Trends In Indicators Research Articles

Accurate and efficient stock market index prediction: an integrated approach based on VMD-SNNs

The stock market index typically mirrors the financial market's performance. Hence, accurate prediction of stock market index trends is essential for investors aiming to mitigate financial risk and enhance future investment returns. Traditional statistical approaches often struggle with the non-linear nature of stock market index data, leading to potential inaccuracies in long-term predictions. To address this issue, we introduce the TCN-LSTM-SNN (TLSNN) model, a hybrid framework that integrates Long Short-Term Memory (LSTM) and Temporal Convolutional Network (TCN) for robust feature extraction, within a highly efficient Spiking Neural Network (SNN) architecture. Additionally, we employ the Subtraction-Average-Based Optimizer (SABO) to refine the Variational Mode Decomposition (VMD) technique, thereby separating the periodic and trend components of stock indices, reducing noise interference, and establishing a decomposition ensemble framework to bolster the model's resilience. The experimental results show that the VMD-TLSNN hybrid model suggested in this study surpasses other individual benchmark models and their hybrid models in prediction accuracy. Additionally, it demonstrates notably lower energy consumption compared to other hybrid models.

Trends in extreme rainfall and their relationship to flooding episodes in Vhembe district, South Africa

Extreme weather events, such as heavy rainfall, are being increased by climate change in various regions, and such events often cause floods. This study examined the trends and variability of extreme rainfall indices using daily rainfall data (1981–2023) from three study sites at different socio-economic development spectra in Vhembe District, Limpopo Province, South Africa. The analyses focus on indices such as the annual total rainfall from wet days (PRCPTOT), the maximum number of consecutive dry days (CDD) and wet days (CWD), annual maximum 1-day and 5-day rainfall (RX1 day and RX5 day), the Simple Daily Intensity Index (SDII), the number of days exceeding varying amounts of precipitation (R10, R20, R40) and the annual number of wet days with rainfall greater than the 95th and 99th percentile (R95p and R99p) of the 1981–2023 daily rainfall. We discuss the observed trends in extreme rainfall indices in light of the actual flood occurrences to establish linkages. Several statistically significant and marginal changes in extreme rainfall trends were identified and provided key insights into reported flooding events in the district—flooding episodes were mainly attributed to the significant increases in total precipitation (PRCPTOT) and rainfall exceeding the 99th percentile of daily rainfall (R99p). Other significant contributors were declining CDD and increasing RX1day at Duthuni, increasing R40 at Musina as well as increasing R1 and declining CDD at Sane. However, the low altitude, urbanization, poor waste management and inadequate drainage systems were among the key non-climatic drivers of flood risk across the study sites, but these warrant further investigation. The complex interplay between climatic and non-climatic drivers of flood risk underscores the importance of localized climate studies and the need for adaptive strategies to minimize loss and damage. Overall, this research provides valuable insights into localized extreme rainfall trends, which are essential for developing site-specific flood mitigation and adaptation strategies. However, such initiatives require placing vulnerable communities at the centre in order to develop solutions that are locally led and relevant.

Trend and driving factors in burden of age-related macular degeneration in older adults aged 60-89years: a global analysis over three decades.

To explore temporal trends and determine driving factors of age-related macular degeneration (AMD) burden in older adults aged 60-89years at global, regional and national levels from 1990 to 2019. Prevalence and years lived with disability (YLDs) were extracted. Joinpoint regression analysis was adopted to calculate average annual percentage change and to identify the year with the most significant changes. Global trends were stratified by sex, age and sociodemographic index, and regional and national trends were explored. Decomposition analysis was conducted to determine what extent the forces of population size, age structure and epidemiologic change driving alterations of AMD burden. Globally, prevalence rate slightly increased whereas YLDs rate decreased. The year 2005 marked a turning point where both prevalence and YLDs started to decline. Regionally, Western Sub-Saharan Africa had the highest prevalence and YLDs rates in 2019, with East Asia experiencing the most notable rise in prevalence from 1990 to 2019. Global decomposition revealed that the increased case number was primarily driven by population growth and ageing, and epidemiological change was only detected to lessen but far from offset these impacts. Although there was only slight increase or even decrease in prevalence and YLDs rates of AMD in older adults, the case number still nearly doubled, which may be primarily attributed to population growth and ageing, coupled with the emerging growing pattern of prevalence rate from 2015, collectively suggesting a huge challenge in control and management of AMD.

Phase-Amplitude Coupling in Theta and Beta Bands: A Potential Electrophysiological Marker for Obstructive Sleep Apnea.

Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function. : We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices. Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%). OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.

The Impact of Environmental Governance and Quality of Life on Fertility Intentions

Objectives: Here, local environmental governance, quality of life, and fertility intention in 30 provinces, municipalities, and regions of China during 2004–2020 are also examined in terms of their co-evolution pattern. Methods: A detailed analytical method of evaluation is used by our team. It entails the determination of the environmental governance index, quality of life index and fertility intention index in order to examine their inter relacion with each other the variation and distribution within regions. Results: Our research is also demonstrated by the fact that as a whole the values of the environmental governance index and the quality of life index are increasing nationwide, which indicates that China is also experiencing certain positive changes for the better regarding environmental protection and the quality of life. Nonetheless, fertility intention index trend was characterized by increase then decrease, apparently indicating the underlying socioeconomic factors. Regional comparisons show that the East is the best place for environment governance and quality, and the fertility intention index of Northeast remains lower than other areas. Conclusions: China has become one of the advanced countries in environmental governance and improved quality of life, but the continuously decreasing level in fertility intention reflects the complex effect of changes in population policy and soci:economic factors.

Drought Awareness over Continental United States

Understanding the relationship between droughts and drought awareness is vital towards decision making and policy for water management and conservation strategies, and socioeconomic outcomes. We used computer vision (UNet models) to analyze nonlinear, heterogeneous, lagged correlations between Standardized Precipitation Evapotranspiration Index (SPEI) and Google Trends Search Interest within the Continental United States (CONUS). The most important drivers of the relationship between drought occurrence and drought awareness are the variability and ranges of drought trends and severity, as well as extreme drought conditions. This relationship was the strongest for Western states, followed by Northeastern, Southeastern, and Central regions. Search interest tends to lag droughts by a period of̃1-3 months. We also found evidence that reductionist linear approaches, such as a Principal Component Analysis, might not be as effective as UNet models in capturing the nuanced relationship between droughts and drought awareness at various dimensions and scales.

Enhanced photocatalytic degradation of organic pollutants via black phosphorus-mediated electron transfer in g-C3N4/BiOI: Degradation mechanisms and biotoxicity assessment

Photocatalysis is a promising strategy for organic pollutant removal, yet developing a capable photocatalyst remains challenging. Using black phosphorus (BP) as an electron buffer material, the ternary composite photocatalysts of xBP/g-C3N4/BiOI were prepared through a straightforward hydrothermal method. Tetracycline (TC) and Rhodamine B (RhB) removals were 100 % (120 min) and 99 % (90 min) by photocatalytic process on 2.5 %BP/g-C3N4/BiOI under xenon lamp irradiation. Photoluminescence and electrochemical measurements confirmed BP's role in reducing charge transfer barriers between g-C3N4 and BiOI, achieving effective separation of photogenerated electrons. The degradation mechanisms of TC and RhB on 2.5 %BP/g-C3N4/BiOI were revealed by the quenching experiments, electron paramagnetic resonance spectroscopy tests, three-dimensional excitation-emission matrix fluorescence spectrum, and liquid chromatography-mass spectrometry analyses. Plant toxicity assessment experiments confirmed the non-toxic nature of the TC and RhB degradation solutions. Plants grown in the treated solutions exhibited declining trends in both Malondialdehyde and Peroxidase indices compared to untreated solutions. This study offers a fresh approach to advanced photocatalyst design using charge transfer buffer materials.

Trend and inter-annual variability in regional climate models – Validation and hydrological implications in southeast Australia

We assessed the ability of Regional Climate Models (RCMs) to reproduce observed means, inter-annual variance and trends for rainfall indices that were important for runoff generation over southeast Australia. To establish the benefit of the RCM without being penalized or rewarded by the performance of the forcing GCM, we used ECMWF Re-Analysis-interim (ERA-Interim) to force the Weather Research and Forecasting model (WRF) and the Conformal Cubic Atmospheric Model (CCAM). The performance of two different configurations of each RCM was evaluated against an observational dataset (Australian Gridded Climate Data, AGCD) and compared with that of ERA-Interim. The assessments were carried out at both observational and ERA-Interim grid resolutions: ∼5 km and ∼80 km, respectively. As hypothesised, the RCMs outperformed ERA-Interim in representing spatial patterns and magnitude of mean rainfall, because of higher spatial resolution. RCMs also accurately represented the general spatial patterns of variance, but systematically underestimated the inter-annual variability over much of the domain. RCMs performed better than ERA-Interim in reproducing the magnitude of trends in some cases, especially in the decline of cool season rainfall in southeast Australia, which has had significant impacts on water resources. One of the two CCAM runs generally performed best across all rainfall indices, in part because of atmospheric spectral nudging and an improved land-surface model. Based on the findings, we have provided suggestions on where new research on the development of RCMs could be focused and recommendations relevant to the next generation of Australian hydro-climate projections generated from the sixth phase of the Coupled Model Intercomparison Project (CMIP6).

