This study aimed to investigate the relationship between fear of progression and post-traumatic growth in adults with lymphoma and determine whether avoidance coping mediates this relationship. This was a multicenter, cross-sectional study. We used convenience sampling to recruit 322 patients with lymphoma from four tertiary hospitals in Fujian and Anhui provinces, China, between February and August 2023. Participants completed demographic and clinical information questionnaires, the Fear of Progression Questionnaire-Short Form, the Medical Coping Modes Questionnaire, and the Post-traumatic Growth Inventory. Among Chinese patients with lymphoma, the total fear of progression, avoidance coping, and post-traumatic growth scores were 31.91 ± 8.29, 15.67 ± 3.07, and 59.45 ± 14.61, respectively. Fear of progression was positively correlated with avoidance coping, with no significant associations between fear of progression and post-traumatic growth. Avoidance coping was positively correlated with post-traumatic growth. Additionally, avoidance coping exerted a suppression effect between fear of progression and post-traumatic growth. Patients with lymphoma reported moderate-to-high fear of progression and high post-traumatic growth, alongside moderate avoidance coping. Fear of progression predicted post-traumatic growth, while avoidance coping suppressed this effect. These findings highlight the complex role of avoidance coping in psychological adaptation and underscore the need for further qualitative and research to explore its mechanisms in post-traumatic growth. The results offer valuable insights for developing culturally sensitive psychosocial interventions and coping assessments tailored to adults with lymphoma. Not applicable.
Accurately quantifying the inequality of plant organ size distributions, such as leaf area, is essential for understanding plant resource allocation strategies, and this is commonly achieved using Lorenz curves. Previous studies have shown that the performance equation (PE) and its generalized form (GPE) effectively describe Lorenz curves that are rotated 135 degrees counterclockwise around the origin and shifted rightward by 2 units. However, few studies have compared the fitting performance of PE (and GPE) with other traditional equations generating Lorenz curves in modeling empirical leaf area distributions, and even fewer have considered the validity of linear approximation assumptions in these nonlinear models. To address this gap, we quantified the inequality of leaf area distributions in Semiarundinaria densiflora, a bamboo species for which the abundant and measurable leaves per culm provide an ideal system for examining the ecological strategies underlying leaf allocation patterns. Five nonlinear models were employed to fit the leaf area distribution: PE, GPE, the Sarabia equation (SarabiaE), the Sarabia-Castillo-Slottje equation (SCSE), and the Sitthiyot-Holasut equation (SHE). Model performance was assessed using root-mean-square error (RMSE) and Akaike information criterion (AIC), while nonlinearity curvature measures were applied to evaluate the close-to-linear behavior of parameter estimates. In addition, the Lorenz asymmetry coefficient (LAC) was used to quantify the asymmetry of the Lorenz curves. Our results showed a clear trade-off between predictive accuracy and linear approximation behavior. Among the five models, GPE achieved the best fit, with the lowest RMSE and AIC values, yet did not show good close-to-linear behavior. In contrast, SHE provided the poorest fit but demonstrated the strongest close-to-linear properties. LAC values indicated that relatively abundant, larger leaves disproportionately contributed to the inequality in leaf area distribution. These findings highlight an inherent trade-off in using Lorenz-based models to describe leaf area frequency distributions: predictive accuracy does not necessarily align with statistical validity. By integrating model fit, nonlinearity diagnostics, and asymmetry assessment, this study provides new perspectives and methodological tools for future investigations into inequality in plant organ size distributions and their ecological significance.
In this study, bamboo-based hard carbon (HC) was selected as the research object, and a pre-oxidation strategy was employed to regulate the structure of the precursor. The effect of pre-oxidation time on the evolution of pore structure and sodium storage performance was systematically investigated. Structural analysis indicates that extending the pre-oxidation time facilitates the optimization of pore size distribution, promoting the collapse of mesopores and inducing the formation of closed pores. The as-prepared HC-12 h anode material delivers an initial discharge specific capacity of 498.2 mAh g−1 at a current density of 0.1 A g−1, with an initial Coulombic efficiency (ICE) of 84.3
Herein, we report a novel class of 2D organic-inorganic metal halides, An2CdCl4, based on anilinium chloride (An) and its Sb3+-doped derivatives An2CdCl4:x%Sb. This system overcomes limitations of existing long-persistent luminescent materials in color tunability and dynamic responsiveness. Through controlled Sb3+ doping, the material exhibits precise modulation of steady-state photoluminescence across blue, white, and yellow emission. Notably, it demonstrates remarkable room-temperature phosphorescence (RTP) and, for the first time in such materials, excitation-wavelength-dependent afterglow with continuous color gradation from blue to green and yellow. The corner-sharing [CdCl6]4- octahedral network, with halogen aggregation effects, induces multiple phosphorescent centers. Sb3+ doping enhances octahedral distortion and lattice rigidity and promotes energy transfer from triplet excitons of An+ to self-trapped excitons (STEs) at [SbCl6]3- sites. This synergy enables multimodal (fluorescence/phosphorescence) and multicolor responsive luminescence. Based on these photophysical properties, an advanced information encryption platform integrating wavelength-responsive patterns, time-resolved color codes, and magic cubes was constructed, demonstrating its potential for dynamic information encryption.
Leaf-shape variation significantly affects the robustness of the square relationship between leaf area and leaf length. Leaf area (A) for many broad-leaved plants is reported to be proportional to the product of leaf length (L) and width (W), which conforms with the Montgomery equation (ME), as shown by previous studies using leaves pooled from multiple individuals across species or from specific crown positions within a species. However, Thompson’s principle of similarity asserts that A ∝ L2, which is referred to as the square-law equation (SLE). Given that leaf functional traits can vary as a function of crown position, the ME vs. SLE inconsistency can be resolved by sampling all leaves for each plant to test the influence of plant size on leaf shape, size, and their variation across plants. In this study, we sampled 121 Semiarundinaria densiflora culms, measured the lamina area of every leaf, and above-ground height of each culm to examine the validity of the ME and SLE, and the influence of culm size on leaf shape, size, and their variation. The data show that (i) the ME provides a better goodness-of-fit than the SLE, (ii) leaf-shape variation reduces the reliability of the SLE, and (iii) mean leaf area increases with increasing culm height. Thus, culm height affects leaf shape, leaf area, and therefore affects the performance of SLE. These findings indicate that mixed sampling from plants differing in height can potentially lead to biased assessments of leaf functional traits.
