Natural Fluctuations Research Articles

Long-Term Study on the Fluctuation of Self-Reported Awake Bruxism in a Cohort of Healthy Young Adults.

The introduction of a smartphone-based ecological momentary assessment (EMA) approach has allowed achieving data on the frequency of different awake bruxism (AB) behaviours (i.e., teeth contact, teeth clenching, teeth grinding, and mandible bracing) reported by an individual in the natural environment. The fluctuation of AB reports over time has a certain degree of variability that has never been investigated. Therefore, the aim of this investigation was to assess the long-term fluctuation of AB behaviours in a population of young adults. A smartphone application was used to assess a real-time report on five specific oral conditions related to AB in a sample of 77 young adults, aged 24.0 ± 0.8 years. Data were recorded over three periods of 7 days, with a three-month interval for a total of 6 months. The average frequency of the relaxed condition was 72.9%, 78.2%, and 80.8% at the end of the first, second, and third sessions, respectively. On average, teeth contact and mandible bracing were the most frequently reported conditions, with a mean prevalence of 12.9% and 7%, respectively, whilst the frequency of teeth clenching and teeth grinding was less than 3%. The ANOVA test showed an absence of significant differences (p < 0.05) between the three recording periods, and the frequency was in general only moderately variable from day-to-day (e.g., the coefficient of variation (CV) for the condition "relaxed jaw muscles" was 0.3). No gender differences were detected either. Findings suggest that in a population of healthy individuals, the frequency of AB behaviours over a six-month monitoring period is quite constant. This investigation represents a standpoint for future comparisons on the study of natural fluctuations of AB behaviours as well as on AB frequency in populations with risk/associated factors and possible clinical consequences.

Toward a metabolic theory of catchments: Scaling of water and carbon fluxes with size

Allometric scaling relations are widely used to link biological processes to body size in nature. Several studies have shown that such scaling laws hold also for natural ecosystems, including individual trees and forests, riverine metabolism, and river network organization. However, the derivation of scaling laws for catchment-scale water and carbon fluxes has not been achieved so far. Here, we focus on scaling relations of catchment green metabolism, defined as the set of ecohydrological and biogeochemical processes through which vegetation assemblages in catchments maintain their structure and react to the surrounding environment. By revising existing plant size-density relationships and integrating them across large-scale domains, we show that the ecohydrological fluxes occurring at the catchment scale are invariant with respect to the above-ground vegetation biomass per unit area of the basin, while they scale linearly with catchment size. We thus demonstrate that the sublinear scaling of plant metabolism results in an isometric scaling at catchment and regional scales. Deviations from such predictions are further shown to collapse onto a common distribution, thus incorporating natural fluctuations due to resource limitations into a generalized scaling theory. Results from scaling arguments are supported by hyperresolution ecohydrological simulations and remote sensing observations.

Memory augmentation with an adaptive cognitive interface.

What we remember reflects both what we encounter, such as the intrinsic memorability of a stimulus, and our internal attentional state when we encounter that stimulus. Our memories are better for memorable images and images encountered in an engaged attentional state. Here, in an effort to modulate long-term memory performance, we manipulated these factors in combination by selecting the memorability of presented images contingent on individuals' natural fluctuations in sustained attention. Can image memorability and attentional state be strategically combined to improve memory? Are memorable images still well remembered during lapses in sustained attention, and conversely, can attentive states rescue memory performance for forgettable images? We designed a procedure to monitor participants' sustained attention dynamics on the fly via their response time fluctuations during a continuous performance task with trial-unique scene images. When high- or low-attentional states were detected, our algorithm triggered the presentation of high- or low-memorability images. Afterwards, participants completed a surprise recognition memory test for the attention-triggered images. Results demonstrated that memory performance for memorable items is not only resistant to lapses in sustained attention but also that memory cannot be further improved by encoding memorable items in engaged attentional states. On the other hand, memory performance for low-memorability images can be rescued by attentive encoding states. In sum, we show that both memorability and sustained attention can be leveraged in real time to maximize memory performance. This approach suggests that adaptive cognitive interfaces can tailor what information appears when to best support overall memory.

