified as a promising avenue to address both industry need and higher education challenges. In this study, we investigate the perceptions of higher education instructors of IVR technology for soft skills training, using Bodyswaps software. A total of 103 instructors from 45 higher education institutions across five countries participated in our study, via self-selection within a vendor-coupled, grant-driven deployment. An extended UTAUT2 research model was adopted to investigate their perceptions. Next, we asked them to rate commonly cited educational affordances of IVR technology, further detailing the concept of performance expectancy. The results indicate that our research model could account for 57% of the explained variance and show that performance expectancy, facilitating conditions, and personal innovativeness significantly affect the behavioural intention to use. No significant moderating effects of age, gender, or prior IVR experience could be retrieved. Despite the limitations of self-selection recruitment bias in this grant-driven study, our findings provide both theoretical and practical contributions, following the ecological validity of this study. Several directions for future research are formulated. Full article

Complex knowledge work depends on individual output and on public exchanges that document problems, evaluate contributions, route expertise, and preserve reusable knowledge. Software work makes this infrastructure unusually visible through GitHub issues, reviews, comments, mentions, and cross-project ties. As generative AI coding tools become private, on-demand sources of task support, it is unclear whether productive output remains tightly coupled with participation in this GitHub-visible public knowledge infrastructure. This study examines that question using a balanced panel of approximately 38,000 freelance developers on GitHub observed quarterly from 2019 to 2025 (approximately 1,080,000 person-quarter observations), estimating within-person changes in the association between a Productivity Index and a Social Connectivity Index. Two-way fixed effects models estimate a substantively large weakening after mid-2022 (−0.138 SD, about 44 percent of the pre-AI slope), and the pattern remains stable across alternative operationalizations, model specifications, and sample definitions. A survey-linked subsample (n = 237) provides individual-level triangulation: the weakening aligns with developers’ self-reported AI adoption dates, and heavier AI users exhibit larger decoupling. Decomposition by exchange function is selective: public exchanges with more direct private AI support pathways (information seeking, troubleshooting, preliminary evaluation) weaken more than exchanges anchored in contextual judgment and new-tie formation. This study documents a large-scale behavioral decoupling between productive output and visible GitHub-based public knowledge-infrastructure participation in a real-world problem-solving setting. The pattern is consistent with cognitive offloading as one micro-level pathway, while direct process evidence is left to future work. Full article

Empathetic dialogue systems built upon large language models overwhelmingly adopt a monolithic inference paradigm that processes emotion perception, causal reasoning, memory retrieval, and response planning within a single forward pass without architecturally enforced intermediate representations, forfeiting intermediate-state transparency and long-horizon personalization. Drawing on neuroscientific and cognitive–psychological evidence that human empathy is functionally dissociable, we present MOSAIC (Multi-agent Orchestration with Structured Affective memory for Interpretable empathiC dialogue), a training-free framework that operationalizes empathetic dialogue as a four-stage cognitive pipeline: affective perception, causal appraisal, episodic memory retrieval, and response synthesis. Three innovations distinguish MOSAIC from prior work: (1) a cognitively motivated modular architecture whose functionally dissociable stages enable post hoc failure attribution through logged intermediate states; (2) a hierarchical three-tier emotional memory—perceptual, semantic, and episodic—coupled with adaptive three-dimensional retrieval over emotion, situation, and coping-strategy cues; and (3) a heterogeneous model orchestration strategy coordinating open-source and API-accessible models through role-specific chain-of-thought prompts, requiring no task-specific fine-tuning. We note that the EmpatheticDialogues evaluation pre-populates the memory store with 200 training-split episodes prior to test-set interaction, a data-access asymmetry relative to single-model baselines that must be borne in mind when interpreting comparative results. Experiments on EmpatheticDialogues and ESConv show that MOSAIC achieves a 76.4% weighted F1 and an empathy score of 3.87 (on a 1–5 Likert scale) and that it improves over single-model, training-free baselines on aggregate empathy and—most prominently—on human-rated personalization (3.67 vs. 3.24 against Claude-3.5 five-shot, $d=0.48$). We caution that the comparison against training-free baselines is not data access-controlled (see the cold-start discussion in Methods); the personalization advantage, supported by the ablation without the Event Agent, is the result we treat as the primary practical contribution of this work. Full article

This article analyses how capacity building programmes interact with structural constraints in mission-oriented climate policy, focusing on the Italian pilot Let’sGOv (GOverning the Transition through Pilot Actions) within the EU Mission “100 Climate-Neutral and Smart Cities by 2030”. Using an iterative, reflexive methodology (document analysis, direct observation, and qualitative analysis of questionnaires, workshop outputs, and online training feedback), it examines how municipal actors experience and reinterpret capacity building across three coupled dimensions: internal organisational capacity, external stakeholder relations, and multilevel governance interfaces. The empirical setting is a network of nine Italian Mission Cities (Bergamo, Bologna, Florence, Milan, Padua, Parma, Prato, Rome, Turin) supported by technical partners. The bench-learning pathway combined barrier diagnosis, an intensive in-person workshop, and a codesigned online curriculum structured around three thematic clusters (engagement, data, climate finance). Findings indicate that persistent barriers—departmental silos, resource and time scarcity, rigid human resources and procurement routines, asymmetric data access, and regulatory instability—are not removed by capacity building; rather, they are progressively articulated, specified, and reframed into actionable organisational and policy demands. Bench-learning strengthens diagnostic and relational capacities and enables modest institutional innovations (templates, protocols, internal task forces, shared policy briefs), while “hard” governance infrastructures largely remain unchanged. The paper argues that networked capacity building contributes to the emergence of nascent, project-dependent multilevel interfaces only when it supports collective negotiation with national actors and translates local experimentation into durable multilevel interfaces, mitigating risks of projectification and downward responsibility shifting. Full article

Breast cancer stem-like cells (bCSCs) fundamentally represent a highly dynamic “immune-adaptive functional state” rather than a fixed cellular lineage, serving as the core engine driving tumor recurrence, metastasis, and therapeutic resistance. Despite rapid advances, the heterogeneity of bCSC states and their intricate interactions with the immune microenvironment lack systematic integration. This review centers on the dynamic evolution and niche adaptation of bCSCs. First, we systematically dissect the multilayered regulatory network maintaining stemness, encompassing core transcription factors, epigenetic–metabolic coupling, and the synergistic mechanisms of critical signaling pathways such as Wnt and Notch. Second, we propose a trinary “stemness–immune–spatial” feedback model, elucidating how bCSCs achieve active immune evasion by downregulating antigen presentation, secreting immunosuppressive factors, and embedding within perivascular “immune-cold niches.” Finally, leveraging a multi-omics integration perspective, we reconstruct precision intervention strategies, exploring the synergistic potential of targeting stemness pathways in conjunction with immunotherapies like PD-1/PD-L1 blockade and STING agonists. Furthermore, we highlight the pivotal role of integrating organoids, PDX models, and AI-assisted decision systems in overcoming heterogeneity and enabling personalized treatment. By establishing a closed-loop framework spanning mechanistic insight to spatially precise intervention, this review aims to provide novel theoretical foundations and translational pathways to surmount the bottleneck of therapeutic resistance in breast cancer. Full article