Search Results (34)

(1) Background: Proactive health behaviors are key to reducing their burden and supporting healthy aging. (2) Methods: We analyzed five waves (2011–2020) of CHARLS data from 1343 middle-aged and older adults (≥45 years) with multimorbidity. An entropy weight method was used to create a composite score for proactive health behaviors, and group-based trajectory modeling identified behavioral trajectories. Multivariate logistic regression and Shapley value decomposition assessed determinants and their relative contributions. Generalized structural equation modeling and latent class analysis were applied to estimate direct and indirect effects across the full sample and key multimorbidity subgroups. (3) Results: Two trajectories emerged: a “declining group” (91.44%) and an “improving group” (8.56%). The improving group was more likely to include younger, urban individuals with higher education, retired status, smaller family size, and lower depression levels. Education (40.67%) and depressive symptoms (31.22%) were the strongest determinants of trajectory. Path analysis showed that higher education and retirement indirectly supported sustained proactive health behaviors by reducing depression. The direct and indirect effects varied across subgroups. (4) Conclusion: The proactive health behaviors of middle-aged and elderly patients with multimorbidity exhibit a declining trend. Future health policies and interventions should prioritize mental health. Full article

Monitoring bird activity at public roosts is essential for understanding stopover behavior during migration, assessing ecological change, and supporting conservation strategies. Existing weather radar-based roost detection methods primarily rely on high-reflectivity ring-shaped echoes, which can lead to missed detections when roost-related echo structures are weak or indistinct. To address this limitation, this study proposes a saliency-constrained multi-peak spectral approach for monitoring and identifying public bird roosts using weather radar. At the radar resolution-cell scale, a saliency-constrained multi-peak Doppler spectrum decomposition and classification method is developed. Mixed Doppler power spectra are decomposed into multiple independent subpeaks through spectral peak saliency detection, and spectral polarimetric features are utilized to identify bird-related subpeaks, yielding a set of bird motion subgroups within each resolution cell. On this basis, a Bird Roost Index (BRI) is introduced, which couples the number of bird subgroups with their radial velocity dispersion to quantitatively characterize the complexity of bird motion modes in local airspace. Finally, the proposed method is applied to operational S-band weather radar observations collected over the Dongting Lake Basin roosts region during the spring season. The results demonstrate that the BRI exhibits strong spatial consistency and coherent temporal evolution, enabling robust characterization of communal roosting activity. This confirms the robustness of the proposed approach and highlights its potential for operational monitoring of migratory bird communal roosts using weather radar spectral data. Full article

Background: Pain remains one of the most debilitating and prevalent symptoms in cancer patients. However, assessment based solely on subjective self-report tools is limited by cognitive impairment and the heterogeneous nature of cancer pain. Since evidence on the ability of physiological biosignals to discriminate cancer pain intensity and pain phenotypes in real clinical settings remains limited, this study explored the potential of biosignals to discriminate between pain intensity and pain type. Methods: Electrodermal activity (EDA) and electrocardiogram (ECG) signals were recorded in cancer patients using the BITalino (r)evolution board (sampling frequency 1000 Hz). EDA was processed to extract skin conductance responses (SCRs) using continuous decomposition analysis (CDA) and trough-to-peak (TTP) methods. Heart rate variability (HRV) features were extracted in both time and frequency domains, including low frequency (LF), high frequency (HF), and the LF/HF ratio. Non-parametric Kruskal–Wallis tests were performed to compare biosignal parameters across pain intensity (Numeric Rating Scale, NRS: low 1–3; medium 4–6; and high 7–10) and pain types (nociceptive, neuropathic, mixed, and breakthrough cancer pain—BTCP). Results: Data from 61 patients were analyzed. For EDA, the maximum skin conductance response amplitude (MaxCDA) significantly differed across intensity groups (p = 0.037). Post hoc analysis showed a significant difference between the low- and high-intensity groups (p = 0.015), with the low-intensity group exhibiting a higher mean MaxCDA (0.063 µS) than the high-intensity group (0.024 µS). Several EDA parameters were significantly associated with pain type. The number of SCRs (TTP) (p = 0.015) and maximum SCR amplitude (TTP) (p = 0.040) were significantly lower in the mixed pain group compared with the nociceptive and neuropathic groups. No HRV parameters showed significant associations with pain intensity or pain type. BTCP did not significantly affect any biosignal parameters. Subgroup analyses showed that EDA features discriminating mixed pain were preserved in patients without bone metastases, BTCP, or high opioid burden, whereas no clinical variable modified the association between biosignals and pain intensity and type. Conclusions: In this investigation, selected EDA parameters were associated with cancer pain intensity and pain type, whereas heart rate variability measures did not show significant discrimination under the present methodological conditions. These findings suggest that EDA may provide complementary information on pain-related autonomic alterations in oncology patients. However, biosignals should not be considered standalone indicators of pain, and their interpretation requires integration with clinical variables and pharmacological context. Further studies adopting multimodal and longitudinal approaches are needed to clarify their role in automatic pain assessment in cancer care. Full article

