Patterns Of Variability Research Articles

Inter-annual hydrographic changes in the Southern Ocean: analysis of Vendée Globe Race and Barcelona World Race data

Abstract The Southern Ocean remains one of the most data-deficient ocean basins despite its crucial role in global climate regulation. This study uses racing sailboats from the Barcelona World Race (2010/2011 and 2014/2015) and the Vendée Globe Race (2020/2021) as vessels of opportunity to collect sea-surface temperature and salinity measurements, offering a unique dataset for assessing oceanographic variability in this remote region. We conducted an inter-annual analysis of surface temperature and salinity anomalies relative to ARMOR-3D reanalysis and World Ocean Atlas 2023 climatological datasets, identifying regional patterns of change and variability. The results reveal a warming trend and general freshening of the Southern Ocean surface over the last decade, with the highest anomalies observed in the Indian and Atlantic sectors, whereas the Pacific sector showed the lowest anomalies in absolute terms. Notably, El Niño-Southern Oscillation (La Niña) and Southern Annular Mode phases played a significant role in modulating these temperature and salinity anomalies. This study underscores the scientific value of non-research vessels in monitoring climate-driven changes in Antarctic and sub-Antarctic waters, highlighting their potential to complement traditional observation networks in data-sparse regions.

Unveiling two millennia of ecosystem changes in the Azores through elementome trajectory analysis

Unveiling two millennia of ecosystem changes in the Azores through elementome trajectory analysis

The winter North Atlantic Oscillation downstream teleconnection: insights from large-ensemble climate model simulations

Abstract The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures downstream over Eurasia through establishing a large-scale teleconnection, but past studies on the NAO’s downstream teleconnection have been largely limited to observational data, and further evidence of downstream impacts and associated mechanisms from comprehensive climate modeling is desirable. This study quantifies and analyzes this teleconnection on an interannual timescale by using both ERA5 reanalysis, and five large ensembles from four climate simulation models. A particular focus is placed on dynamical pathways, as well as variability among ensemble members that modulates the teleconnection strength. Results suggest that NAO signals are propagated downstream by Rossby waves, efficiently transmitted through waveguides along both the polar and subtropical jet streams to Eastern Eurasia; while heat can be advected weakly from upstream, advection plays a rather local effect inducing temperature anomalies from the Pacific Ocean onshore. Multiple linear regression shows that internal climate variability significantly modulates the teleconnection: a more locally dominant NAO pattern, and narrower waveguides could strengthen the teleconnection. These two factors combine to explain up to 70% of variance in the teleconnection strength, with each contributing almost equally. Reanalysis data marginally agree with the regression model (1.9 standardized residuals higher in strength), suggesting potential model biases in jets and the NAO variability. Monitoring these modulating factors would be crucial to understanding downstream climate predictability and improving climate prediction models linked to the NAO.

Developing an Entrepreneurial Ecosystem Framework for Student-Led Start-Ups in Higher Education

Higher education institutions (HEIs) are increasingly seen as central actors in entrepreneurial ecosystems, yet their support mechanisms do not always align with the needs of student entrepreneurs. This study investigates how key stakeholders, business students, professors, and experienced start-up founders perceive the relative importance of success factors for student-led start-ups within HEIs. Using a cross-sectional descriptive design, this study used a 34-item survey instrument developed through an extensive literature review and validated for content by a panel of experts. Triangulation between stakeholder groups enabled a multidimensional comparison of perspectives. Descriptive statistics were used to analyze patterns of agreement and variability, resulting in a three-tier framework of success factors based on perceived importance and consensus. High-impact factors included faculty entrepreneurial experience, student mindset, and access to mentorship, while traditional inputs such as infrastructure, legal support, and funding were ranked lower. The findings highlight a misalignment between institutional offerings and stakeholder priorities, highlighting the critical role of social and human capital. This research provides practical guidance for HEIs seeking to improve entrepreneurial support and contributes to theoretical discussions on stakeholder-informed ecosystem models. Although limited by its single-institution context, this study offers a foundation for future cross-institutional and longitudinal research.

