Temporal Trend Analysis Research Articles

Spatiotemporal analysis of land surface temperature trends in Nashik, India: A 30-year study from 1992 to 2022

Spatiotemporal analysis of land surface temperature trends in Nashik, India: A 30-year study from 1992 to 2022

Trend analysis of temperature and vegetation cover in the distribution range of Apis florea in Iran

Trend analysis of temperature and vegetation cover in the distribution range of Apis florea in Iran

Exploring the pathophysiological influence of heme oxygenase-1 on neuroinflammation and depression: A study of phytotherapeutic-based modulation

BackgroundThe heme oxygenase (HO) system plays a significant role in neuroprotection and reduction of neuroinflammation and neurodegeneration. The system, via isoforms HO-1 and HO-2, regulates cellular redox balance. HO-1, an antioxidant defense enzyme, is highlighted due to its association with depression, characterized by heightened neuroinflammation and impaired oxidative stress responses. MethodologyWe observed the pathophysiology of HO-1 and phytochemicals as its modulator. We explored Science Direct, Scopus, and PubMed for a comprehensive literature review. Bibliometric and temporal trend analysis were done using VOSviewer. ResultsSeveral phytochemicals can potentially alleviate neuroinflammation and oxidative stress-induced depressive symptoms. These effects result from inhibiting the MAPK and NK-κB pathways - both implicated in the overproduction of pro-inflammatory factors - and from the upregulation of HO-1 expression mediated by Nrf2. Bibliometric and temporal trend analysis further validates these associations. ConclusionIn summary, our findings suggest that antidepressant agents can mitigate neuroinflammation and depressive disorder pathogenesis via the upregulation of HO-1 expression. These agents suppress pro-inflammatory mediators and depressive-like symptoms, demonstrating that HO-1 plays a significant role in the neuroinflammatory process and the development of depression.

Breath of Change: Evaluating Asthma Information on TikTok and Introducing the Video Health Information Credibility Score.

Introduction Asthma's global prevalence underscores the need for accessible health information dissemination, especially in the digital age. TikTok, known for its wide reach and diverse content, presents both opportunities and challenges in health information dissemination. This study aims to characterize the quality and reach of asthma-related content on TikTok and introduces the Video Health Information Credibility Score (VHICS) as a novel tool for quality assessment. Materials and methods We used a systematic methodology to analyze the top 100 TikTok videos by the number of likes tagged with #asthma. Data were collected in June 2023 and January 2024 to allow for temporal trend analysis. Videos were evaluated based on engagement metrics (views, likes, comments, shares, and favorites) and quality using the DISCERN instrument. Results Our analysis showed that physician-generated content accounted for a significant proportion of asthma-related videos, with varying levels of engagement. The DISCERNscores, with a range of 1 (lowest) to 5 highest),provided insights into content quality, revealing trends in user engagement and information reliability over time. Temporal analysis indicated changes in content creation and audience interaction. Discussion The study highlights the evolving landscape of digital health communication on TikTok. The introduction of VHICS added depth to the quality assessment of future directions, indicating the necessity for accurate and reliable health information on social media. The findings suggest an imperative for healthcare professionals to address misinformation and leverage digital platforms for patient education effectively. Conclusions TikTok is a significant medium for health information dissemination, with substantial potential for impact in patient education. The introduction of VHICS can enrich the analysis of video content, offering a robust tool for assessing the quality of health information on social media. This study underscores the importance of credible, clear, and audience-relevant health communication in the digital era.

Effect of long-term climate signatures on regional and local potato yield in Finland

This research study investigates the impact of air temperature and precipitation on annual potato crop yield in Finland region and a local area in northern Finland. For this, the annual crop yield data of regional and local case study area is processed using Z-score normalization technique. Classification of computed z-score values was carried out into different classes ranging between the most beneficial crop yield year and the most vulnerable crop yield year. Later, the detection of feasible potato cropping season at monthly and daily scale was carried out using different weather parameters. Further, long-term trend analysis using Mann-Kendall's approach at annual, seasonal, and monthly scales was carried out using 60 years of dataset of both case study areas. Then after, the comparative analysis of annual crop yield and the characteristics obtained within climate data using different statistical approaches at annual, seasonal, and monthly scale. Finally, multivariate analysis was carried out to find most influential climate variables obtained using different statistical signatures. The results shows that, over the 100 years of period the annual potato crop yield of regional case study area shows a rising trend with declining area under potato crop. Classification approach found 16 % annual yield scored lowest Z-score while, 18% the highest. Likewise, 20 years of data for the local case study area found that 25 % of the dataset scored the highest Z-score and 15 % of the dataset values scored the lowest. Long-term trend analysis of air temperature shows significant increasing trend annually, seasonally and for monthly during the months between July-September. Whereas, similar procedure with the precipitation data showed increasing trend only at annual scale with the precipitation data analysis. During the comparative analysis between the annual crop yield data based on z-score classification and different statistical results obtained from weather parameters such as variation of precipitation and temperature sum, long-term climate data maximum-minimum totals seasonally as well as monthly during crop growing season; noticeable anomalies were observed in the weather parameters in line with the crop yield years grouped into the lowest and the highest Z-scores. The Multivariate analysis emphasized the impact of air temperature over precipitation on potato crop yield. Present study provides quantitative assessment on usefulness of long-term climate signatures for region specific either event-based or crop-based modelling development efforts to provide efficient decision support for enhancing farm-level crop productivity and sustainability of local and regional agriculture.

