Environmental Variables Research Articles

Spatial analysis with unoccupied aircraft systems data in wheat breeding yield trials

AbstractAn important aspect of reliable cultivar development is good field trial evaluations. Unoccupied aircraft systems (UAS also known as drones or UAVs) are a popular high‐throughput phenotyping tool that has been used to successfully evaluate plant stress and other canopy characteristics in a field. In precision agriculture applications, UAS imagery has been used to identify spatial variability in field settings. Here, we use UAS spectral imagery to improve field trial spatial analysis, better control spatial variability, and reduce errors for more reliable selections. UAS imagery data were collected across 47 breeding trials planted in an augmented complete block design (ACBD) or alpha‐lattice replicated designs from 2020 through 2023. Trials were evaluated using three spatial analysis strategies: linear models incorporating block effect, row‐column effect, or 2D splines. UAS‐derived spectral reflectance indices (SRI) were combined with each model as covariates. Modeling strategies were used across all trials and evaluated for autocorrelation, model fitness, and coefficient of variation (CV). Akaike information criterion (AIC) was used to assess model fitness. For spatial analysis trials, SRIs significantly lowered model AIC by an average of 38.4 for alpha‐lattice trials and 69.1 for ACBD trials. CV scores were also lowered when SRIs were utilized, with average CV values being 2.6 lower for alpha‐lattice and 2.1 for ACBD trials. This study highlights the potential for SRIs to improve the analyses of field breeding trials despite extreme environmental variables and climate conditions, improving experiment reliability and changing the way breeders plan and implement breeding experiments.

Intercontinental Insights into Autism Spectrum Disorder: A Synthesis of Environmental Influences and DNA Methylation

Abstract Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by a broad range of symptoms. The etiology of ASD is thought to involve complex gene-environment interactions, which are crucial to understanding its various causes and symptoms. DNA methylation is an epigenetic mechanism that potentially links genetic predispositions to environmental factors in the development of ASD. This review provides a global perspective on ASD, focusing on how DNA methylation studies may reveal gene-environment interactions characteristic of specific geographical regions. It delves into the role of DNA methylation in influencing the causes and prevalence of ASD in regions where environmental influences vary significantly. We also address potential explanations for the high ASD prevalence in North America, considering lifestyle factors, environmental toxins, and diagnostic considerations. Asian and European studies offer insights into endocrine-disrupting compounds (EDC), persistent organic pollutants (POP), maternal smoking, and their associations with DNA methylation alterations in ASD. In areas with limited data on DNA methylation and ASD, such as Africa, Oceania, and South America, we discuss prevalent environmental factors based on epidemiological studies. Additionally, the review integrates global and country-specific prevalence data from various studies, providing a comprehensive picture of the variables influencing ASD diagnoses over region and year of assessment. This prevalence data, coupled with regional environmental variables and DNA methylation studies, provides a perspective on the complexities of ASD research. Integrating global prevalence data, we underscore the need for a comprehensive global understanding of ASD’s complex etiology. Expanded research into epigenetic mechanisms of ASD is needed, particularly in underrepresented populations and locations, to enhance biomarker development for diagnosis and intervention strategies for ASD that reflect the varied environmental and genetic landscapes worldwide.

Integrated approach to predicting habitat suitability and evaluating quality variations of Notopterygium franchetii under climate change.

The impact of climate change on medicinal plants has significantly altered their suitable environments, thereby affecting the quality of herbal medicines. Notopterygium franchetii (N. franchetii), a medicinal plant intricately linked to its natural habitat, exhibits substantial quality variations influenced by the ecological conditions of its native region. In this study, comprehensive field surveys were conducted to gather occurrence records and samples of N. franchetii. The Maxent model and ArcGIS software were employed to predict the suitable habitats of N. franchetii during different time periods. A high-performance liquid chromatography (HPLC) method was developed to establish the chemical fingerprints of 21 sample batches. Fourteen common peaks were subjected to cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis. The findings revealed quality variations correlated with their geographic origins, identifying peaks 10, 1, 14, 3, and 4 as crucial for quality differentiation. The study indicates that precipitation, temperature, and altitude significantly influence the distribution of N. franchetii. Under current climate conditions, the suitable habitat area for N. franchetii is estimated to be approximately 94,637.33 km2. However, projections under three future climate scenarios suggest a declining trend in suitable habitat areas. A quality zoning map of N. franchetii was developed, integrating a correlation model between chemical composition and environmental variables with the spatial analysis and visualization capabilities of ArcGIS. The high-quality regions for N. franchetii are predominantly located in the Gannan, Linxia, Dingxi, Longnan, and Wuwei districts. These research outcomes offer a valuable reference for identifying suitable cultivation areas and assessing the quality of N. franchetii in Gansu Province.

