Functional traits are important in understanding how plants respond and adapt to their immediate environment. Parrotia subaequalis is a highly endangered arbor species found throughout eastern China, primarily inhabiting hillsides and valleys, yet, little is known about the variation in leaf traits across these environments. In the present study, we tested this by comparing leaf surface area, leaf weight, leaf length, leaf symmetry and leaf mass per unit area, as well as the relationship between leaf traits and environmental factors and the scaling relationship between leaf surface area versus leaf dry mass. We observed significant differences in leaf surface area, weight, and length among the population sites, and these variables were strongly affected by environmental factors, especially high mean annual temperatures in hillside habitats and high mean annual precipitation in valley habitats. The scaling exponents remained numerically variant among the 10 populations, with different slopes greater than 1.0, and the scaling exponents increased significantly with hillside habitats. These metrics correlated with soil thickness associated with different habitat types. The areal ratio (AR) values in all populations deviated from 1, indicating that the two lamina sides were asymmetrical. The standardized symmetry index (SI) values displayed significant variation, especially in leaves from hillside habitats with a high degree of asymmetry. Collectively, our findings demonstrated that leaf functional traits exhibit considerable variability in response to different environmental contexts and provide valuable reference data that could be useful for conserving this endangered species.

BACKGROUND: Bursting nonsustained cardiac arrhythmia events are a common observation during sleep.
OBJECTIVE: The purpose of this study was to investigate the hypothesis that nocturnal arrhythmia episode durations could follow a power law, whose exponent could predict long-term clinical outcomes.
METHODS: We defined \"nocturnal arrhythmia avalanche\" (NAA) as any instance of a drop in electrocardiographic (ECG) template-matched R-R intervals ≥30% of R-R baseline, followed by a return to 90% of baseline. We studied NAA in ECG recordings obtained from the Sleep Heart Health Study (SHHS), Osteoporotic Fractures in Men Study (MrOS) Study, and Multi-Ethnic Study of Atherosclerosis (MESA). The association of nocturnal arrhythmia durations with a power-law distribution was evaluated and the association of derived power-law exponents (α) with major adverse cardiovascular (CV) events and mortality assessed with multivariable Cox regression.
RESULTS: A total of 9176 participants were studied. NAA episodes distribution was consistent with power-law vs comparator distributions in all datasets studied (positive log likelihood ratio of power-law vs exponential in MESA: 83%; SHHS: 69%; MrOS: 81%; power-law vs log-normal in MESA: 95%; SHHS: 35%; MrOS: 64%). The NAA power-law exponent (α) showed a significant association of with adverse CV outcomes (association with CV mortality: SHHS hazard ratio 1.39 [1.07-1.79], P = .012; MrOS hazard ratio 1.42 [1.02-1.94], P = .039; association with CV events: MESA HR 3.46 [1.46-8.21], P = .005) in multivariable Cox regression, after adjusting for conventional CV risk factors and nocturnal ectopic rate.
CONCLUSIONS: The NAA power-law exponent is a reproducible, predictive marker for incident CV events and mortality.

Scale-free brain activity, linked with learning, the integration of different time scales, and the formation of mental models, is correlated with a metastable cognitive basis. The spectral slope, a key aspect of scale-free dynamics, was proposed as a potential indicator to distinguish between different sleep stages. Studies suggest that brain networks maintain a consistent scale-free structure across wakefulness, anesthesia, and recovery. Although differences in anesthetic sensitivity between the sexes are recognized, these variations are not evident in clinical electroencephalographic recordings of the cortex. Recently, changes in the slope of the power law exponent of neural activity were found to correlate with changes in Rényi entropy, an extended concept of Shannon\'s information entropy. These findings establish quantifiers as a promising tool for the study of scale-free dynamics in the brain. Our study presents a novel visual representation called the Rényi entropy-complexity causality space, which encapsulates complexity, permutation entropy, and the Rényi parameter q. The main goal of this study is to define this space for classical dynamical systems within theoretical bounds. In addition, the study aims to investigate how well different time series mimicking scale-free activity can be discriminated. Finally, this tool is used to detect dynamic features in intracranial electroencephalography (iEEG) signals. To achieve these goals, the study implementse the Bandt and Pompe method for ordinal patterns. In this process, each signal is associated with a probability distribution, and the causal measures of Rényi entropy and complexity are computed based on the parameter q. This method is a valuable tool for analyzing simulated time series. It effectively distinguishes elements of correlated noise and provides a straightforward means of examining differences in behaviors, characteristics, and classifications. For the iEEG experimental data, the REM state showed a greater number of significant sex-based differences, while the supramarginal gyrus region showed the most variation across different modes and analyzes. Exploring scale-free brain activity with this framework could provide valuable insights into cognition and neurological disorders. The results may have implications for understanding differences in brain function between the sexes and their possible relevance to neurological disorders.