The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2021-2022.

This report by the European Food Safety Authority and the European Centre for Disease prevention and Control, provides an overview of the main findings of the 2021-2022 harmonised Antimicrobial Resistance (AMR) monitoring in Salmonella spp., Campylobacter jejuni and C. coli from humans and food-producing animals (broilers, laying hens and fattening turkeys, fattening pigs and cattle under one year of age) and relevant meat thereof. For animals and meat thereof, AMR data on indicator commensal Escherichia coli, presumptive extended-spectrum beta-lactamases (ESBL)-/AmpC beta-lactamases (AmpC)-/carbapenemase (CP)-producing E. coli, and the occurrence of methicillin-resistant Staphylococcus aureus (MRSA) are also analysed. Generally, resistance levels differed greatly between reporting countries and antimicrobials. Resistance to commonly used antimicrobials was frequently found in Salmonella and Campylobacter isolates from humans and animals. In humans, increasing trends in resistance to one of two critically antimicrobials (CIA) for treatment was observed in poultry-associated Salmonella serovars and Campylobacter, in at least half of the reporting countries. Combined resistance to CIA was however observed at low levels except in some Salmonella serovars and in C. coli from humans and animals in some countries. While CP-producing Salmonella isolates were not detected in animals in 2021-2022, nor in 2021 for human cases, in 2022 five human cases of CP-producing Salmonella were reported (four harbouring bla OXA-48 or bla OXA-48-like genes). The reporting of a number of CP-producing E. coli isolates (harbouring bla OXA-48, bla OXA-181, bla NDM-5 and bla VIM-1 genes) in fattening pigs, cattle under 1 year of age, poultry and meat thereof by a limited number of MSs (5) in 2021 and 2022, requires a thorough follow-up. The temporal trend analyses in both key outcome indicators (rate of complete susceptibility and prevalence of ESBL-/AmpC-producers in E. coli) showed an encouraging progress in reducing AMR in food-producing animals in several EU MSs over the last 7 years.

A Century of Reforestation Reduced Anthropogenic Warming in the Eastern United States

AbstractRestoring and preserving the world's forests are promising natural pathways to mitigate some aspects of climate change. In addition to regulating atmospheric carbon dioxide concentrations, forests modify surface and near‐surface air temperatures through biophysical processes. In the eastern United States (EUS), widespread reforestation during the 20th century coincided with an anomalous lack of warming, raising questions about reforestation's contribution to local cooling and climate mitigation. Using new cross‐scale approaches and multiple independent sources of data, we uncovered links between reforestation and the response of both surface and air temperature in the EUS. Ground‐ and satellite‐based observations showed that EUS forests cool the land surface by 1–2°C annually compared to nearby grasslands and croplands, with the strongest cooling effect during midday in the growing season, when cooling is 2–5°C. Young forests (20–40 years) have the strongest cooling effect on surface temperature. Surface cooling extends to the near‐surface air, with forests reducing midday air temperature by up to 1°C compared to nearby non‐forests. Analyses of historical land cover and air temperature trends showed that the cooling benefits of reforestation extend across the landscape. Locations surrounded by reforestation were up to 1°C cooler than neighboring locations that did not undergo land cover change, and areas dominated by regrowing forests were associated with cooling temperature trends in much of the EUS. Our work indicates reforestation contributed to the historically slow pace of warming in the EUS, underscoring reforestation's potential as a local climate adaptation strategy in temperate regions.