Leveraging advanced AI algorithms with transformer-infused recurrent neural networks to optimize solar irradiance forecasting

Solar energy (SE) is vital for renewable energy generation, but its natural fluctuations present difficulties in maintaining grid stability and planning. Accurate forecasting of solar irradiance (SI) is essential to address these challenges. The current research presents an innovative forecasting approach named as Transformer-Infused Recurrent Neural Network (TIR) model. This model integrates a Bi-Directional Long Short-Term Memory (BiLSTM) network for encoding and a Gated Recurrent Unit (GRU) network for decoding, incorporating attention mechanisms and positional encoding. This model is proposed to enhance SI forecasting accuracy by effectively utilizing meteorological weather data, handling overfitting, and managing data outliers and data complexity. To evaluate the model’s performance, a comprehensive comparative analysis is conducted, involving five algorithms: Artificial Neural Network (ANN), BiLSTM, GRU, hybrid BiLSTM-GRU, and Transformer models. The findings indicate that employing the TIR model leads to superior accuracy in the analyzed area, achieving R2 value of 0.9983, RMSE of 0.0140, and MAE of 0.0092. This performance surpasses those of the alternative models studied. The integration of BiLSTM and GRU algorithms with the attention mechanism and positional encoding has been optimized to enhance the forecasting of SI. This approach mitigates computational dependencies and minimizes the error terms within the model.

2D Magnetotelluric Resistivity Structure Modeling Using Finite Element Method Based on Vector Triangular Grid and Its Application to Lembang Fault MT Data

Abstract Magnetotellurics is one of the geophysical exploration techniques that relies on the natural fluctuations of electromagnetic waves to delineate their influence on the Earth. The primary focus of this method is to reveal the structure of Earth’s subsurface with the value of resistivity. The application of numerical approaches in magnetotelluric modeling has proven to be an efficient method in various theoretical studies in the field of geophysics, particularly in the context of modeling two-dimensional structures. This research explains a 2D resistivity structure modeling using a vector finite element method. This approach utilizes the edges of elements as vector bases. The presented results include response values such as apparent resistivity and impedance phase at the surface. The study employs the standard model from COMMEMI as a reference to validate the modeling program. Furthermore, the results from this modeling program are compared with the outcomes of the modeling program developed by Weaver et al. The good results were obtained with error values for each model for layered and homogeneous Earth &lt; 3%. Additionally, for the reference model COMMEMI, errors of 3.4393% and 1.4050% were obtained for TE and TM modes, respectively. Furthermore, apparent resistivity and impedance phase results closely approximated the reference values for the topography model. Subsequently, in the application to field data, specifically the Lembang Fault, errors were obtained for the TE and TM modes within the range of 1.16 – 9.16% for each MT data acquisition site.

Impact of abiotic stressors on oleic acid accumulation in the leaves of young quinoa plants

Investigating the impact of not only individual stress factors but also their combined effect on plants becomes imperative in the context of natural and climatic fluctuations. 18-carbon unsaturated fatty acids such as oleic (18:1), linoleic (18:2) and α-linolenic (18:3) serve as vital non-enzymatic antioxidants, making significant contributions to plant defense. Moreover, they are indispensable in assessing the nutritional and biological value of plant lipids. Currently, Chenopodium quinoa L., a member of the Amaranth family, is increasingly recognized as a valuable source of antioxidant metabolites. Current study examined the fluctuation patterns in oleic acid ester content, serving as a non-enzymatic antioxidant, when plant exposed to varying intensities of osmotic, saline, and combined stress. A constant concentration of oleic acid esters was shown under different levels of saline stress. Osmotic stress did not affect the oleic acid content. Under salt stress, the oleic acid content increased compared to the control, varying at different NaCl concentrations. However, under combined stress, there was a significant increase in ester content, peaking at a stress level of 200NaCl/L+PEG, followed by a decrease as stress increased. It was noted that signs of stress for the photochemical quenching index of YII and ETR in photosystem II of young quinoa plants also occur with a combination of exposure to 300 mM/L NaCl + PEG. It was suggested that the level of combined stress at 200NaCl/P is transitional from eustress to distress. The results obtained could potentially become the basis for the targeted synthesis of valuable plant antioxidants for food and pharmaceutical purposes in the future.