Cancer, a disease intimately linked to cellular mutations, is commonly believed to exhibit a positive association with the cell count and lifespan of a species. Despite this assumption, the observed uniformity in cancer rates across species, referred to as the Peto\'s paradox, presents a conundrum. Recognizing that tumour progression is not solely dependent on cancer cells but involves intricate interactions among various cell types, this study employed a Lotka-Volterra (LV) ordinary differential equation model to analyze the evolution of cancerous cells and the cancer incidence in an immune environment. As a result, this study uncovered the sufficient conditions underlying the absence of correlation in Peto\'s paradox and provide insights into the reasons for the equitable distribution of cancer incidence across diverse species by applying nondimensionalization and drawing an analogy between the characteristic time interval for the variation of cell populations in the ODE model and that of cell cycles of a species.

Dispersion of Basil seed gum has high viscosity and exhibits shear-thinning behavior. This study aimed to analyze the influence of microwave treatment (MT) at various time intervals (0, 1, 2, and 3 min) on the viscosity and rheological behavior of Basil seed gum dispersion (0.5%, w/v). The finding of this study revealed that the apparent viscosity of Basil seed gum dispersion (non-treated dispersion) reduced from 0.330 Pa.s to 0.068 Pa.s as the shear rate (SR) increased from 12.2 s-1 to 171.2 s-1. Additionally, the apparent viscosity of the Basil seed gum dispersion reduced from 0.173 Pa.s to 0.100 Pa.s as the MT time increased from 0 to 3 min (SR = 61 s-1). The rheological properties of gum dispersion were successfully modeled using Power law (PL), Bingham, Herschel-Bulkley (HB), and Casson models, and the PL model was the best one for describing the behavior of Basil seed gum dispersion. The PL model showed an excellent performance with the maximum r-value (mean r-value = 0.942) and the minimum sum of squared error (SSE) values (mean SSE value = 5.265) and root mean square error (RMSE) values (mean RMSE value = 0.624) for all gum dispersion. MT had a considerable effect on the changes in the consistency coefficient (k-value) and flow behavior index (n-value) of Basil seed gum dispersion (p < 0.05). The k-value of Basil seed gum dispersion decreased significantly from 3.149 Pa.sn to 1.153 Pa.sn (p < 0.05) with increasing MT time from 0 to 3 min. The n-value of Basil seed gum dispersion increased significantly from 0.25 to 0.42 (p < 0.05) as the MT time increased. The Bingham plastic viscosity of Basil seed gum dispersion increased significantly from 0.029 Pa.s to 0.039 Pa.s (p < 0.05) while the duration of MT increased. The Casson yield stress of Basil seed gum dispersion notably reduced from 5.010 Pa to 2.165 Pa (p < 0.05) with increasing MT time from 0 to 3 min.

The Fourier theorem states that any time-series can be decomposed into a set of sinusoidal frequencies, each with its own phase and amplitude. The literature suggests that some frequencies are important to reproduce key qualities of eye-movements (\"signal\") and some of frequencies are not important (\"noise\"). To investigate what is signal and what is noise, we analyzed our dataset in three ways: (1) visual inspection of plots of saccade, microsaccade and smooth pursuit exemplars; (2) analysis of the percentage of variance accounted for (PVAF) in 1,033 unfiltered saccade trajectories by each frequency band; (3) analyzing the main sequence relationship between saccade peak velocity and amplitude, based on a power law fit. Visual inspection suggested that frequencies up to 75 Hz are required to represent microsaccades. Our PVAF analysis indicated that signals in the 0-25 Hz band account for nearly 100% of the variance in saccade trajectories. Power law coefficients (a, b) return to unfiltered levels for signals low-pass filtered at 75 Hz or higher. We conclude that to maintain eyemovement signal and reduce noise, a cutoff frequency of 75 Hz is appropriate. We explain why, given this finding, a minimum sampling rate of 750 Hz is suggested.