What is the best sampling region for endocrine hair analysis? A comparison between the posterior vertex and occipital region and recommendation for standardization.

Hair analysis is increasingly used to index long-term cumulative hormone levels. However, it remains unclear from which scalp region hair should be sampled to yield best results. Here, we conduct an in-depth, systematic investigation into this question, comparing quality characteristics between the two most promising sampling areas, the posterior vertex and the occipital region. To advance standardization in future research, we specify anatomical landmarks to clearly define sampling regions. Participants (N = 53) provided a total of twelve hair samples across two time points, three months apart. At each time point, six hair samples (three from each region) were analyzed for concentrations of cortisol, cortisone, progesterone, dehydroepiandrosterone and endocannabinoids (AEA, 1/2-AG, OEA, SEA, PEA) via liquid chromatography-tandem mass spectrometry. Patterns of intra-region variability, mean differences, test-retest correlations and associations with external criteria (anthropometrics and perceived stress) were compared between regions. Overall, no consistent differences were found between the posterior vertex and occipital region with regard to intra-region variability, test-retest correlations and external associations. However, significant mean differences in analyte concentrations were observed: hair cortisol and cortisone were higher in the occipital region, while OEA, SEA and PEA were higher at the posterior vertex. Our findings highlight the importance of sampling from a defined scalp region for endocrine hair analyses. While neither scalp region was unequivocally superior, differences in mean concentrations call for increased standardization of methodological practice in future research. We propose anatomical landmarks for precise region localization and offer practical recommendations concerning the choice of sampling region.

Health risks of ambient polycyclic aromatic hydrocarbons based on the prediction of their gas-phase concentrations in the central Yangtze River Delta, China: Regional and time-resolved variability.

Health risks of ambient polycyclic aromatic hydrocarbons based on the prediction of their gas-phase concentrations in the central Yangtze River Delta, China: Regional and time-resolved variability.

Small flakes for sharp needs: Technological behaviour in the Lower Palaeolithic site of Marathousa 1, Greece

Marathousa 1 (~430 ka BP), located in the Megalopolis Basin, Greece, represents the earliest documented butchery site in the Southern Balkans, providing clear evidence of a direct association between artefacts and remains of Palaeoloxodon antiquus. The lithic assemblage features a distinctive small tools industry, primarily produced from local radiolarite, comprising both simple flakes and retouched tools. Through technological analysis, raw material characterisation, experimental knapping, and statistical analyses, this study explores how Middle Pleistocene hominins organised their technological behaviour as reflected in the lithic assemblage, and how these behaviours were shaped by the resource-rich setting of the Megalopolis Basin, characterised by abundant raw materials, water sources, and faunal availability. Results demonstrate the interplay between freehand and bipolar knapping, reflecting a flexible technological strategy to exploit the available radiolarite. Freehand percussion was mainly used in flake production, while the bipolar technique facilitated initial core reduction and late-stage exhaustion. The consistent microlithisation at the site is also evident in the exploitation of other locally available raw materials, such as limestone, flint, and quartz, supporting previous studies demonstrating small flakes’ effectiveness in diverse tasks. Technological patterns at Marathousa 1 broadly correspond to those observed at other Middle Pleistocene small tool sites; however, its distinctive intersection of raw material availability, technological choices and functional demands provides new insights into regional patterns of lithic variability across Eurasia during this period.

Patterns of IgE-mediated molecule sensitization across Four Peruvian Cities: Exploring Relationships with Regional Climate Classifications.