Trend detection in the temperature of Quebec (Canada) rivers

ABSTRACT Trend detection in environmental data subjected to natural fluctuations can prove difficult. With river temperature, the difficulty also lies in the typically limited lengths of the time series. In this work, three different river temperature data sources (continuous and spot instream measurements, and satellite thermal images) were combined to build 30- to 44-year-long time series at 116 locations, distributed throughout most of the Quebec Province territory. Mann-Kendall tests and a non-linear model were used to detect and quantify trends. Uncertainty and biases due to the different data sources and uneven samplings were evaluated and included in the assessment of the trends’ quantification and reliability. Overall, most trends detected in the temperature of Quebec rivers are positive, with higher warming occurring in summer. Annual maxima are found to have increased by 0.023°C/year (median value) between 1979 and 2022, and this maximum appears to occur 2.6 days (median value) later.

Development of the Flexibility in Daily Life scale to measure multidimensional cognitive and behavioural flexibility in health and disease

AbstractObjectivesInflexibility of thought and behaviour is a transdiagnostic feature of many neuropsychiatric disorders and presents several empirical measurement challenges. Here, we developed and validated the Flexibility in Daily Life scale (FIDL); a novel, self‐report questionnaire, which captures expressions of cognitive and behavioural flexibility in daily life and is sensitive to natural shifts in these processes across the adult lifespan.MethodsThe FIDL was developed using a deductive scale development approach, which aimed to capture common themes within the flexibility literature and across diagnoses (e.g. insistence on sameness, preference for routines). Following multidisciplinary consensus, an initial 37‐item questionnaire was submitted for validation in an online sample of 295 healthy adult participants (19–78 years).ResultsExploratory factor analysis produced a revised 21‐item version comprising five factors, labelled: Repetition, Switching, Predictability/Control, Routine, and Thoughts/Beliefs. Internal consistency reliability was good‐to‐strong for the total FIDL score and moderate‐to‐strong for individual subscales. Convergent validity was established between the FIDL and an existing measure of cognitive flexibility. Critically, the FIDL total score evinced a U‐shaped relationship with age, whereby flexibility was lower at the younger and older tails of the lifespan and greater in middle age. The same U‐shaped trajectory emerged for the Repetition, Routine, and Thoughts/Beliefs factors.ConclusionsOverall, the FIDL is a valid and reliable multidimensional measure of flexibility, which upholds a clearly defined factor structure and good psychometric properties. It promises to be a valuable clinical and research tool to assess the natural fluctuations in flexibility across the lifespan and departures thereof.

Abiotic stress responses in crop plants: A multi-scale approach

Population stress has compelled the whole world to think about increasing, protecting, and finding ways to develop the best plant species for assured productivity in spite of all environmental odds. In addition to climate change, fluctuations in nature and human activities pose serious environmental degradation, threatening global food security through physical stress in the environment. Significant environmental constraints on agricultural yield worldwide include salt stress, water deficiency stress, nutritional imbalances (including mineral toxicity and deficiencies), and temperature extremes. Abiotic factors, such as agronomic factors, climatic factors, and nutrient availability in the soil, influence crop yield. Plants initiate and develop various possible stress mechanisms for their survival, which can be molecular, cellular and physiological. Abiotic stress has a high impact on crop growth and productivity, either in single forms or in combined forms. For example, drought stress causes a decrease in leaf area, plant height, and crop development. Cold stress reduces plant development and crop efficiency, resulting in productivity loss. Salinity stress not only contributes to water stress in plants, but it can also adversely influence cytosolic metabolism, cell development, membrane function, and increase reactive oxygen species (ROS) generation. Higher concentrations of CO2 could potentially improve global precipitation, resulting in increased rainfall, which can adversely affect crop development. Crops under excessive water stress have a lower percentage of amylose but a higher crude protein content. This in turn, affects the quality and quantity of crop production by hindering seed germination and causing growth damage due to the combined effects of higher osmotic potential and ion toxicity. In response to abiotic stress, plants evolve a variety of escape-avoidance and tolerance mechanisms, which include physiological adaptation and integrated cellular or molecular responses. Therefore, the main purpose of the current review paper is to investigate the effect of abiotic stress on morpho-physiological, biochemical and molecular activities in various crops. Moreover, we concentrate on crop inter-relativity with abiotic stress to react to and adapt to for survival, which can be a basic roadmap for the selection of species or the development of new tolerant species in the future.

