We present a year-long experiment using a pinhole camera to determine the Sun's angular size, employing a flat mirror to project large-scale solar images of about 50–60 cm in diameter. Our analysis resolves the annual angular variation of 65 arc sec, reflecting Earth's elliptical orbit. Additionally, we observed atmospheric seeing effects (the effects of atmospheric turbulence) and sunspots visible with the naked eye. The project offers an accessible platform for high school and undergraduate students to engage in scientific inquiry.

Secondary analysis of a prospective cross-sectional study at an academic tertiary spine care center. To examine the prevalence and risk factors for preoperative Vitamin D (VitD) deficiency and secondary hyperparathyroidism (SHPT), and to assess the seasonal variation of metabolic bone laboratory parameters in patients undergoing lumbar fusion surgery (LFS). LFS relies on adequate connective tissue quality and bone healing capacity. VitD deficiency and SHPT significantly impact bone metabolism and are linked to lower fusion rates and poorer bone quality. However, their seasonal variation in LFS patients remains unexplored. Patients undergoing LFS for degenerative conditions received preoperative VitD, parathyroid hormone (PTH), and bone turnover markers laboratory routinely from December 2014 to December 2023. Descriptive and comparative statistics, logistic regression, and univariable and multivariable cosinor regression models were used to evaluate VitD status, SHPT prevalence, their risk-factors and seasonal variations in VitD, PTH, and bone turnover markers. Data from 431 patients (49% female, median age 64y) was analyzed. VitD insufficiency (<30ng/mL) was observed in 34% of patients, ranging from 48% in winter to 25% in summer. SHPT was present in 24%, with winter prevalence at 28%. Surgery during winter and spring was associated with a 7.5-fold increased risk of VitD deficiency and a 2.1-fold increased risk of SHPT. Seasonal changes with peaks for VitD, PTH, and bone-specific alkaline phosphatase were observed in July, February, and November, respectively, with no significant annual variation in other bone metabolism markers. The prevalence of VitD deficiency and SHPT in LFS patients is high, especially during winter and spring. Seasonal variations in VitD and bone metabolism markers suggest that single-timepoint laboratory evaluations may not reflect bone metabolism throughout the year, highlighting the need for further studies investigating whether seasonal factors in preoperative assessments could affect outcomes.

The gravity recovery and climate experiment (GRACE) and GRACE follow-on (GFO) gravity observations have significantly improved our understanding of the terrestrial water cycle. However, GRACE-assimilated (GA) hydrological models still differ significantly. This paper uses global navigation satellite system (GNSS) data to assess two global GA datasets: Global land water storage release 2 (GLWS2.0) and catchment land surface model GRACE data assimilation (CLSM-DA). From 2004 to 2019, the mean annual amplitude of equivalent water thickness (EWT) of these datasets differs by more than 25mm over 40% of the modeled land area, and the timing of peak water storage diverges by as much as 30-days across 50% of their domain. We compare the modeled hydrological loading vertical displacement predicted from these models with GNSS uplift data to compare and contrast the model quality. Using river basin boundary information from 89 rivers, we cluster 9,163 global GNSS stations, each with at least three years of daily data. Results show that CLSM-DA generally agrees better with GNSS data across more river basins. Its 100-300mm larger annual water variation accounts for better agreement in Africa, Southeast Asia, and parts of South America. In regions like the Western United States and Eastern Europe, where both models estimate similar annual amplitudes, CLSM-DA's 30-60day phase delay improves alignment with GNSS. This evaluation also reveals key limitations in both models, especially during extreme hydrological events such as droughts, and highlights the value of geodetic observations in advancing GA hydrological modeling.

This paper aims to study the spatiotemporal variations in PM2.5 concentrations between 2015 and 2020 in the Fen–Wei Plain. The AOD products of MCD19A2 based on MAIAC were utilized. Besides of AOD, some of its arithmetic values were also introduced to determine the best variable. AOD was determined as the variable for retrieval because of its highest correlation coefficient with PM2.5, reaching up to 0.526**. Several statistical models and SVR have been used and compared for establishing the best retrieval model. Results showed, the determination coefficient r 2 of the cubic function was the best (r 2 = 0.294**), and the correlation between the predicted and measured values was strong (k = 1.1478, r 2 = 0.532**). Both monthly and annual variations of PM2.5 concentrations were researched, which indicated the changing trend was fluctuating. The mean value in 2015 was the largest, reaching up to 38.02 μg/m3, the smallest value of 28.28 μg/m3 appeared in 2019. It can be concluded the influencing mechanism of PM2.5 was complicated, as proven by correlation analysis and gray relational analysis. The influencing factors should be introduced as auxiliary data to promote the retrieval accuracy. With advancements in remote sensing technology, the monitoring efficiency can be effectively improved, which will greatly promote sustainable development.