How Much Hatchery-Reared Brown Trout Move in a Large, Deep Subalpine Lake? An Acoustic Telemetry Study

Fish movement into large, deep lakes has been rarely investigated due to the complexity and extent of such ecosystems. Among the different monitoring methods available, acoustic telemetry enables the study of the spatial ecology and behavior of aquatic organisms in lentic environments. In this study, the movement of 69 hatchery-reared adult brown trout (size 43–61 cm) marked with acoustic transmitters was monitored in the large and deep subalpine Lake Lugano (Switzerland and Italy). Trout were tracked for six consecutive months by seven acoustic receivers (March–August 2022), positioned in a non-overlapping array. Trout movement was reconstructed using R packages specific for acoustic telemetry (actel and RSP), which also allowed us to translate tracking information into utilization distribution (UD) areas for each fish. The effects of different environmental variables (rainfall, water discharge of the two main tributaries of Lake Lugano, atmospheric pressure, cloud coverage, and moon phases) on trout movement were tested, but none of these variables seemed to significantly correlate with fish movement. After release, most of the tagged fish exhibited reiterative movements during the initial month, with some maintaining this behavior throughout the entire study period. This spatial behavior can be particularly evident in hatchery-reared fish due to their aggressive and bold attitude. The association of these behavioral traits, shaped by domestication, could expose hatchery-reared fish to high risks and post-release mortality in the wild. Indeed, within a few months after the release, most of the tagged fish were no longer detected by the acoustic receivers. In addition, 26% of the total tagged fish were caught by recreational or professional fishermen.

Index for Assessing the Performance Level of Vehicular Traffic on Urban Streets

Vehicular transportation is one of the most widely used modes in modern cities for reaching key destinations such as workplaces, healthcare facilities, recreational areas, and educational institutions, among others. However, the performance of vehicular traffic on these roads can vary significantly due to the influence of different environmental variables. In the literature, factors such as traffic incidents, weather conditions, road infrastructure, and driving habits, among others, have been identified as impacting vehicular traffic performance. In this context, predictive models have been developed to anticipate congestion at specific points in cities based on statistics, machine learning, simulation, and complex networks. This study proposes a novel index aimed at assessing the level of performance of vehicular traffic on streets based on the relationship among relevant urban environmental variables. This index is generated through Genetic Programming, considering a set of variables related to traffic, incidents, and services. The case study will focus on the streets of the Tlalpan Municipality in Mexico City.

Language teacher emotional intelligence: A scoping review

The current study reviewed and synthesized empirical research on foreign/second language teacher emotional intelligence (EI) using a scoping review approach. Specifically, 15 articles published between 2018 and 2024 were included and analyzed with a particular emphasis on the theoretical perspectives, research themes, research background, and methodologies. The results indicated that there were a variety of models and theories in language teacher EI research, with the trait EI model and theories of self-efficacy and emotion regulation receiving the most attention. Moreover, most reviewed studies regarded language teacher EI as an independent variable or antecedent, examining its impact on other individual and environmental variables. Underdeveloped regions, other target languages apart from English, multilingual teachers, and primary or secondary school teachers haven’t received much attention in the included articles. Additionally, homogenization in research design among these studies was noticeable, with quantitative studies, cross-sectional design, and self-reported questionnaires being prevalent. Finally, implications were provided based on these findings for the further development of language teacher EI.