Climatic fluctuations alter the preference of stingless bees (Apidae, Meliponini) towards food contaminated with acephate and glyphosate

The global decline of pollinators has become a major concern for the scientific community, policymakers, and the general public. Among the main drivers of diminishing bee populations is the widespread use of agrochemicals. To gain a comprehensive understanding of the foraging dynamics of bees at agrochemical-contaminated areas, it is essential to consider both environmental conditions and the specific foraging ecology of bee species. For the first time, we conducted a semi-field study to investigate whether stingless bees exhibit a preference for food contaminated with agrochemicals compared to non- contaminated food, under natural weather conditions. Colonies of Plebeia lucii Moure, 2004 were placed in a greenhouse and subjected to a preference test, where bees were given the freedom to choose between contaminated or non-contaminated food sources following a preliminary training period. Within the greenhouse, we placed feeders containing realistic concentrations of an insecticide (acephate: 2 mg a.i./L), a herbicide (glyphosate: 31.3 mg a.i./L), or a mixture of both, alongside non-contaminated food. Environmental variables (temperature, humidity, and light intensity) were monitored throughout the experiment. At higher temperatures, the foragers preferred food containing the mixture of both agrochemicals or uncontaminated food over the other treatments. At lower temperatures, by contrast, the bees preferred food laced with a single agrochemical (acephate or glyphosate) over uncontaminated food or the agrochemical mixture. Our findings indicate that agrochemical residues in nectar pose a significant threat to P. lucii colonies, as foragers do not actively avoid contaminated food, despite the detrimental effects of acephate and glyphosate on bees. Furthermore, we demonstrate that even minor, natural fluctuations in environmental conditions can alter the colony exposure risk. Despite the interplay between temperature and bees' preference for contaminated food, foragers consistently collected contaminated food containing both agrochemicals, whether isolated or in combination, throughout the whole experiment.

EXPLANA: A user-friendly workflow for EXPLoratory ANAlysis and feature selection in cross-sectional and longitudinal microbiome studies.

Longitudinal microbiome studies (LMS) are increasingly common but have analytic challenges including non-independent data requiring mixed-effects models and large amounts of data that motivate exploratory analysis to identify factors related to outcome variables. Although change analysis (i.e. calculating deltas between values at different timepoints) can be powerful, how to best conduct these analyses is not always clear. For example, observational LMS measurements show natural fluctuations, so baseline might not be a reference of primary interest; whereas, for interventional LMS, baseline is a key reference point, often indicating the start of treatment. To address these challenges, we developed a feature selection workflow for cross-sectional and LMS that supports numerical and categorical data called EXPLANA (EXPLoratory ANAlysis). Machine-learning methods were combined with different types of change calculations and downstream interpretation methods to identify statistically meaningful variables and explain their relationship to outcomes. EXPLANA generates an interactive report that textually and graphically summarizes methods and results. EXPLANA had good performance on simulated data, with an average area under the curve (AUC) of 0.91 (range: 0.79-1.0, SD = 0.05), outperformed an existing tool (AUC: 0.95 vs. 0.56), and identified novel order-dependent categorical feature changes. EXPLANA is broadly applicable and simplifies analytics for identifying features related to outcomes of interest.