Background All the scholarly papers on “Job Satisfaction” and “Motivation” published from the year 2014 to 2023 constitute the database for conducting a scientometric analysis. Methods The types of records in the literature, including authors, nations, keywords, references, and citation counts, were studied using scientometric analysis. The keywords “Job Satisfaction” and “Motivation” were used to gather all data from the SCOPUS database as of January 10 th , 2025. Both VosViewer and Biblioshiny were used to analyze the data. AScientometric method was used to determine the various parameters that fulfilled the research objectives. Results The study finds that there has been an increasing trend of publications and their corresponding citations from the year 2014 to 2023 and the USA publications received the highest number of citations of 8350, followed by the Netherlands (4832 citations), and the United Kingdom (2595 citations). Conclusion The evolution of publications on “Motivation” and “Job Satisfaction” from 2014 to 2023 showed a steady growth rate, despite annual variations over the previous ten years. Research on job satisfaction and motivation has advanced through the work of authors from the USA. We mapped the entire research structure and features of job satisfaction research over the past decade. This was accomplished by examining the research topics of motivation and the analysis revealed a gradual rise in scientific output on the subject of “Job Satisfaction” and “Motivation” from 2014 to 2023. Overall, the study’s findings show that research productivity in the Human Resource Management literature is increasing, which seems to be a healthy trend. The findings of this study add niceties to the corpus of existing literature.

Climate fluctuations are expected to drive a decline in the growth of many conifer and broadleaf species, especially in the Mediterranean region, where these species grow at or very near the southern limits of their distribution. Such trends have important implications not only for forest productivity but also for plant diversity, as shifts in species performance may alter competitive interactions and long-term community composition. Using tree-ring data sourced from two Abies cephalonica stands with different elevation in Mount Parnassus in Central Greece, we evaluate the growth responses of the species to climatic variability employing a dendroecological approach. We hypothesize that radial growth at higher elevations is more strongly influenced by climate variability than at lower elevations. Despite the moderate to relatively good common signal indicated by the expressed population signal (EPS: 0.645 for the high-altitude stand and 0.782 for the low-altitude stand), the chronologies for both sites preserve crucial stand-level growth patterns, providing an important basis for ecological insights. The calculation of the Average Tree-Ring Width Index (ARWI) for both sites revealed that fir in both altitudes exhibited a decline in growth rates from the late 1980s to the early 1990s, followed by a general recovery and increase throughout the late 1990s. They also both experienced a significant decline in growth between approximately 2018 and 2022. The best-fit model for annual ring-width variation at lower elevations was a simple autoregressive model of order one (AR1), where growth was driven exclusively by the previous year’s growth (p &lt; 0.001). At the higher elevation, a more complex model emerged: while previous year’s growth remained significant (p &lt; 0.001), other variables such as maximum growing season temperature (p = 0.041), annual temperature (inverse effect, p = 0.039), annual precipitation (p = 0.017), and evapotranspiration (p = 0.039) also had a statistically significant impact on tree growth. Our results emphasize the prominent role of carry-over effects in shaping their annual growth patterns.

ABSTRACT This study investigated the relationship between soil type and paddy yield in Japan on a national scale. Previous studies have primarily relied on field experimental data and were limited to site comparisons within regions under similar climatic conditions, making it challenging to clarify the influence of soil factors on paddy yields independently of climatic factors. To address this issue, we conducted a big data analysis using nationwide databases to statistically examine the relationship between soil type, climate, and paddy yield. A generalized additive model was used to evaluate the effects of soil distribution patterns and climatic conditions on paddy yields, based on municipal-level databases from 1993 to 2019. Soil distribution patterns within each municipality were categorized into five classes according to the proportion of the distribution area of lowland soil groups. In addition to soil distribution and climatic conditions, the model included prefecture and year as explanatory variables to account for fixed effects related to rice variety, management practices, and annual variation. The results showed that paddy yields tended to be higher in municipalities with a large distribution area of the Gray lowland soil group compared to those with other lowland soil groups. This finding reinforces the existing understanding of the influence of soil drainage conditions on crop growth and highlights the importance of soil management and assessment in rice cultivation. Furthermore, aggregating the distribution trends of soil types at the municipal level proved to be an effective approach for evaluating crop productivity at the national scale from the perspective of soil conditions. This study underscores the value of soil map information by clarifying its relationship with productivity and proposing strategies for its effective utilization.