Value networks, consolidation, and risks of an agricultural territory

Objective: Producer and marketer value networks in an agricultural land in Veracruz, Mexico were identified and characterized, to determine its consolidation level (primary, emergent, potential, or combined), as well as to detect risks and to establish an improvement proposal. Design/Methodology/Approach: An area of the Altas Montañas Veracruz, Mexico was used for the experiment. Surveys were conducted with producers (n=131) and marketers (n=42) of agricultural produce. Socioeconomic, environmental, technical, commercial, and chain link variables were analyzed to detect risks, opportunities, and revaluations. The study was carried out with the RStudio v. 4.3.3 software. Results: Six producer value networks and three marketer value networks were identified. Socioeconomic, environmental, commercial, and technological risks were detected. However, public health risks were different depending on the application of raw manure. Chayote and avocado have displaced other crops. The revaluation proposals for emergent and potential producer and marketer networks were focused on technical support (i.e., commercialization and generational change).

Using iNaturalist presence data to produce suitability maps for Triatoma protracta, T. rubida and T. recurva in the American Southwest, Texas and northern Mexico, to identify potential transmission zones of Chagas disease.

There are 11 species of triatomines in the USA, with seven reported in the American Southwest. These species are capable of transmitting Trypanosoma cruzi, the etiological agent of Chagas disease, but are generally sylvatic and rarely infect humans in the USA. iNaturalist is one of the most popular citizen science data portals, where users record encounters with any individual organism. As of November 2023, iNaturalist reported 722 confirmed triatomine observations in the American Southwest. Maximum entropy ecological niche modelling and bioclimatic environmental variables were used to predict zones of highest human-triatomine interaction. Models fit well for Triatoma protracta (0.85), T. rubida (0.94), and T. recurva (0.96). Precipitation in the warmest quarter was most predictive of T. protracta presence, while precipitation in the driest quarter was most predictive of T. rubida and T. recurva. Locations identified in the American Southwest with highest potential for human-triatomine interaction, and potential T. cruzi transmission, were coastal California, the Sierra Nevada foothills, southern Arizona and border areas of northern Mexico. Study findings can be used for targeted surveillance efforts to address the paucity of contemporary information regarding triatomine species diversity and geographical and ecological associations in the American Southwest.

Exploring phyto- and zooplankton community structure, spatial variation, and driving forces shaping the community from a large-scale freshwater dominated estuary

Abstract Plankton is essential to estuarine food webs, providing key food for species like fish larvae, and understanding their dynamics helps us comprehend ecological interactions and energy transfer in aquatic ecosystems. This study examined the plankton community structure, diversity, variability and the environmental variables of water that influenced these communities in a freshwater-dominated estuary along the Northern Bay of Bengal during the dry season. A variety of tools were employed, including a dissecting microscope, a Sedgwick-Rafter cell, and a Hanna multi-parameter meter, to obtain detailed and comprehensive data. From the analyses, in total 37 genera of phytoplankton belonging to 11 classes such as Bacillariophyceae (66%), Coscinodiscophyceae (28%), Fragilariophyceae (1%), Euglenophyceae (1%), Cyanophyceae (1%), others (3%) were recorded. Zooplankton, consisting of multicellular organisms, was represented by 11 genera across five classes, with Monogononta (53%) and Insecta (29%) being the most prevalent. Phytoplankton exhibited a mean abundance of 180,000 ± 20,200 cells L⁻¹ whereas zooplankton showed a mean abundance of 3,000 ± 200 cells L⁻¹. The diversity indices (H’), evenness (J’) and dominance (D) ranged from 1.188 ± 0.015 to 0.19 ± 0.006, 0.9377 ± 0.002 to 0.5118 ± 0.006, 0.365 ± 0.001 to 0.143 ± 0.002 respectively, suggested low to moderate plankton diversity with a suppressed community and moderate to high dominance in the river water. Based on the similarity percentage (SIMPER) and analysis of similarity (ANOSIM), Phytoplankton and zooplankton varied significantly between stations while non-metric multi-dimensional scaling (nMDS) indicated greater consistency in phytoplankton communities across stations compared to zooplankton. Furthermore, Pearson's correlation coefficient (rs) and canonical correspondence analysis (CCA) identified transparency, sulfates, dissolved oxygen, conductivity, TDS, pH, and salinity as major influencers of plankton abundance; nitrate had a moderate effect. Spearman's rank correlations showed significant positive (p < 0.05) correlations between diversity indices and environmental variables.