We propose and develop a unified framework for Weyl-type symmetry in von Neumann algebras. Motivated by recent automorphism-rigidity phenomena that identify finite Weyl groups inside automorphism groups of crossed products arising from lattice actions on homogeneous spaces, we introduce the Weyl group of an inclusion $W(M;B):={\mathrm{Aut}}_B\left(M\right)/{\mathrm{Inn}}_B\left(M\right)$, for a unital inclusion $B\subset M$ of von Neumann algebras, and investigate its structure across several rigidity regimes. Our main results (1) prove finiteness or triviality of $W(M;B)$ for large classes of nonamenable crossed products, including hyperbolic and product-type actions with spectral gap and malleability; (2) establish a subgroup-normalizer rigidity principle for inclusions $L(\Lambda )\subset L(\Gamma )$ that identifies ${\mathrm{Aut}}_{L(\Lambda )}\left(L(\Gamma )\right)$ with a discrete group controlled by $N_{\Gamma }(\Lambda )$; (3) show that permutation-type symmetry for product/tensor decompositions is the only possible nontrivial symmetry of the underlying group subalgebras; and (4) extend the analysis to type III factors via Maharam extensions and unique-Cartan phenomena, proving that $W(M;B)$ is discrete and often trivial, leaving only modular flows as outer symmetries. Consequences include new computations of outer automorphism groups, constraints on intermediate subalgebras, and classification consequences for crossed products and amalgamated free products. The methods combine Popa’s intertwining-by-bimodules, spectral-gap and s-malleable deformations, boundary/ucp-map rigidity, and groupoid/Cartan techniques. Full article

The rise in seasonal lifestyle tourism, characterized by winter-escape health and wellness stays and long-term leisure residence, has intensified peak–off-peak imbalances and pressures on the allocation of tourism service supply in tropical island destinations. However, existing research lacks a systematic comparison of seasonal fluctuations and long-term evolution for this subgroup at the city/county level. Therefore, this study aims to characterize the seasonal pattern, long-term trend features, and typological differentiation of seasonal lifestyle tourism at the county level, and to compare differences across types. Using monthly data on seasonal lifestyle tourism for 18 cities/counties in Hainan from 2021 to 2024, we apply TRAMO/SEATS decomposition to identify seasonal structures and measure seasonal amplitude and employ the Hodrick–Prescott (HP) filter to extract trend components and determine their directions of change. We further construct five development types by integrating trend categories and changes in seasonal amplitude and test between-type differences using one-way analysis of variance (ANOVA). Results show that Hainan exhibits a stable “winter–spring peak and summer–autumn trough” pattern (peaks concentrated in January–March and December, with the off-season typically spanning May–October), with strong seasonality and pronounced spatial heterogeneity. The four-year mean seasonal range at the county level is 215.01, with high values clustered in southern Hainan; Haikou remains relatively low, while Wenchang shows an upward trend. Long-term trends are clearly differentiated: 13 counties show sustained growth, 2 show decline, and 3 display a U-shaped recovery (decline followed by rebound). Growth rates also vary substantially, with Qionghai increasing at roughly 27 times the rate of Qiongzhong. Integrating seasonal and trend characteristics yields five types, of which the Robust Development type accounts for the largest share (50%). Between-type differences are mainly reflected in tourism service supply capacity: the number of star-rated hotels (p = 0.033, η² = 0.530) and overnight visitors (p = 0.004, η² = 0.676) differ significantly across types, whereas differences in natural-environment conditions are not significant. This study provides a scientific basis for zoning management and optimizing low-season strategies in Hainan. Full article