Allergic sensitization varies by region and environmental conditions. This study evaluated IgE-mediated sensitization patterns in four Peruvian cities with diverse climates. To assess the relationship between climate variability and allergic sensitization patterns in four Peruvian cities. Patients aged 3 to 70 years diagnosed with allergic rhinitis and/or asthma were recruited in Piura, Lima, Tarapoto, and Arequipa. Cities were classified using the Thornthwaite methodology adopted by SENAMHI. IgE-mediated sensitization was evaluated through skin prick tests and the Allergy Explorer 2 assay to detect reactivity to molecular allergen components. Chi-square analysis and Tukey's multiple comparisons identified significant differences among climatic zones. Allergic sensitization patterns varied across climate regions. In temperate arid zones, Blo t 5 sensitization was higher (25.3%) compared to warm arid zones (6.3%, p=0.050). Fel d 1 sensitization showed marked regional differences (56.0% in temperate arid vs 18.4% in warm rainy zones, p=0.003). Despite having the highest humidity (92.3%), Tarapoto showed lower sensitization rates across all molecular components for mites in comparison with cities that are also characterized by high humidity, with most differences reaching statistical significance (p<0.001). Pet allergen sensitization demonstrated climate-dependent variations, with both Fel d 1 and Can f 1 showing higher rates in temperate arid zones. Peru's climatic diversity could be associated with distinct allergic IgE-mediated sensitization patterns, highlighting environmental factors' relevance in allergic disease management. Lower mite sensitization in the highest humidity zone suggests factors beyond humidity influence regional allergen sensitization patterns.

Utilizing Kernel Density Estimation and Butterfly Diagram to Characterize the Gait Variability in the Fallers: A Cross-Sectional Study.

The butterfly diagram is an effective tool for visualizing gait patterns and identifying potential areas of instability in the elderly individuals who fall. Nevertheless, there is a lack of comprehensive exploration regarding the quantification of variability at the intersections in butterfly diagrams. We proposed the utilization of kernel density estimation (KDE) and center of pressure (COP) symmetry index to analyze the spatial probability distribution of intersections in butterfly diagrams and to characterize the variability of gait patterns in elderly fallers. Twenty active elderly individuals (including both fallers and non-fallers) volunteered to participate in this study. Initially, the self-selected walking speed of each subject was assessed using a treadmill. Subsequently, each participant walked for a duration of 60 s. The bilateral toe-off (TO) and initial contact (IC) points of the butterfly diagram were identified for the computation of the COP symmetry index and the intersections of bilateral TO-IC. Following this, the intersections within the walking window were utilized to assess their density and variability through Kernel density estimation. Fallers exhibited a significantly greater COP symmetry index (mean = 0.09, SD = 0.55), than non-fallers (mean = 0.58, SD = 0.56; sig. = 0.03, η2 = 0.09). No significant differences were found in step width, step length, or COP distances (p > 0.05). KDE revealed distinct variability patterns: non-fallers showed two patterns (A, B), while fallers displayed three (C, D, E), suggesting greater gait instability in fallers. KDE and COP symmetry analysis appeared to effectively quantify gait variability, offering insights into fall risk factors and potential intervention targets for elderly women.

Predicting the impact of target volume contouring variations on the organ at risk dose: results of a qualitative survey.

Predicting the impact of target volume contouring variations on the organ at risk dose: results of a qualitative survey.

Do Infant Heart Rate Variability and Visual Attention Predict Autism and Concerns for ADHD?

Investigate whether patterns of heart rate variability (indexed via respiratory sinus arrhythmia) and visual attention at 12 to 18 months of age predict elevated ADHD symptoms, autism, or neither during the preschool period. Ninety infants 12 to 18 months of age (M = 17.27, SD = 1.93; 36 females; 82.2% non-Hispanic) participated in a split-screen eye-tracking task of dynamic social and non-social moving objects. Respiratory sinus arrhythmia was derived from heart rate data collected at baseline and during the task condition. Between 24 and 65 months of age (M = 38.22, SD = 11.14), participants were evaluated and classified into one of three outcome groups: ADHD Concerns (n = 21), Autism (n = 12), or Comparison (i.e., non-Autism/non-ADHD Concerns; n = 57). The ADHD Concerns group exhibited significantly less whole-screen looking time (t(76) = -2.98, p = .004, d = 0.82) and spent a significantly lower proportion of time attending to the social portion of the stimulus (t(76) = -2.53, p = .01, d = 0.67) than the Comparison group. Respiratory sinus arrhythmia reactivity moderated the association between proportion of time spent looking at the social portion of the stimulus in infancy and ADHD symptoms during the preschool period (b = 0.004, 95% CI [0.0001, 0.01], t(89) = 2.11, p = .04), such that greater quantity/intensity of ADHD symptoms was associated with a smaller proportion of look time to the social portion of the stimulus for infants engaging in HRV withdrawal, but not HRV augmentation. Hypotheses focused on autism were not supported. Infants demonstrate distinct patterns of visual attention predictive of elevated ADHD symptoms in the preschool period. Heart rate variability may also demonstrate predictive utility in the context of early ADHD when examined in relation to social attention, but not independently.