Changes in waterbird occurrence and abundance at their northern range boundaries in response to climate warming: importance of site area and protection status

AbstractClimate warming is driving changes in species distribution, but habitat characteristics can interact with warming temperatures to affect populations in unexpected ways. We investigated wintering waterbird responses to climate warming depending on habitat characteristics, with a focus on the northern boundary of their non‐breeding distributions where winter climatic conditions are more extreme. At these Nordic latitudes, climate warming is expected to drive positive changes in species occurrence and abundance, with likely differences in species‐specific responses. We analyzed the occurrence and abundance of 18 species of waterbirds monitored over 2,982 surveys at 245 inland wetlands over a 25‐year period in Sweden. We used hierarchical modeling of species communities (HMSC) which enabled us to relate species‐specific changes to both functional traits and phylogenetic relatedness. We investigated occurrence and abundance changes in response to average temperature, temperature anomalies, site area, site protection status (Natura 2000), and land use in agricultural and urban surfaces. Unsurprisingly, both average temperatures and temperature anomalies were the most important variables influencing positively waterbird occurrence and abundance. For 60% of the species, the effect of temperature anomalies was even stronger in large or protected wetlands. Geese and mallard occurred more often at sites surrounded by agricultural and urban surfaces, respectively, but their occurrence in these habitats was not affected by interactive effects with climate warming. Species abundance was greater inside protected areas only for 11% of the species, but occurrence probability was higher inside protected areas for 44% of the species. Overall, we observed that species thermal affinity was a strong predictor for positive species response to temperature anomalies, and that species sharing similar phylogenetic history had similar relationships with environmental variables. Protection of large wetlands and restoration of the surrounding habitats are two targets for climate change adaptation strategies to facilitate future responses of waterbirds to climate warming.

Dynamic multi-objective optimization based on classification response of decision variables

In recent years, many dynamic multi-objective optimization algorithms (DMOAs) have been proposed to address dynamic multi-objective optimization problems (DMOPs). Most existing DMOAs treat all decision variables uniformly and respond to them in an identical manner. This paper proposes a dynamic multi-objective optimization algorithm based on the classification response of decision variables (CRDV-DMO). Firstly, CRDV-DMO categorizes the decision variables into convergence variables and diversity variables. Different decision variables adopt distinct response strategies. The response strategy of diversity variable (RSDV) uses Latin hypercube sampling to generate the diversity variables of the new environment. For each dimensional convergence variable, the response strategy of convergence variable (RSCV) first evaluates whether the basic center prediction strategy (CPS) yields positive feedback or negative feedback, further determining the predictability of that dimensional convergence variable. RSCV then decides to either use the basic CPS to generate the convergence variable for that dimension or to retain that dimensional convergence variable from the current environment, based on the predictability of that dimensional convergence variable. The proposed algorithm is extensively studied through comparison with several advanced DMOAs, demonstrating its effectiveness in dealing with the benchmark DMOPs and the parameter-tuning problem of the PID controller on a dynamic system.