Assessment of observed temperature trend patterns of Bhubaneswar city, India with special prominence on future projections using SimCLIM climate model and farmer’s perception

<p>Temperature dynamics is a widely recognized indicator of the global warming phenomenon. Changes in temperature patterns in Bhubaneswar, India, were assessed by examining the monthly minimum and maximum temperature data for 60 years (1956–2015) sourced from the Indian Meteorological Department. SimCLIM climate change risk assessment software was used for projecting the temperature regime for four different representative concentration pathways. Further, a survey of 112 farmers was conducted to understand their perceptions of temperature variations in and around Bhubaneswar city using a multi-stage sampling technique. Mann–Kendall statistics and linear regression were used to analyze the monthly temperature data and trend detection. The study reveals a change of +4%,-4.44%, and +1.09% in the mean monthly maximum, minimum, and annual temperature. The results of the future projection show a temperature change of 0.81°C for RCP 2.6, 1.12°C for RCP 4.5, 1.03°C for RCP 6.0, and 1.54°C for RCP 8.5 for the year 2050. Confirming the analysis findings, most of the interviewed farmers also perceived increasing temperatures and decreasing precipitation in and around the city. The study outcome of temperature trend analysis and future projections will be helpful for farmers and policymakers in formulating adaptation strategies to climate change.</p>

Trend analysis of precipitation, temperature and snow water equivalent in Lombardy region, northern Italy

The analysis of precipitation, temperature, and snow water equivalent (SWE) trends offers a scientific approach for understanding the impacts of climate change. This paper presents a comprehensive analysis of climate change indicators in Lombardy, Italy, covering the yearly and monthly trends of precipitation and temperature from 1990 to 2020. Additionally, the yearly and monthly SWE variations. For this purpose, a range of statistical tests have been used including Mann–Kendall, Pettitt’s change point detection and Sen’s slope estimator. Precipitation trend shows a slight annual increase of around 5.42 mm per year. This trend is not statistically significant with a Mann–Kendall p value of 0.1448 and no changing point has been detected. Moreover, seasonal precipitation patterns show minor variations, with Kendall’s Tau values ranging from − 0.0431 to 0.1761. However, none of these trends are statistically significant, as reflected in Mann–Kendall p values ranging from 0.1679 to 0.7339. Conversely, Lombardy is experiencing a significant annual temperature increase of 0.0436 °C. Notably, in Autumn, temperatures rise at a rate of 0.0565° per year. Summer also shows a significant warming trend, with temperatures increasing by 0.0421° per year. In Winter and Spring, there are milder, non-significant temperature trends, with Kendall’s Tau values around 0.17. SWE trend shows minor annual variations (5–10%) and monthly shifts. Winter shows a slight decrease (2–3%), implying delayed snow accumulation, while Spring indicates minor change (1–2%) suggesting earlier snowmelt. This study emphasizes temperature's strong impact on SWE and stresses the importance of climate monitoring and collaboration for understanding changing climate patterns.

Analysis of Temperature Trends and Variations in the Arabian Peninsula’s Upper Atmosphere

Analysis of Temperature Trends and Variations in the Arabian Peninsula’s Upper Atmosphere

Transplant management in Brazil: a temporal analysis of financial investments and procedures.

To analyze public management actions regarding organ, cell, and tissue transplant procedures and their financial investments in Brazil. Mixed (time and place) ecological study, carried out based on data from the Hospital Information System of the Brazilian Public Health System (SUS) Information Technology Department and the National Transplant System, from 2001 to 2023. Temporal trend analyses, descriptive and inferential statistics were performed. Organ, cell, and tissue transplants are concentrated in the Southeast region of the country, with increased costs there. The Northeast and South regions of Brazil have the longest waiting list, with an increasing trend (R2 = 0.96), associated with a decreasing trend in the number of transplants (R2 = 0.97). The difference in the total number of transplants and procedures performed among the Brazilian regions represents the need for organization and investments with strategies aimed at training professionals and raising awareness among the population.

Pollution characteristics of heavy metal(loid)s in soil in China: Implications for health risk assessment and temporal trend analysis

The ecological and human health risks associated with heavy metal(loid)s (HMs) have attracted much attentions worldwide. In this study, 153 topsoil samples were collected across China in 2019, aiming to investigate the HMs pollution characteristics. The soil samples were collected from areas such as parks, schools, communities, and rural regions, which were far away from pollution sources of HMs. In order to study the temporal trend of pollution, related studies from 2000 to 2015 in China were also summarized. The findings indicated that Cd, Cu, Zn, and Pb were the major HMs with the mean concentrations of Cd, Cu, Zn, and Pb were 0.40, 36.5, 107, and 33.5 mg/kg, respectively. High background values and metal processing resulted in high total concentrations of Cd, As, Cr, and V especially in Southwest China (such as Guizhou and Yunnan provinces). The result of the Positive Matrix Factorization (PMF) model indicated the primary source of HMs was natural source (45.3%), followed by traffic source (20.6%), industrial source (17.3%), and agricultural source (16.8%). The health risk assessment of HMs indicated that non-carcinogenic risks were minimal, however, carcinogenic risks (95th) for As, Cr, and Cd should attract attentions. Compared with the measurements from 2000 to 2015, the pollution levels of HMs showed a decreasing trend in China in 2019, which indicated the effectives on HMs control along with the implementation of the control policy on soil in China.