Human influence on climate detectable in the late 19th century

The physics of the heat-trapping properties of CO[Formula: see text] were established in the mid-19th century, as fossil fuel burning rapidly increased atmospheric CO[Formula: see text] levels. To date, however, research has not probed when climate change could have been detected if scientists in the 19th century had the current models and observing network. We consider this question in a thought experiment with state-of-the-art climate models. We assume that the capability to make accurate measurements of atmospheric temperature changes existed in 1860, and then apply a standard "fingerprint" method to determine the time at which a human-caused climate change signal was first detectable. Pronounced cooling of the mid- to upper stratosphere, mainly driven by anthropogenic increases in carbon dioxide, would have been identifiable with high confidence by approximately 1885, before the advent of gas-powered cars. These results arise from the favorable signal-to-noise characteristics of the mid- to upper stratosphere, where the signal of human-caused cooling is large and the pattern of this cooling differs markedly from patterns of intrinsic variability. Even if our monitoring capability in 1860 had not been global, and high-quality stratospheric temperature measurements existed for Northern Hemisphere mid-latitudes only, it still would have been feasible to detect human-caused stratospheric cooling by 1894, only 34 y after the assumed start of climate monitoring. Our study provides strong evidence that a discernible human influence on atmospheric temperature has likely existed for over 130 y.

A unifying principle for multispecies coexistence under resource fluctuations

Resource fluctuations are ubiquitous in nature and yet are generally assumed to play a limited role in the maintenance of biodiversity. We challenge this assumption by analyzing resource competition dynamics under conditions where prevailing theory does not hold. We show that multispecies coexistence can be sustained when species are able to specialize on different temporal patterns of resource variability, including the asymmetries and periodic extremes commonly observed in natural systems. We further show how this partitioning of the statistical moments of the resource distribution provides a unified framework for explaining coexistence in variable resource environments. The multiplicity of niches we find in a single fluctuating resource highlights the potential for anthropogenic changes in resource regimes to drive cascading biodiversity losses.

Integrating Sustainable Development and Disaster Mitigation into Climate Policies to Support Water Security in Africa

Africa’s water security is inextricable from the recent patterns of climate variability. Effective formulation and implementation of climate policies require efficient integration of disaster mitigation and sustainable development to eliminate maladaptation and enhance water security. However, practical implementation is still lacking in many African countries. This study aims to examine practical measures and strategies for the integration of sustainable development and disaster mitigation into climate policies to enhance water security in Africa. A systematic bibliometric and thematic analysis was conducted using 95 peer-reviewed articles within the period 2010 to 2025 from the Scopus database. Software and frameworks such as VOSviewer and the Preferred Reporting Items for Systematic Reviews (PRISMA) were employed to analyze publication trends, co-authorship networks, keyword co-occurrence, and themes. The study revealed current research themes such as nature-based solutions for water security, climate-resilient infrastructure and technologies, and practical measures, such as eco-based adaptation and water energy food nexus, as some components of climate policy integration that can enhance water security in Africa. The study offers key policy recommendations for policymakers in the implementation of integrated climate policies adequate and effective enough to deal with water security issues in Africa.