Background: Rotating and night-including shifts disrupt circadian alignment, impair sleep, and may reduce nurses’ physiological recovery. Objectives: This study aimed (1) to compare sleep quality and physical well-being across four shift schedules among hospital nurses and (2) to examine whether the association between rotating shifts and physical well-being was statistically consistent with an indirect association via sleep quality. Methods: In this cross-sectional study, 173 nurses from a tertiary hospital in Zagreb, Croatia, completed validated measures of sleep quality and physical well-being. Four shift patterns were analyzed—fixed morning, morning–afternoon, extended 12-h, and rotating three-shift—using Welch ANOVA and regression models. A bootstrapped mediation analysis (10,000 resamples; BCa method), interpreted as a statistical decomposition, estimated an indirect association consistent with sleep quality. Results: Rotating-shift nurses reported the poorest sleep (PSQI = 10.2 ± 2.6; p = 0.003). Physical well-being did not differ significantly across shift types (p = 0.08), although rotating-shift nurses had the lowest mean physical scores (24.3 ± 4.4). The rotating-shift subgroup was small (n = 16), limiting precision. The mediation analysis was statistically consistent with an indirect association between rotating shifts and physical well-being via sleep quality (ACME = −1.85, 95% CI −3.05 to −0.88; p < 0.001), while the proportion of the total association was imprecisely estimated. Conclusions: In this single-site cross-sectional sample, rotating night shifts were associated with poorer sleep and, on average, lower physical well-being; patterns were statistically consistent with an indirect association via sleep quality. Because exposure, mediator, and outcome were measured concurrently, these findings are hypothesis-generating and do not establish causality. Full article

Background: Health disparities research increasingly relies on complex survey data to understand survival differences between population subgroups. While Peters–Belson decomposition provides a principled framework for distinguishing disparities explained by measured covariates from unexplained residual differences, traditional approaches face challenges with complex data patterns and model validation for counterfactual estimation. Objective: To develop validated Peters–Belson decomposition methods for survival analysis that integrate ensemble machine learning with transfer learning while ensuring logical validity of counterfactual estimates through comprehensive model validation. Methods: We extend the traditional Peters–Belson framework through ensemble machine learning that combines Cox proportional hazards models, cross-validated random survival forests, and regularized gradient boosting approaches. Our framework incorporates a transfer learning component via principal component analysis (PCA) to discover shared latent factors between majority and minority groups. We note that this “transfer learning” differs from the standard machine learning definition (pre-trained models or domain adaptation); here, we use the term in its statistical sense to describe the transfer of covariate structure information from the pooled population to identify group-level latent factors. We develop a comprehensive validation framework that ensures Peters–Belson logical bounds compliance, preventing mathematical violations in counterfactual estimates. The approach is evaluated through simulation studies across five realistic health disparity scenarios using stratified complex survey designs. Results: Simulation studies demonstrate that validated ensemble methods achieve superior performance compared to individual models (proportion explained: 0.352 vs. 0.310 for individual Cox, 0.325 for individual random forests), with validation framework reducing logical violations from 34.7% to 2.1% of cases. Transfer learning provides additional 16.1% average improvement in explanation of unexplained disparity when significant unmeasured confounding exists, with 90.1% overall validation success rate. The validation framework ensures explanation proportions remain within realistic bounds while maintaining computational efficiency with 31% overhead for validation procedures. Conclusions: Validated ensemble machine learning provides substantial advantages for Peters–Belson decomposition when combined with proper model validation. Transfer learning offers conditional benefits for capturing unmeasured group-level factors while preventing mathematical violations common in standard approaches. The framework demonstrates that realistic health disparity patterns show 25–35% of differences explained by measured factors, providing actionable targets for reducing health inequities. Full article