Oxygen allocation dynamics in a seagrass Zostera marina meadow.

Annual variation in gonadal parameters and the effects of estradiol (E2) on ovarian development in the thick-shelled mussel, Mytilus coruscus

Seasonal influenza continues to pose a substantial and recurrent public health challenge in Queensland, driven by annual variability in transmission and uncertainty in climatic, demographic, and behavioural determinants. Predictive modelling is constrained by data limitations and parameter uncertainty. In response, this study developed a Bayesian network (BN) model to estimate the probability of influenza epidemics in Queensland, Australia. The model integrated diverse inputs, including international and local influenza surveillance data, demographic health statistics, and expert and stakeholder insights to capture the complex multifactorial causal relationships underlying epidemic risk. Scenario-based simulations revealed that Southeast Asian viral origin, severe global influenza seasons, peak season timing, increasing international travel, absence of control measures, and low immunisation rates substantially elevate the likelihood of influenza epidemics. Southeast Queensland was identified as particularly vulnerable under high-risk conditions. Model evaluation demonstrated good discriminative performance (AUC = 0.6974, accuracy = 70%) with appropriate uncertainty quantification through credible intervals and sensitivity analysis. Its modular design and capacity for integrating various data sources make it a practical decision-making support tool for public health preparedness and responding to evolving climatic and epidemiological conditions.

ABSTRACTHippophae tibetana Schltdl, a valuable plant with significant edible, medicinal, and ecological restoration functions, has long attracted considerable attention. This study, based on the MaxEnt model, combines current and future climate scenarios (2050s and 2070s) to predict the distribution of suitable habitats for H. tibetana. The results demonstrated that the spatial distribution patterns of H. tibetana are primarily governed by the combined effects of key environmental factors, including elevation gradient, annual precipitation variation, and mean annual temperature fluctuation. Modeling results demonstrate that H. tibetana currently occupies 157.62 × 104 km2 of suitable habitats, showing high concentration in three key zones: (1) Qinghai's eastern‐southwestern belt, (2) Gansu's southeastern/Sichuan's western‐southeastern corridor, and (3) Tibet's eastern‐southwestern quadrant. Under future climate scenarios, with increasing temperatures and changes in precipitation patterns, the suitable habitats for Hippophae are generally expected to expand northeastward, particularly in high‐altitude and northwestern regions where the environment becomes more favorable. However, in some extreme climate scenarios, significant changes in temperature and precipitation could have negative effects on the growth and expansion of Hippophae. The study suggests that climate change may drive H. tibetana to expand into more suitable areas, but it may also lead to the reduction or migration of suitable habitats in some regions. Therefore, future ecological conservation and planting plans for Hippophae should fully consider the impact of climate change and adopt flexible adaptive management strategies to ensure its sustainable development in the context of climate change.

Exploring climate adaptation in European Merino sheep: a landscape genomics approach.

To understand the potential suitable habitats of Limosa limosa and clarify the dominant environmental factors affecting its distribution, we collected a total of 239 distribution sites and 29 environmental variables, and simulated with the MaxEnt model. The results showed that the dominant factors influencing the suitable habitats for L. limosa during the breeding period included isothermality, slope, elevation, distance to major water, distance to paddy field, distance to village, and mean temperature of the coldest quarter. During the breeding period, L. limosa preferred inland wetlands and their surrounding grassland and farmland with high annual temperature variation, low winter temperature, medium elevation, low slope, near water sources and with little human activity. The dominant influencing factors during the overwintering period were precipitation of the coldest quarter, slope, distance to major water, normalized vegetation index, elevation, and mean diurnal temperature range. During the overwintering period, L. limosa preferred areas with a certain amount of rainfall during the coldest season, low elevation and slope, closer to water sources, low temperature variation and suitable degree of concealment. The highly suitable area for the L. limosa during the breeding period covered an area of 17.8×104 km2, and was mainly distributed in northern Xinjiang, central and northeastern Inner Mongolia, with a few breeding sites in Heilongjiang and Jilin provinces. The highly suitable area for the overwintering period covered an area of 6.1×104 km2, and was mainly distributed in the middle and lower reaches of the Yangtze River (such as Hunan, Hubei, Jiangxi provinces) and its southern coastal provinces (such as Fujian and Guangdong provinces). Due to the influence of human activities and global warming, the wintering area of the L. limosa has gradually shifted from the coastal areas to the middle and lower reaches of the Yangtze River in recent years. Our findings hold significant implications for the conservation of L. limosa population and habitat management.