Surveillance of TB-HIV coinfection in Brazil: a space-time approach.

To identify the epidemiological, spatial, and temporal pattern of TB-HIV coinfection in Brazil during the period from 2001 to 2020. Ecological study using space-time analysis techniques. It included cases of TB-HIV coinfection registered in Brazil from 2001 to 2020. The temporal trend analysis was performed using segmented regression by Joinpoint regression. For spatial analysis, Moran indices were calculated and choropleth maps were produced using TerraView and QGIS software. A stable temporal trend was observed in the incidence rates of TB-HIV coinfection in Brazil during the analyzed period. In addition, high-risk areas for coinfection located in states in the North, Southeast, South, and Midwest regions were identified. There was stability in the incidence of TB-HIV coinfection in Brazil over the last 20 years and heterogeneous geographic distribution of risk areas for the condition.

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran.

Temperature fluctuations and related factors are among the main causes of climate change. Understanding the temporal and spatial variations in temperature can shed light on how species respond to climate change. Plants generally persist in suitable microclimates in response to environmental change; however, examining long-term temperature variations within a species' range can be challenging using field observations. Thermal remote sensing, on the other hand, provides multi-scale time-series data with good coverage and regularity to overcome the challenges associated with field observations in environmental monitoring. Although changes in land surface temperature (LST) affect climate, hydrological processes, land-atmosphere interactions, and ecological activities, this metric has not received much research attention. This study aimed to analyze changes in habitat suitability and microclimatic conditions for Moringa peregrina. Seasonal changes in LST within the distribution range of the species were also investigated. To this aim, mean seasonal LST was computed in Google Earth Engine using the daily MODIS/006/MYD13A2 product from 2003 to 2023. Subsequently, a binary habitat suitability map was created based on the true skill statistic (TSS). The Mann-Kendall test was used to analyze seasonal LST trends. Major trends in LST were quantified based on the z-score, and compatibility with habitat suitability was evaluated via GAP analysis and the Kappa index. Seasonal temperature trends were evaluated by comparing each season with the following season using binary comparison. Landforms at presence points were regarded as microclimates and the sensitivity of microclimates to LST was evaluated using two methods: Principal component analysis (PCA) was used to quantify seasonal LST heterogeneity and the random forest (RF) approach was used to evaluate the effect of environmental parameters on habitat suitability within microclimates. The Kappa index revealed a weak overlapping between suitable / unsuitable habitat and the surfaces affected by the trend of changes. Moreover, the suitable habitat of Moringa peregrina in spring, autumn and winter is spatially overlapped by areas that have shown an increasing LST trend, and the presence points have not experienced an increasing temperature trend only in the summer. The findings show that the analysis of seasonal trends in LST provides insights into the effect of LST on habitat suitability and the condition of vegetation. The current study clearly shows that seasonal changes have had a significant impact on the distribution and habitat suitability of M. peregrina, particularly during summer and winter. Improved habitat suitability and range expansion were observed throughout the year. The study also highlights the role of landforms in regulating temperature. Landforms such as local ridges with minimal temperature fluctuations and regions near the Oman Sea were identified as potential future habitats due to favorable humidity conditions.

Spatial and Temporal Analysis of Maximum and Minimum Temperature Trends in Northern Sudan during (1990-2019)

Spatial and Temporal Analysis of Maximum and Minimum Temperature Trends in Northern Sudan during (1990-2019)

Assessing Climate Variability and Its Impacts on Selected Forest Ecosystems in Taraba State: Insights from the Mann-Kendall Trend Analysis of Rainfall and Temperature

This study examines climate variability and its effects on selected forest ecosystems in Taraba State, Nigeria, using Mann-Kendall trend analysis of rainfall and temperature data from 1991 to 2021. Climatic variables, including average monthly rainfall and mean minimum and maximum temperatures, were sourced from the Upper Benue River Basin Development Authority. The Mann-Kendall test was applied to assess trends, revealing slight upward trends in annual rainfall and maximum temperatures, and a subtle downward trend in minimum temperatures, although none were statistically significant. Hypothesis testing was conducted, with results suggesting no significant long-term trends in annual rainfall, maximum temperatures, or minimum temperatures over the study period. Specifically, for annual rainfall, the Mann-Kendall slope was 0.03 with a p-value of 0.96, indicating no significant trend. Similarly, for minimum and maximum temperatures, the Mann-Kendall slopes were -0.01 and 0.01, respectively, with p-values of 0.99, indicating no significant trends. It was recommended that strengthening monitoring efforts to track long-term climate trends accurately, utilizing advanced statistical techniques to discern meaningful patterns from natural variability among other recommendations.