This paper provides advances in the study of principal $\mathrm{SO}\left(3\right)$-bundles over smooth projective real curves, with applications to robot manipulation orientation. The work introduces a novel specific classification of these bundles, establishing a bijection between isomorphism classes and specific direct sums of cyclic groups. The explicit computation of the cohomology ring $H^{*}(P,\mathbb{Z})$ for a principal $\mathrm{SO}\left(3\right)$-bundle P over a real curve X, revealing its complete structure and torsion subgroups, is a major contribution of the paper. This paper further demonstrates that the equivariant cohomology $H_{\mathrm{SO}\left(3\right)}^{*}(P,\mathbb{Z})$ is isomorphic to $H^{*}(X,\mathbb{Z})\otimes H^{*}(B\mathrm{SO}\left(3\right),\mathbb{Z})$, with implications for connections and curvature. These results are then applied to robotics, showing that for manipulators with revolute joints, a principal $\mathrm{SO}\left(3\right)$-bundle encoding end-effector orientation whose second Stiefel–Whitney class characterizes the obstruction to continuous orientation control exists. For robots with spherical wrists, the configuration space factors as a product, allowing for the decomposition of connections with control implications. Finally, a mechanical connection is constructed that minimizes kinetic energy, with its curvature identifying configurations where small perturbations cause large orientation changes. Full article

The understanding of the properties of multipartite systems is a long-standing challenge in quantum theory that signals the need for new ideas and alternative frameworks that can shed light on the intricacies of quantum behavior. In this work, we argue that symmetric spaces provide a common language to describe two-qubit and two-mode Gaussian systems. Our approach relies on the use of equivalence classes that are defined by a subgroup of the maximal symmetry group of the system and involves an involution which enables the Cartan decomposition of the group elements. We work out the symmetric spaces of two qubits and two modes to identify classes which include an equal degree of mixing states, product states, and X states, among others. For three qubits and three modes, we point out how the framework can be generalized and report partial results about the physical interpretations of the symmetric spaces. Full article

There are differences in the litter quality and decomposition rate of kiwifruit varieties, but it is not clear whether these differences are related to microbial communities. The leaf litters of two kiwifruit varieties (A. chinensis cv ‘Hongyang’ and A. chinensis cv ‘Jinyan’) were taken as objects, and the structure, diversity, and succession of the soil microbial communities were analyzed using an in situ decomposition experiment. Moreover, the contents of C, N, P, and K in the litters during decomposition were analyzed. The results show that there were variety differences in community structure at the generic level. Lophotrichus, Acaulium, and Fusarium were relatively more abundant in the microbial community of the ‘Hongyang’ kiwifruit litter, and Humicola and Tausonia were relatively more abundant in the microbial community of the ‘Jinyan’ kiwifruit litter. Subgroup_6 and Sphingomonas were the dominant bacteria. The bacterial community diversity of ‘Jinyan’ kiwifruit was higher than that of the ‘Hongyang’ kiwifruit litter. The community diversity was higher in the middle and later periods. The contents of C and N in the litters were the main factors affecting microbial communities. The abundances of Humicola and Apiotrichum were negatively correlated with the contents of C and N, and the abundances of Sphingomonas and SC-I-84 were positively correlated with the content of C. There were variety differences in the microbial communities corresponding to the decomposition processes of the ‘Hongyang’ and ‘Jinyan’ kiwifruit litters. The mechanisms of the variety differences were related to litter quality and the initial soil microbial community. Full article

The Zernike representation of wavefronts interlinks low- and high-order aberrations, which may result in imprecise clinical estimates. Recently, the Gatinel–Malet wavefront representation has been introduced to resolve this problem by deriving a new, unlinked basis originating from Zernike polynomials. This new basis preserves the classical low and high aberration subgroups’ structure, as well as the orthogonality within each subgroup, but not the orthogonality between low and high aberrations. This feature has led to conversions relying on separate wavefront reconstructions for each subgroup, which may increase the associated numerical errors. This study proposes a robust, minimised-error (lossless) analytical approach for conversion between the Zernike and Gatinel–Malet spaces. This method analytically reformulates the conversion as a nonhomogeneous system of linear equations and computationally solves it using matrix factorisation and decomposition techniques with high-level accuracy. This work fundamentally demonstrates the lossless expression of complex wavefronts in a format that is more clinically interpretable, with potential applications in various areas of ophthalmology, such as refractive surgery. Full article