Complex networks describe a wide range of systems in nature and society. As a fundamental concept of graph theory, the path connecting nodes and edges plays a vital role in network science. Rather than focusing on the path length or path centrality, here we draw attention to the path multiplicity related to decision-making efficiency, which is defined as the number of shortest paths between node pairs and thus characterizes the routing choice diversity. Notably, through extensive empirical investigations from this new perspective, we surprisingly observe a \"hesitant-world\" feature along with the \"small-world\" feature and find a universal power-law of the path multiplicity, meaning that a small number of node pairs possess high path multiplicity. We demonstrate that the power-law of path multiplicity is much stronger than the power-law of node degree, which is known as the scale-free property. Then, we show that these phenomena cannot be captured by existing classical network models. Furthermore, we explore the relationship between the path multiplicity and existing typical network metrics, such as average shortest path length, clustering coefficient, assortativity coefficient, and node centralities. We demonstrate that the path multiplicity is a distinctive network metric. These results expand our knowledge of network structure and provide a novel viewpoint for network design and optimization with significant potential applications in biological, social, and man-made networks.

Molecular diffusion of chemical species in subsurface environments─rock formations, soil sediments, marine, river, and lake sediments─plays a critical role in a variety of dynamic processes, many of which affect water chemistry. We investigate and demonstrate the occurrence of anomalous (non-Fickian) diffusion behavior, distinct from classically assumed Fickian diffusion. We measured molecular diffusion through a series of five chalk and dolomite rock samples over a period of about two months. We demonstrate that in all cases, diffusion behavior is significantly different than Fickian. We then analyze the results using a continuous time random walk framework that can describe anomalous diffusion in heterogeneous porous materials such as rock. This methodology shows extreme long-time tailing of tracer advance as compared to conventional Fickian diffusion processes. The finding that distinct anomalous diffusion occurs ubiquitously implies that diffusion-driven processes in subsurface zones should be analyzed using tools that account for non-Fickian diffusion.

Identifying the sources and fate of microplastics in natural systems has garnered a great deal of attention because of their implications for ecosystem health. This work characterizes the size fraction, morphology, color, and polymer composition of microplastics in western Lake Superior and its adjacent harbor sampled in August and September 2021. The results reveal that the overall microplastic counts are similar, with the harbor stations ranging from 0.62 to 3.32 microplastics per liter and the lake stations ranged from 0.83 to 1.4 microplastics per liter. However, meaningful differences between the sample locations can be seen in the size fraction trends and polymer composition. Namely, the harbor samples had relatively larger amounts of the largest size fraction and more diversity of polymer types, which can be attributed to the urbanized activity and shorter water residence time. Power law size distribution modeling reveals deviations that help in the understanding of potential sources and removal mechanisms, although it significantly underpredicts microplastic counts for smaller-sized particles (5-45 μm), as determined by comparison with concurrently collected microplastic samples enumerated by Nile Red staining and flow cytometry.

Colloidal semiconductor quantum dots have many potential optical applications, including quantum dot light-emitting diodes, single-photon sources, or biological luminescent markers. The optical properties of colloidal quantum dots can be affected by their dielectric environment. This study investigated the photoluminescence (PL) decay of thick-shell gradient-alloyed colloidal semiconductor quantum dots as a function of solvent refractive index. These measurements were conducted in a wide range of delay times to account for both the initial spontaneous decay of excitons and the delayed emission of excitons that has the form of a power law. It is shown that whereas the initial spontaneous PL decay is very sensitive to the refractive index of the solvent, the power-law delayed emission of excitons is not. Our results seem to exclude the possibility of carrier self-trapping in the considered solvents and suggest the existence of trap states inside the quantum dots. Finally, our data show that the average exciton lifetime significantly decreases as a function of the solvent refractive index. The change in exciton lifetime is qualitatively modeled and discussed.