Using remote sensing techniques to delineate SDS “hotspot” source regions

Operational remote sensing (ORS) is an effective tool for hazard zonation of the dust source areas for remediation and vegetation purposes. Various ORS satellite monitoring techniques, including NASA MODIS Aqua/Terra, Landsat and ESA Sentinel, were used to delineate a major sand and dust storm (SDS) “hotspot” area in the Mesopotamia region of southern Iraq. SDS blown from this “hotspot” area is transboundary and travels thousands of kilometres from the source affecting multi-countries, including Kuwait, Saudi Arabia, Bahrain, and Qatar. We applied various ORS datasets to clearly delineate the “hotspot” area with high temporal and spatial resolution. The techniques used include: (1) surface composition analysis and mapping, (2) vegetation mapping, (3) topographic and soil moisture, (4) aerosol optical depth (AOD), and (5) temporal monitoring and trend analysis. ORS identified severe wind erosion located in the top center (hotspot 1) and southwest (hotspot 2) regions of the “hotspot” area. By leveraging these ORS techniques scientists can properly assess and understand the soil structure of areas prone to SDS, delineating factors contributing to soil erosion and SDS generation. This understanding is fundamental for implementing effective land management strategies, conservation efforts, and early warning systems aimed at mitigating the impacts of SDS on both local and transboundary scales.

Hanseníase em menores de quinze anos no município mais hiperendêmico do Brasil

ABSTRACT Objective: To describe leprosy involvement and physical disability profiles in children and adolescents under 15 years old. Methods: Ecological time series study, based on data from the Brazilian Notifiable Diseases Information System, including new cases of leprosy residing in Palmas (TO), from 2001 to 2020. Results: A total of 471 notified cases in children and adolescents under 15 years of age were evaluated, resulting in a detection coefficient of 26.5 per 100,000 inhabitants. Of these, 52% (n=243) were women, 5% (n=24) corresponded to grade two disability, and 36% (n=168) were diagnosed through spontaneous demand. The temporal trend analysis showed a 0.5% reduction in the detection coefficient. There was a significant decrease in the diagnosis of the undetermined and tuberculoid clinical forms and a significant increase in the dimorphous form. Diagnosis through contact examination increased significantly by 13.1% and that through spontaneous demand decreased by 4.9%. The detection coefficient of cases with grade two disability reduced significantly by 7.4% while those with grade one increased by 16.8%. Conclusions: Despite the downward trend in the detection coefficient in children and adolescents under 15 years of age and in cases with grade two disability, other factors indicate failure in the adequate management of leprosy in Palmas.

High-resolution sequence stratigraphy research based on continuous wavelet transform and INPEFA - A case study in the Kalashayi formation, Tarim Basin, China

The Carboniferous Kalashayi Formation, situated in the Lungu-Sangtamu area within the Tarim Basin, exhibits protracted sedimentation periods, intricate sand-mud depositional sequences, and scant paleontological and core datasets. Precision in delineating high-resolution sequences using conventional core and logging data poses a considerable challenge. To enhance the stratigraphic accuracy of the Kalashayi Formation in the Tarim Basin and facilitate quantitative analysis, this study employs continuous wavelet transform on the gamma ray (GR) curves obtained from core wells within the study area. Subsequently, various sequence boundaries are discerned by integrating the resulting wavelet coefficient curves with time-frequency energy maps. Discrimination and subdivision of base-level cycle structures of varying orders are achieved through temporal trend analyses of integrated prediction error filter analysis (INPEFA) curves. Integration of drilling, logging, lithofacies, and core data enables the identification and subdivision of high-resolution sequence stratigraphy using wavelet analysis and INPEFA techniques. Ultimately, the Carboniferous Kalashayi Formation in the Lungu-Sangtamu region is classified into 2 long-term, 5 medium-term, and 14 short-term base-level cycles, establishing a meticulously delineated isochronous stratigraphic framework. This framework serves as a fundamental basis for subsequent discussions on reservoir prediction within the study area.

Long-term spatial and temporal trend analysis of stream flow and suspended sediment transport of Godavari River Basin, India

Long-term spatial and temporal trend analysis of stream flow and suspended sediment transport of Godavari River Basin, India