This paper analyzes how export margins responded to an intermediate input supply shock caused by the 2020 lockdown in China. We use regression decomposition with triple and quadruple difference-in-differences models to identify causal impacts and mitigate potential heterogeneity in transaction-level customs data from the Bangladesh apparel manufacturing industry. The triple difference estimate shows that the average export value per firm–product–destination combination declined by approximately 65%, leading to a decrease in overall exports of woven apparel from Bangladesh. The input supply shock also adversely affected the subgroups of firms across various firm-level characteristics along the intensive margin. Moreover, the export market share decomposition reveals that the shock significantly affected intensive margins by decreasing incumbents’ market allocation by 9%. An equivalent increase in extensive margins led to a readjustment in the market allocation, leading to fewer market leavers and slightly more new market entrants. Our results indicate that Bangladesh’s exports mostly decreased due to the smaller quantities of products exported rather than there being fewer firms, destinations, or products involved in export trade. There were significant market share reallocations that occurred after the Chinese input supply shock. An appropriate policy stance is required for sustainable export sector growth strategies, which will enhance the country’s defense against potential future shocks and foster the achievement of sustainable development goals (SDGs) in Bangladesh. Full article

Perovskite-style materials are cathode systems known for their stability in solid oxide fuel cells (SOFCs). Pr_0.5Sr_0.5FeO_3−δ (PSF) exhibits excellent electrode performance in perovskite cathode systems at high temperatures. Via VB subgroup metals (V, Nb, and Ta) modifying the B-site, the oxidation and spin states of iron elements can be adjusted, thereby ultimately adjusting the cathode’s physicochemical properties. Theoretical predictions indicate that PSF has poor stability, but the relative arrangement of the three elements on the B-site can significantly improve this material’s properties. The modification of Nb has a large effect on the stability of PSF cathode materials, reaching a level of −2.746 eV. The surface structure of PSF becomes slightly more stable with an increase in the percentage of oxygen vacancy structures, but the structural instability persists. Furthermore, the differential charge density distribution and adsorption state density of the three modified cathode materials validate our adsorption energy prediction results. The initial and final states of the VB subgroup metal-doped PSF indicate that PSFN is more likely to complete the cathode surface adsorption reaction. Interestingly, XRD and EDX characterization are performed on the synthesized pure and Nb-doped PSF material, which show the orthorhombic crystal system of the composite theoretical model structure and subsequent experimental components. Although PSF exhibits strong catalytic activity, it is highly prone to decomposition and instability at high temperatures. Furthermore, PSFN, with the introduction of Nb, shows greater stability and can maintain its activity for the ORR. EIS testing clearly indicates that Nb most significantly improves the cathode. The consistency between the theoretical predictions and experimental validations indicates that Nb-doped PSF is a stable and highly active cathode electrode material with excellent catalytic activity. Full article

We demonstrate the emergence of an effective “time” axis in the ground state of a gauged rotational symmetry theory in four-dimensional Euclidean space. In so doing, we remove the necessity of Wick rotation to Lorentz spacetime, an arbitrary and sometimes ill-defined procedure, especially for gravity-related theories. We begin by adapting the Cho-Duan-Ge decomposition to the gauge theory of the four-dimensional rotational symmetry group $SO\left(4\right)$, where it identifies the maximal Abelian subgroup $SO\left(2\right)\otimes SO\left(2\right)$ in a gauge covariant manner. We then find the one-loop effective theory to have a stable condensate of monopoles corresponding to the reduction of $SO\left(4\right)$ symmetry to $SO\left(2\right)\otimes SO\left(2\right)$. The construction of the condensate ensures that the four-dimensional spatial direction of its field strength must coincide with that of this embedding, and that a magnetic potential must be worked against to divert a trajectory away from this direction. Indeed, movement along this direction represents minimal potential energy. We take it to be the time direction. The gauge-dependent nature of the condensate is such that different gauge choices may lead to different time axes and we show on very general grounds that these different coordinate systems must be relatable by transformations of Lorentz form. Full article

This study examines the impact of demographic shifts on income inequality among farm households over an 18-year period, from 2003 to 2021. Our principal aim is to determine whether changes in income inequality are driven more by intra-group changes in age/household size groups or by changes between these groups. Furthermore, the study aims to understand which age/household size groups are associated with changes in income inequality. The methodology of this study involves using the generalized entropy (GE) index, which allows for the decomposition of inequality within and between population subgroups. The study divides the total population into subgroups based on age and household size and analyzes both static and dynamic inequality. Results show that (i) the within-group effect for static farm income inequality is more significant than the between-group effect. (ii) On the other hand, for changes in inequality (dynamic inequality), the between-group effect in the case of age and the within-group effect in the case of household size are important. (iii) Changes in income inequality are more related to structural changes in the age group of farmers than to the size of household. Full article