Changes in urban green space configuration and connectivity using spatial graph-based metrics in Ardabil developing city, Iran.

Urban planning is essential for managing the diverse impacts of urban green spaces, such as public access, stormwater control, urban life quality, and landscape aesthetics, promoting sustainable urban development and urban residents' well-being by integrating green space considerations into city planning. The aim of this study is to use graph-based metrics to calculate the connectivity of UGS across the main municipal zones of Ardabil city over consecutive periods under different population growth rates. Another objective of this study is to compare the connectivity values of UGS in the four municipal zones and to evaluate changes in the connectivity indices at various distance thresholds of UGS patches. After identifying UGS in different periods, the changes in graph-based connectivity indices at various distance thresholds of UGS patches were analyzed. Additionally, the changes in connectivity indices over different periods and across various municipal zones were compared and analyzed. The findings reveal that UGS areas were larger in the past but have recently had smaller patch sizes. Connectivity between UGS nodes (dNL) decreased at various distances over the study years, showing a declining trend in different connectivity indices. UGS connectivity decreased in municipal zones 1, 2, and 3 but increased in recent years after a decline until 2012 across all four zones of Ardabil city. Zone 4 had the highest UGS connectivity due to newly developed urban areas and well-allocated UGSs. Integrating the ecological impacts of UGS connectivity in urban development and design will enhance trade-offs between conservation, public health, and social equity. New urban areas should allocate sufficient land for UGS and parks, ensuring accessibility to support health and leisure through municipal planning. The study highlights the need for sustainable urban development policies that prioritize the allocation and maintenance of UGSs.

Temporal variation characteristics in the association between climate and vegetation in Northwest China

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) RNDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while RNDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of RNDVI-GP and RNDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in RNDVI-GP but an insignificant increase in RNDVI-GT, while no significant temporal changes in RNDVI-GP or RNDVI-GT were observed in the barren land. (3) The fluctuations in RNDVI-GP and RNDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in RNDVI-GP but an increase in RNDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both RNDVI-GP and RNDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations.

Coupled Spatial–Temporal Evolution and Influencing Factors of Chemical Industry Development and Water Environment in Yangtze River Economic Belt

Revealing the coordinated correlation between chemical industry development and the water environment is essential for promoting high-quality development in the Yangtze River Economic Belt. Based on the data in the Yangtze River Economic Belt from 2011 to 2021, this study explores the spatial–temporal evolution and influencing factors of the coupled coordination between chemical industry development and the water environment by using the global entropy method, a coupling coordination model, and the Tobit model. The results indicate a general upward trend in the comprehensive indices of chemical industry development and water environment systems, albeit with distinct spatial patterns. A mismatch between the two systems is observed in terms of spatial distribution. Regarding the coupling coordination degree, the relationship shows an upward trend, primarily at a mild-to-moderate coupling stage, exhibiting a spatial pattern of “downstream &gt; midstream &gt; upstream”. Moreover, a trend of increasing coordination and narrowing disparities between high- and low-level regions can be observed. The model results suggest that environmental regulation, economic development, government capacity, and urbanization play a crucial role in promoting the coupled development of the chemical industry and the water environment. However, openness to external markets may not enhance coupled coordination. These findings may provide policy guidance for the development status of two subsystems in other locations.

Elevation dependent change in ERA5 precipitation and its extremes

Mountain regions are recognised as hot-spots of climate change. Although the existence of an Elevation-Dependent Warming has been extensively confirmed in several mountain areas of the globe, fewer studies have analysed the elevational stratification of temporal trends of other climate variables, and particularly for precipitation. This study analyses changes in mean precipitation and its extremes in ERA5 global reanalysis data in key mountain areas of the globe, along with their elevational dependence, from 1951 to 2020. These include the Tibetan Plateau, the US Rocky Mountains, the Greater Alpine Region, and the Andes, as representative of different latitudes and climatic influences. Our analysis reveals common patterns of elevational dependent change in precipitation and its extremes in most of the mountainous areas, which emerge beyond their geographical differences. A positive elevational gradient of trends of extreme precipitation indices is found in the Tibetan Plateau, the Greater Alpine Region, and the subtropical Andes, highlighting a wetting effect (positive trends) at very high elevations. In contrast, the Rocky Mountains exhibit a negative elevational gradient, with a drying effect (negative trends) increasing with the elevation. Notably, a simple linear regression proved to be effective to describe the stratification of change in the Greater Alpine Region and the Rocky Mountains, whereas more complex vertical patterns need to be considered for the Andes and the Tibetan Plateau. Mean precipitation, heavy (≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}10 mm) precipitation and the length of consecutive wet days show a consistent elevation-dependent stratification within each of the study areas, suggesting possible common driving mechanisms.