Determination of the Abundance of Mercury from the Hg ii Line at 5677.10 Å. XXII. HD 144206 (υ Her)

Abstract The weak line of Hg ii located at 5677.10 Å is detected in ELODIE spectra of the HgMn star HD 144206 as a feature absorbing about 2% of the continuum. The synthesis of this line yields a mercury abundance which is slightly larger than previous determinations. Line synthesis is used to measure the abundances of several elements. The following excesses/deficiencies are found: helium (−1.00 dex), magnesium (−0.47 dex), titanium (+0.91) , chromium (+0.54), manganese (+1.92), iron (−0.71) , yttrium (+2.50), mercury (+4.97). A conservative uncertainty on the excesses/deficiencies is estimated to be ±0.10 dex. The recent Transiting Exoplanet Survey Satellite lightcurves of HD 144206 acquired in 2022 and 2024 show a complex pattern of variability but no clear periodicity.

Comparing functional immune responses in three aquatic turtle species.

Reptiles are increasingly faced with conservation challenges and ecoimmunological techniques would be a beneficial tool in monitoring and evaluating populations that are at-risk. However, the reptilian immune system is poorly understood, and few studies have made intraspecies comparisons, making generalizations difficult. To help address this gap, innate immune function across three conspecific freshwater turtle species was evaluated. Red-eared sliders (Trachemys scripta elegans), Mississippi mud (Kinosternon subrubrum hippocrepis), and musk turtles (Sternotherus odoratus), are found throughout the Southeastern United States and represent different ecological microhabitats and life histories. In spring 2024, male aquatic turtles were caught using hoop nets, and blood samples were taken to assess immune characteristics. Microbial killing assays were conducted using multiple blood serum and buffy layer (hereafter referred as "serum+BL") manipulations (fresh, frozen, and frozen+heat manipulated serum+BL) as well as three microbes that activate specific immunological responses: Gram-positive bacterium (Staphylococcus aureus), Gram-negative bacterium (Escherichia coli) and a fungus (Candida albicans). By using this suite of microbial assays, differences in immune prioritization can be observed across species. This study revealed that there are differences in immunocompetence in each species of freshwater turtle that varied by microbe and serum+BL manipulation. We determined that because of the contribution of complement proteins when challenged against Gram-negative bacteria, frozen manipulated serum+BL appears to be a reliable way to assess immunocompetence in individuals across turtle species. Conducting intraspecies comparisons in immune function using integrative approaches can provide valuable insight into the underlying patterns of physiological variability within wild organisms, especially those that are of conservation concern.

Linkage of nucleotide and functional diversity varies across gut bacteria

Understanding the forces shaping genomic diversity within bacterial species is essential for interpreting microbiome evolution, ecology, and host associations. Here, we analyze over one hundred prevalent gut bacterial species using the Unified Human Gut Genome (UHGG) collection to characterize patterns of intra-specific genomic variability. Gene content divergence scales predictably with divergence in core genome single nucleotide polymorphisms (SNPs), though there is substantial variability in evolutionary dynamics across species. Overall, accessory genes exhibit consistently faster linkage decay compared to core SNPs, highlighting the fluidity of functional repertoires within species boundaries. This signal is strongest for mobile genetic elements, which show minimal linkage to core genome SNPs. Together, our findings reveal species-specific recombination regimes in the gut microbiome, underscoring the importance of accounting for horizontal gene transfer and genome plasticity in microbiome-wide association studies and evolutionary models.