Phosphatization in the São Pedro and São Paulo Archipelago (SPSPA), Equatorial Atlantic, Brazil: Insights from guano leaching and chemical weathering

This research explores the phosphatization process in the São Pedro and São Paulo Archipelago (SPSPA), located in the Equatorial Atlantic, by analyzing the geochemical interactions between guano coatings and the underlying rocks. The study also examines the geochemical characteristics of the substrates, assessing the behavior of major, minor, trace, and rare earth elements, and determines the degree of weathering degradation of guano crusts, speleothems, peridotites and carbonate sedimentary rocks affected by environmental factors as rain, wind and halmyrolysis. The distribution of chemical elements in water-soluble, adsorbed, acid-extractable/exchangeable, readily acid and reducible, acid oxidizable, and residual phases were investigated. The principal findings of this method show that elevated Na levels are leached in water-soluble fractions, thereby highlighting the occurrence of rapid and active geochemical cycling, which is influenced by seawater. In contrast, in more acidic environments (pH close 4.8 to 2.0), considerable amounts of macroelements like P, Fe, Mg, Al, and Mn are found in association with remaining phases, indicating a slower and more incremental geochemical cycle of mature guano in the input and output systems of these nutrients in the archipelago. The mineralogy, as indicated by the presence of mafic minerals such as olivine, augite, and Cr-spinel, as well as phosphates including fluorapatite, collinsite, and spheniscidite, also supports this finding. The findings underscore the complex interplay between biological activities and geochemical processes, which influence the elemental dynamics in the phosphate-rich rocks of the SPSPA at depth. This study not only enhances our understanding of phosphatization processes but also offers important insights into the sustainable management of marine resources in environmentally sensitive areas. The research underscores the necessity of considering biological and environmental variables when examining geochemical cycles, particularly in regions exhibiting distinctive geological and biological interactions that challenge the prevailing models, such as those identified in the ASPSP.

Variations of phosphorus in sediments and suspended particulate matter of a typical mesotrophic plateau lake and their contribution to eutrophication

Internal phosphorus loading (IPL), as an important part of lake phosphorus cycle and the key to solve the eutrophication problem, is still an important cause of regional and seasonal algal blooms for some mesotrophic lakes located in plateau areas. We investigated the composition, distribution of P fractions in sediments and suspended particulate matter (SPM) of Erhai Lake, southwest China, and explored the relationships between environmental variables and spatial-temporal variations of P fractions. The total P (TP) in surface sediments ranged from 817 to 1216 mg/kg, with inert Ca-P (32%) and Res-P (24%) predominating, at a moderate level. The comparison of short-term release fluxes (0.08 mg/(m2·d)) and long-term release fluxes (0.09 mg/(m2·d)) reflected that the northern region was recovering slowly from the previous P pollution. Mobile-P (the sum of loosely adsorbed P, iron bound P, and organic P) accounted for 52.3% of the TP in SPM and showed high spatial-temporal variations, which were closely related to the growth of algae throughout the investigation. The results suggested that sediments could make a sustained contribution to IPL, and that the P in SPM was highly active and significantly contributed to eutrophication in Erhai Lake especially at the time of seasonal alternations. Our data provided important theoretical bases for the relationship between internal phosphorus loading and eutrophication in plateau lakes.

Scoping review on shamanistic trances practices

BackgroundShamanism is a spiritual tradition in which trance practitioners deliberately modify their state of consciousness to seemingly interact with an invisible world to resolve their community members’ problems. This review aims to provide a multidisciplinary overview of scientific research on shamanic trance.MethodsThe search was performed using PubMed and Google Scholar databases. Twenty-seven articles were found to be eligible, and their data were classified into four dimensions, namely, a) phenomenology, b) psychology, c) neuro-physiological functions, and d) clinical applications.ResultsThese studies suggest that these trances are non-pathological, different from normal states of consciousness in terms of phenomenology and neurophysiology, and influenced by multiple personal and environmental variables. Furthermore, while trances may offer therapeutic potential, their scope should be approached cautiously, underscoring the need for rigorous studies to assess the effectiveness of shamanic approaches for complementary therapies.ConclusionOverall, shamanic trance and its potential benefits remain an intriguing and multifaceted area of scientific study, offering insights into the intersections of consciousness, spirituality, and possibly therapy.