Extreme weather event causes the death of White-collared Swift Streptoprocne zonaris (Shaw, 1796) (Aves, Apodidae) individuals in sinkholes in the State of Goiás, Brazil

The use of caves and rocky walls is common for some birds, like swifts, to shelter, sleep, nest, feed, and protect themselves from predators, wind, and rain. Several environmental and ecological factors associated with the habits and adaptations of certain species allow birds to use cave environments. The White-collared Swift Streptoprocne zonaris (Shaw, 1796) is distributed from Mexico and the Antilles south to northern Argentina, Paraguay, and southern Brazill, being frequent in areas with waterfalls and river rapids with rocky beds and crystal-clear water. Individuals live in flocks and have the habit of roosting and nesting in damp, dark caves or behind waterfalls. Herein, we aim to report the case and identify the cause of death of S. zonaris individuals found dead in a sinkhole in the State of Goiás, Brazil, in 2020. Global warming resulting from anthropogenic emissions of greenhouse gases can alter the natural fluctuations of atmospheric circulation systems, responsible for rainfall distribution, substantially affecting rainfall and increasing the frequency of heavy rainfall events in some locations. Due to climate change and the increasing frequency of flooding records, we have raised the hypothesis and drawn attention to our record may have been originated due to these climatic events. However, we do not dismiss the hypothesis that the flooding may be due to an extreme event. The fact that S. zonaris spends the night and nests close to water bodies makes the species more susceptible to the effects of a flash flood. Further studies will be able to show the real effects of global warming on the species.

In the heat of the moment: Including realistic thermal fluctuations results in dramatically altered key population parameters.

Temperature is commonly acknowledged as one of the primary forces driving ectotherm vector populations, most notably by influencing metabolic rates and survival. Although numerous experiments have shown this for a wide variety of organisms, the vast majority has been conducted at constant temperatures and changes therein, while temperature is far from constant in nature, and includes seasonal and diurnal cycles. As fluctuating temperatures have been described to affect metabolic processes at (sub)cellular level, this calls for studies evaluating the relative importance of temperature fluctuations and the changes therein. To gain insight in the effects of temperature fluctuations on ectotherm development, survival, and sex ratio, we developed an inexpensive, easily reproducible, and open-source, Arduino-based temperature control system, which emulates natural sinusoidal fluctuations around the average temperature. We used this novel setup to compare the effects of constant (mean) temperatures, most commonly used in experiments, block schemes, and natural sinusoidal fluctuations as well as an extreme variant with twice its amplitude using the cosmopolitan mosquito species Culex pipiens s.l. as a study organism. Our system accurately replicated the preprogrammed temperature treatments under outdoor conditions, even more accurately than traditional methods. While no effects were detected on survival and sex ratio within the ranges of variation evaluated, development was sped up considerably by including temperature fluctuations, especially during pupation, where development under constant temperatures took almost a week (30%) longer than under natural fluctuations. Doubling the amplitude further decreased development time by 1.5 days. These results highlight the importance of including (natural) oscillations in experiments on ectotherm organisms - both aquatic and terrestrial - that use temperature as a variable. Ultimately, these results have major repercussions for downstream effects at larger scales that may be studied with applications such as ecological niche models, disease risk models, and assessing ecosystem services that rely on ectotherm organisms.

Simulations of design and high load operation of a model Francis turbine using bridged approach to turbulence modelling

Abstract Off-design operation of hydraulic turbines is contemporarily frequented for balance of variable energy intermittence in the electric grid. Being operationally highly flexible, these turbines allow a quick transition to off-design operation from the design point. However, such operational flexibility, and therefore the grid balancing capability is impeded by generation of flow instabilities like vortex breakdown during off-design operation. Vortex breakdown causes losses in efficiency and pressure recovery, pressure fluctuations and possibly mechanical vibrations in event of resonance between system natural and flow field fluctuation frequencies. While substantial experimental and numerical effort has already been made to study draft tube vortex breakdown, an accurate numerical flow characterization of the phenomenon is still a challenge. To this end, operation of a high head model Francis turbine under design and high load regimes using a bridged turbulence modelling approach is simulated. The approach allows a seamless transition between direct numerical simulation and Reynolds averaged Navier-Stokes equations. The highest attainable accuracy is limited by the mesh size. As such a satisfactory compromise between desired accuracy and invested computational effort is attained. The flow in the draft tube is free of anomalies under design specified operation. However, at high load an axial flow stagnation occurs centrally, and the flow is separated about the stagnated zone. The core of the vortex is enlarged with flow recirculation within it. Shear layers between the central stagnant zone and surrounding outflow kink and roll up transforming it into a spiral structure. In this work, a basic yet accurate numerical flow characterization of the aforementioned flow situations is achieved.