Central American climate extreme trends: A statistical analysis of CLIMDEX indices

AbstractPrecipitation and temperature extremes from daily data indexed using the CLIMDEX methodology were calculated over the Central American region. The data comprises the coarsened versions of the Climate Hazards and Infrared Precipitation with stations (CHIRPs) and the corresponding data set for temperature (CHIRTs) from the year 1981 to 2020 and 1983 to 2016, respectively. The objective is to detect trend patterns in extremes in recent periods, use novel statistical techniques for assessing the trend significance and study the monthly and annual trends for each of the indices. Trends of extreme temperature indices show more consistent, robust and widespread significant results according with the observed warming of the region. Significant extreme precipitation indices trends are more localized, and therefore harder to analyse, but it seems that one robust result from several indices is the trend toward more intense extreme precipitation events in Costa Rica. The findings of this work suggest possible impacts in human and environmental systems across the region.

Sustained underweight in rural areas and emergence of overweight in urban Ethiopian women: a multivariate analysis of EDHS data 2000–2016

A growing body of evidence indicates the emergence of overweight/obesity in developing countries before the battle against undernutrition has been won. We conducted this study to quantify the reduction of underweight and the emergence of overweight among Ethiopian women from 2000 to 2016 and evaluate factors explaining the progress. We used the four Ethiopian Demographic and Health Surveys (2000–2016) to analyze body mass index (BMI) trends among women. Data from 43,815 non-pregnant, non-puerperal reproductive-age women was used to evaluate the linear change in BMI and changes in the percentage of overweight and underweight over time. Using multivariate decomposition analysis of change in underweight and overweight percentages, we identified sources of change in BMI in the past 16 years of the survey periods. The BMI of Ethiopian reproductive-age women increased by 0.88 kg/m2 from 2000 to 2016. The increment was pronounced in urban areas with 1.46 kg/m2. There has been a significant reduction in underweight women since 2000 (p-value < 0.001), and 87.62% of the changes were attributed to behavioral changes toward weight management. And there was a significant upswing in overweight women from 2000 to 2016 (p-value < 0.001) as well. A compositional change of factors including region, women’s age, women’s educational status, religion, type of place of residence, and use of contraceptives contributed to 57.51% of the observed increment in the percentage of overweight women. A relatively slow decrease in underweight and an increment in overweight have been observed. This progress can be disaggregated into persistent underweight in the rural and poorest, and swift development of overweight in the urban and richest communities. Targeted nutrition interventions for both underweight and overweight women are mandatory. Nutritional interventions in Ethiopia should focus on behavioral change to reduce hunger and malnutrition as well as to avert the emergence of overweight or obesity in the affected communities.

Scalp Electroencephalogram-Derived Involvement Indexes during a Working Memory Task Performed by Patients with Epilepsy.

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject's engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions.

Biases in Ecoacoustics Analysis: A Protocol to Equalize Audio Recorders.

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices' values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs. Thus, there is a need to reduce these biases and incongruences to ensure an accurate analysis and comparison between soundscape ecology studies and habitat assessments. In this study, we propose and validate an audio recording equalization protocol to reduce eco-acoustic indices' biases, by testing three soundscape recorder models: Song Meter Micro, Soundscape Explorer Terrestrial and Audiomoth. The equalization process aligns the signal amplitude and frequency response of the soundscape recorders to those of a type 1 level meter. The adjustment was made in MATLAB R2023a using a filter curve generated comparing a reference signal (white noise); the measurements were performed in an anechoic chamber using 11 audio sensors and a type 1 sound level meter (able to produce a .WAV file). The statistical validation of the procedure was performed on recordings obtained in an urban and Regional Park (Italy) assessing a significant reduction in indices' biases on the Song Meter Micro and Audiomoth.