Evaluation of Rainfall Distribution Based on the Precipitation Concentration Index: A Case Study over the Selected Summer Rainfall Regions of South Africa

The Precipitation Concentration Index (PCI) is considered a powerful tool that can be used to analyse the spatial and temporal distribution and variability of precipitation over a region. It plays a significant role in planning and managing water resources, including monitoring and forecasting drought and flood risks. As such, the present study used the PCI to investigate the spatio-temporal distribution of precipitation in summer rainfall regions covering six selected South African provinces. Specifically, this study analysed monthly precipitation data from 49 rainfall districts spanning from 1979 to 2023 and assessed the spatio-temporal variability patterns of annual, seasonal and supra-seasonal PCI values and their trends based on the Mann–Kendall trend test. Pearson’s correlation was used to evaluate the relationship between the PCI values and precipitation across the provinces. Moderate annual PCI values were observed mainly in KwaZulu-Natal and the eastern regions of the Free State and Mpumalanga provinces. A large portion of the study site exhibited irregular annual precipitation concentrations. The PCI decreased by −1.5 and −1.2 magnitudes of change during 1979–1989 and 2000–2011 and increased by 2.1 and 2.8 magnitudes between 1990–2000 and 2012–2023, respectively. Uniform precipitation concentration was mostly recorded during the December–January–February (DJF) season. The entire study area recorded moderate precipitation concentration during the March–April–May (MAM) and September–October–November (SON) seasons (with exceptions for KwaZulu-Natal (KZN)). In addition, irregular precipitation concentration dominated during the June–July–August (JJA) rainy season. All provinces except KZN recorded positive trends in annual PCI. Also, positive trends in PCI were observed during the supra-wet season across the provinces, except KZN and in parts of the Free State. Furthermore, negative trends in seasonal PCI were mostly dominant during DJF and MAM, while positive trends were mostly observed during SON and JJA rainy seasons. The annual PCI values were positively correlated with annual precipitation in KZN, Free State and Limpopo, while negative correlations were observed in Mpumalanga and North West provinces. The results presented in this study contribute to drought and flood monitoring in support of water resource management and planning.

Learning Models on Physiological and Behavioral Data

The rising incidence of stress-related mental health issues, particularly among college students, has highlighted the need for effective, real-time detection methods. Traditional self-reported assessments are subjective and often unreliable. In this study, we present a data-driven approach using machine learning (ML) models to predict stress levels from physiological and behavioral indicators such as heart rate variability, skin conductance, and sleep patterns. We evaluate and compare the performance of multiple ML algorithms—Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbors (KNN), and Convolutional Neural Networks (CNN). Among these, Random Forest achieved the highest accuracy of 92%, followed by CNN at 90%, demonstrating strong precision (91% and 89%, respectively) and F1-scores (92% and 94%). These results affirm the potential of AI-powered stress monitoring systems for early mental health intervention, particularly when integrated with wearable technologies.

Structural and Molecular Evolution of Macrophomina spp. Isolated From Sesame in Eastern India: An In Silico Divergence Analysis

ABSTRACTCharcoal rot is a disease that is becoming more and more prevalent in sesame and is brought on by the fungus Macrophomina phaseolina. It significantly reduces yields all over the world. Understanding the pathogen's diversity at the crop field level is essential for managing the disease effectively and for understanding the epidemiology of the disease and host–pathogen interactions. This study investigates the genetic diversity among Macrophomina isolates (MAC S01–MAC S08) through comprehensive analysis of RNA secondary structures, phylogenetic relationships and structural divergence. Distinctive folding patterns, including variations in helices, loops and base‐pair stability, were observed, indicating structural and functional diversity. Consensus RNA structures revealed conserved helices crucial for stability and function, alongside flexible variable regions indicative of adaptive roles. Phylogenetic analysis highlighted distinct evolutionary clusters, with MAC S05 emerging as an outlier due to significant divergence. Structural divergence heatmaps quantified pairwise differences, aligning with phylogenetic findings, with mismatch values ranging from 247 to 413 mismatches. Geographic distribution underscored the influence of environmental diversity, with isolates from similar regions displaying structural similarities, while isolates from distinct locations exhibited divergence. Principal component analysis further captured key variability patterns, linking structural features to environmental and evolutionary pressures. These findings provide insights into the adaptive mechanisms and evolutionary dynamics of Macrophomina spp. in diverse ecological contexts. Accordingly, the results indicated that secondary structure analysis can provide new insights for the determination of genetic diversity among various strains isolated from different geographical origins.