MULTILEVEL GRADIENT GENERATOR FOR STUDYING THE EFFECT OF HYPOMAGNETIC FIELDS ON BIOLOGICAL OBJECTS

A multilevel generator has been developed based on a gradient magnetic field source using square Helmholtz coils, which makes it possible to create changes in the level of the magnetic field in the horizontal plane with a constant vertical magnetic component. The error in setting the generated magnetic field can reach 4 %, which is comparable to natural fluctuations of the Earth's magnetic field. The generator provides experiments with biological objects in the working area of square Helmholtz coils with a volume of at least 0.25 m3, reducing the experiment time by more than five times. The developed design options for a multilevel generator make it possible to conduct a variety of magnetobiological experiments: in a uniform and gradient magnetic field, with magnetic field inversion and transition through the zero value, in combined magnetic fields.

How Does Temperature Affect the Charge Transfer Process in Flow Electrode Capacitive Deionization?

In this study, we investigate how temperature variations, a key environmental factor, affect the charge transfer process in FCDI systems across seasonal variation and geographical distributions, which is crucial for optimizing FCDI performance but has not received adequate attention. Therefore, thermal-assisted FCDI systems were proposed by controlling the temperatures of the flow electrode and saline water to simulate the environmental conditions, and the temperature effects on the charge transport and desalting ability of FCDI were investigated. First, the isothermal mode was performed, where the flow electrode and saline water were controlled at the same temperatures (0-50 °C) to simulate the natural atmospheric temperature fluctuations and industrial circulating cooling water system. Experimental results showed a strong positive correlation between temperature and electrosorption dynamics. Elevated temperatures significantly improved ion electromigration and diffusion, thereby enhancing the electrosorption capacity of the FCDI device. On this basis, the nonisothermal mode was designed via maintaining the temperature of the flow electrode at 50 °C to improve the desalination performance of FCDI for saline water at different temperatures (0-50 °C). Finally, the East China seawater and industrial circulating cooling water were both desalted successfully to confirm the feasibility of the temperature field in the practical application of FCDI.

Fluctuations in Cortisol and Testosterone Map to Fluctuations in Opinion Strength in Healthy Men

PurposeOpinions are often linked to emotions and stress. It is well established that testosterone and cortisol are useful biomarkers of stress and can predict human emotion and behavior. Therefore, the purpose of this work was to explore whether changes in testosterone and cortisol concentration map to shifts in opinions.MethodsWe present three studies with healthy men, where we (1) monitored diurnal changes in testosterone and cortisol alongside political opinion change using a descriptive longitudinal design, (2) assessed testosterone, cortisol and political opinion change in an experimental trial using a physical exercise intervention designed to decrease cortisol concentration and/or increase testosterone concentration, and (3) monitored testosterone and cortisol change with political opinion in a trial with psychosocial intervention designed to increase cortisol concentration/decrease testosterone concentration.ResultsTestosterone concentration and opinion changes were observed across the day (p < 0.05). Furthermore, opinions changed similarly to exercise-induced increases in testosterone (8.6–11.5%), but inversely to exercise-induced reductions in cortisol (p < 0.05). Opinion changes also occurred in similar fashion to testosterone changes following psychosocial intervention (-5.6% to -10.0%), and inversely to cortisol changes (p < 0.05). Finally, opinion change and testosterone change correlated at the within person level (r = 0.17 to 0.33; p < 0.05).ConclusionWe showed natural fluctuations in testosterone and cortisol covaried in parallel with shifts in opinion. Further, given the emergence of relationships for opinion change with hormone change, we contend that physiological stress response (i.e., testosterone and cortisol change) may predict, or even cause, opinion change.