Exploring trends and variability of climate change indices in the agro‐ecological zones of Pakistan and their driving mechanisms

AbstractAnthropogenic climate change induced weather and climate extremes have led to frequent heat waves, droughts and floods threatening water resources and food security for an agricultural country like Pakistan. Despite their significance, the trends and variability of extreme temperature and precipitation indices and associated large‐scale drivers in the agro‐ecological zones (AEZs) of Pakistan remain unknown and need urgent attention because of abrupt climate change. The present study documents the spatiotemporal variations of climate change indices together with the elevation‐dependent variability trends over various AEZs in Pakistan for the period of 42 years (1979–2020). Nonparametric Mann–Kendall (MK) and Sen's slope (SS) estimator tests have been employed for trend estimation. Results indicated linearly increasing (warming) and statistically significant trends in Tmean, TNx, WSDI and TR20 whereas significant decreasing (cooling) trends in cool nights (−1.73 days·decade−1) and cold spells (−1.28 days·decade−1). The spatial distribution of temperature indices trends depicts robust warming over southwestern and central zones while cooling trends over northern zones. Regarding precipitation extremes, all indices have shown increasing (wetter) trends with a significant increase in PRCPTOT and RX5day. The stations in northern and subhumid AEZs received more precipitation compared to other zones. Elevation‐dependent trends in temperature indices exhibited a statistically significant positive (negative) relationship with cold (warm) tails. Most of the extreme precipitation indices have a weak, but positive association with elevation except SDII. The weakening of South Asian subtropical upper‐level jet by a high‐pressure system over northeast Pakistan resulted in amplified land surface temperatures. However, the spatial patterns of zonal winds indicate a trough over Pakistan's southern and central parts, with warmer sea‐surface temperature, low sea‐level pressure and easterly anomalies, favour moisture transport and precipitation in Pakistan. The outcomes of present study will be useful in addressing various climate‐induced disasters occurring in various AEZs of Pakistan.

Planetary Health Diet Index Trends and Associations With Dietary Greenhouse Gas Emissions, Disease Biomarkers, Obesity, and Mortality in the United States (2005-2018)

Planetary Health Diet Index Trends and Associations With Dietary Greenhouse Gas Emissions, Disease Biomarkers, Obesity, and Mortality in the United States (2005-2018)

Spatiotemproal changes and hot spots of UTCI index over Iran

In this study, the Universal Thermal Climate Index (UTCI) gridded data from ECMWF (European Centre for Medium-Range Weather Forecasts) database was applied to assess the spatiotemproal changes in thermal comfort in Iran for 1990–2021. This index's monthly changes and trends have been determined, using the Mann-Kendall nonparametric test. Moran's I was used to compute the index's spatial autocorrelation, and the Getis-Ord Gi* statistic was used to calculate the index's hot and cold spots. The findings indicated that the majority of the country experiences thermal comfort condition from June to October. Furthermore, no location of Iran has recorded very hot or very strong heat stress. Moderate and strong heat stress has only been recorded in a few areas along the southern coasts from May to November. Most of the country experiences strong, moderate, or slight cold stress from January to May, as well as November and December. According to the Moran I autocorrelation index, the spatial pattern of UTCI in Iran is cluster throughout the year. Significant hot spots have also formed throughout the country's southern coasts, with limited spatiotemproal variability. Significant cold spots have also formed, with more temporal and spatial variability, along the Alborz and Zagros mountain ranges.

Body Mass Index Trends for the Top Five Finishers in Men's Grand Tour and Monument Cycling Events from 1994-2023: Implications for Athletes and Sporting Stakeholders.

Weight-related issues can be prevalent in elite-level sports, especially in men's road cycling, where riders may exhibit harmful behaviours, with potentially adverse outcomes for mental and physical health. This study investigated Body Mass Index (BMI) values amongst the top five finishers in the three Grand Tours and the five Monuments races between 1994 and 2023 to assess longitudinal patterns. Publicly available height and weight figures were sourced from ProCyclingStats and BMI scores were calculated for n = 154 and n = 255 individual athletes for the Grand Tours and Monuments, respectively. Two analyses were conducted with correlations and ANOVAs: the first included the BMIs of all top-five finishes and the second focussed on the BMIs of new top-five entrants. The results from both analyses revealed consistent mean BMI decreases over the years and larger effect sizes were apparent in the Grand Tours compared to the Monuments. Although lower BMIs are associated with certain performance advantages, these declining trajectories suggest a need for enhanced awareness in the cycling community and possible regulatory measures and educational programmes to promote the sustainable wellbeing of riders. This may be particularly pertinent given the wider evidence of unhealthy weight-related attitudes and behaviours throughout the sport.