A 20-year assessment of AGBD accumulation and its drivers in China's broad-leaved forests across temperature zones.

Annual and Interannual Variability of Chlorophyll-a in the Indian Ocean Tuna Fishing Ground WPPNRI-573

Analysis of Annual Variation in Nighttime 4.3 µm Radiance Under Aurora Disturbance and Correlation with Disturbance Parameters

Abstract Temporal variations of the M2 tidal parameters in gravity are observed at all superconducting gravimeter stations. We specifically investigate the annual variation of M2 tidal parameters. A similar variation is observed for the parameters from sea surface heights which is larger than expected from astronomical forcing alone. This leads to the hypothesis that the variations of the gravimetric tidal parameters are caused by the loading of the annual variation of M2 in the oceans. Only nonlinear, time-stepping ocean models are able to describe such variations. We use sea surface heights from three global and two regional models of this kind to calculate the loading. The loading time series is then added to synthetic body tides and analyzed by a moving window tidal analysis with ETERNA in the same way as the measured data. We compare the resulting variations of the M2 tidal parameters for synthetic gravity with those observed from measurements. Three of the five ocean models show an annual variation of a similar order of magnitude which supports our hypothesis. The other two ocean models produce smaller or no clear annual variation of the M2 tidal parameters. In the ocean the annual variation of M2 has large amplitudes in shelf areas and small amplitudes in the open ocean. Large areas with small amplitude might contribute to the gravity loading as much as small areas with large amplitudes do. We investigate this with the global Hycom model at three SG stations. The investigation shows that not only close shelf areas but also distant ocean regions, including open ocean areas, contribute significantly to the annual variation of the M2 tidal parameters at the superconducting gravimeter stations.

Generic drug entry into the pharmaceutical market typically leads to a substantial decline in originator sales. Understanding the extent and trajectory of this erosion is essential for effective lifecycle management and strategic planning. This study quantified sales erosion after generic entry for originator drugs approved in the United States between 2010 and 2019 and developed a model to predict year-specific sales retention based on key product- and market-level characteristics. A total of 140 originator drugs were analyzed using FDA approval records and sales data from Evaluate Pharma. Five-year retention patterns were modeled using a three-parameter exponential decay function. Subgroup analyses were conducted by year of generic entry, therapeutic class, and product-specific features. A polynomial regression model using 700 product-year observations incorporated three binary market indicators and linear and quadratic time terms. Sales retention declined from 73.1% in the first year after generic entry to 31.7% by year five. The exponential decay model demonstrated a strong goodness-of-fit (root mean squared error [RMSE] = 0.006), capturing the initial steep decline and subsequent stabilization. Subgroup analyses showed faster erosion for blockbuster drugs and in markets with multiple first-generation generics. The regression model explained 96.4% of annual variation in retention (RMSE = 0.033), accounting for product and market heterogeneity. Sales decline after generic entry follows a predictable yet heterogeneous trajectory shaped by product and market factors. Exponential decay and polynomial regression models together offer a robust framework for forecasting sales retention and guiding strategic decisions in the pharmaceutical industry.

Impact of meteorological drivers on air quality index: A case study from Delhi.

We conducted three experiments to investigate the effects of partial replacement of grass silage with maize silage (25% or 50% of the dry matter [DM]) on feed intake, milk production, diet digestibility, and methane (CH4) emissions in dairy cows. The starch concentrations of maize silages were high for northern latitudes and ranged from 236 g kg-1 DM at early harvest to 278 and 254 g kg-1 DM at late harvest, respectively. Partial replacement of grass silage with maize silage increased feed intake, whereas diet digestibility decreased. Milk and energy corrected milk (ECM) yields increased in one experiment, whereas no corresponding changes were observed in the other experiments. Replacing grass silage with maize silage improved nitrogen utilization in all the experiments and CH4 intensity (g kg-1 ECM) decreased in one experiment. In northern conditions, the beneficial effects of maize silage on feed intake can be achieved, while effects on milk production and enteric CH4 emissions are less consistent due to annual variation in maturity and starch content of maize.