Correlations among genetic, epigenetic, and phenotypic variation of Phragmites australis along latitudes

AbstractAimEstuarine vegetation routinely experiences natural tidal fluctuations and is highly vulnerable to extreme events such as heavy rainfall, leading to changes in plant population structure and adaptability. Genetic and epigenetic modifications are widely considered to be mechanisms of phenotypic variation, triggered in plants responding to extreme changing environments. However, understanding on correlations among genetic, epigenetic, and phenotypic variation of wild plant populations is still limited.LocationChina.MethodsIn this study, populations of the typical wetland clonal species Phragmites australis were selected from four estuaries along various latitudes in China. Genetic and epigenetic diversity and phenotypic variation of these populations were analysed.ResultsPhenotypic variation of P. australis populations was the highest at Yellow River Estuary and the lowest at Min River Estuary. Across all estuaries, Genetic and epigenetic diversity was strongly linear‐correlated. Genetic diversity had significant correlations with variation in reproductive traits, whereas epigenetic diversity had significant correlations with variation in growth traits. Climatic factors of mean annual temperature and precipitation, as well as soil nitrogen and phosphorus, were negatively correlated with variation in genetic diversity, epigenetic diversity, and variation in reproductive traits of P. australis populations along latitudes. Variation in growth traits was negatively correlated with soil salinity, reflecting the limiting effect of salinity on plant growth.Main ConclusionOur findings found that genetic and epigenetic variations may play different roles in phenotypic variation of P. australis populations along latitudes, the variation becomes greater when the climatic and edaphic conditions deteriorate. The findings shed new light on the adaptation and evolution of wetland plant populations along a large latitudinal scale, and may contribute to the revegetation of estuary wetlands.

Radiative cooling assisted self-sustaining and highly efficient moisture energy harvesting

Harvesting electricity from ubiquitous water vapor represents a promising route to alleviate the energy crisis. However, existing studies rarely comprehensively consider the impact of natural environmental fluctuations on electrical output. Here, we demonstrate a bilayer polymer enabling self-sustaining and highly efficient moisture-electric generation from the hydrological cycle by establishing a stable internal directed water/ion flow through thermal exchange with the ambient environment. Specifically, the radiative cooling effect of the hydrophobic top layer prevents the excessive daytime evaporation from solar absorption while accelerating nighttime moisture sorption. The introduction of LiCl into the bottom hygroscopic ionic hydrogel enhances moisture sorption capacity and facilitates ion transport, thus ensuring efficient energy conversion. A single device unit (1 cm2) can continuously generate a voltage of ~0.88 V and a current of ~306 μA, delivering a maximum power density of ~51 μW cm−2 at 25 °C and 70% relative humidity (RH). The device has been demonstrated to operate steadily outdoors for continuous 6 days.

Directional connectedness between the electricity prices and natural gas prices: evidence from Alberta’s electricity market

Purpose This study aims to assess volatility spillovers and directional connectedness between electricity (EPs) and natural gas prices (GPs) in the Canadian electricity market, based on a hydrothermal power generation market strongly dependent on exogenous variables such as fossil fuel prices and climatology factors. Design/methodology/approach The methodology is divided into two stages. First, a quantile vector autoregression model is used to evaluate the direction and magnitude of the influence between natural gas and electricity prices through different quantiles of their distributions. Second, a cross-quantilogram is estimated to measure the directional predictability between these prices. The data set consists of daily electricity and natural gas prices between January 2015 and December 2023. Findings The main finding shows that electricity prices are pure shock receivers of volatility from natural gas prices for the different quantiles. In this way, natural gas price fluctuations explain 0.20%, 0.98% and 22.72% of electricity price volatility for the 10th, 50th and 90th quantiles, respectively. On the other hand, a significant and positive correlation is observed in the high quantiles of the electricity prices for any natural gas price value. Originality/value The study described the risk to the electricity market caused by nonrenewable source price fluctuations and provided evidence for designing regulatory policies to reduce its exposure in Alberta, Canada. It also allows us to understand the importance of natural gas in the energy transition process and define it as the fundamental determinant of the electricity market dynamic.