Microbial landscapes in Trinervitermes trinervoides termite colonies are affected by mound compartments and soil properties but not by symbiotic Podaxis fungi

Termites are important ecosystem engineers and play key roles in modulating microbial communities within and outside their mounds. Microbial diversity within termite mounds is generally lower than surrounding soils, due to termite-associated antimicrobial compounds and active sanitary behaviours. Microbial symbionts of termites can also influence the microbial landscape, by inhibiting or out-competing other microbes. Certain members of the arid habitat fungal genus Podaxis (Agaricomycetes; Agaricaceae) are symbiotic with savannah specialist grass-cutting termites, with the potential to influence mound-associated microbiomes. To test this, we characterized fungal (ITS2) and bacterial (16S rRNA) communities within and outside 49 Trinervitermes trinervoides mounds with and without Podaxis fruiting bodies across a 1000 km transect in South Africa. We predicted that Podaxis would be a dominant member of the fungal communities in mounds and negatively impact microbial diversity. Further, we explored how environmental variables shaped microbial communities, including whether soil elemental composition affected Podaxis presence. As expected, we observed less diverse fungal communities, but not bacterial communities, within than outside mounds, while microbial communities differed by sampling regions and mound compartments. Podaxis sequences were present in 48 out of 49 mounds in low relative abundances, and neither fruiting body presence nor sequence abundance were associated with microbial community diversity or composition. There was, however, an overall association between the presence of Podaxis fruiting bodies and elemental composition, with different elements displaying varying associations depending on geographic region. Both environmental variables and soil elements associated with fungal and bacterial taxa, indicating that they are key drivers of microbial community composition. Taken together, our findings suggest that microbial landscapes in termite mounds are not strongly influenced by Podaxis but mainly driven by termite filtering and regional abiotic variables and elemental compositions.

Assessing Non-linear Influences of Urban Layout on Driving Travel Distance: A Mumbai Case Study

Introduction This study investigates the impact of built environment factors on travel behavior in Mumbai, India, focusing on the non-linear effects on driving distances. The rapid urbanization and complex urban of Mumbai constitute present challenges for sustainable transportation, necessitating a deeper understanding of how urban planning influences travel behavior. While demographic factors have often been highlighted in travel studies, this research prioritizes the role of built environment factors. Materials and Methods The study utilized Gradient Boosting Decision Trees (GBDT) to analyze household travel survey data from Mumbai, capturing the non-linear relationships between built environment variables and driving distances. Partial dependence plots were used to visualize these effects, and the relative importance of each variable was assessed to identify key determinants of travel behavior. Results The analysis identified trip time as the most influential factor in determining driving distances, followed by built environment characteristics, such as proximity to commercial areas and intersection density. Socio-demographic factors were found to have a comparatively low impact. Non-linear relationships were observed, such as the stabilization of driving distances beyond certain thresholds of block density and proximity to bus stops. Discussion The findings challenge the traditional emphasis on demographic factors in explaining travel behavior, highlighting the significant role of urban form. The study reveals that specific built environment factors, such as accessibility and connectivity, play a crucial role in shaping driving behavior in a rapidly urbanizing city like Mumbai. These results suggest that urban planning strategies should prioritize these factors to reduce car dependency. Conclusion This study underscores the importance of the built environment in influencing travel behavior in Mumbai, particularly in reducing driving distances. The insights gained offer valuable guidance for urban planners and policymakers aiming to promote sustainable mobility in rapidly developing cities. Further research is recommended to validate and expand upon these findings in other urban contexts.

Appraising the life-course impact of Epstein-Barr virus exposure and its genetic signature on periodontitis.

Periodontitis arises from a multifaceted interplay of environmental variables and genetic susceptibility, where microbial infection plays an indispensable part. Epstein-Barr virus (EBV) exposure has long been considered associated with periodontitis activity; however, the causal relationship and genetic connection between them remain unknown. Within a life-course context, our study employed comprehensive Mendelian randomization (MR) methods, including univariable, multivariable, Bayesian model averaging, and reverse MR, to investigate the causal association between EBV exposure and periodontitis. Additionally, linkage disequilibrium score regression and colocalization analysis were utilized to assess the cross-trait genetic correlations, followed by transcriptome-wide association and enrichment analysis to discern the genetic-phenotypic biological profiles. Heightened levels of EBV antibodies, particularly early antigen diffuses (which serve as indicators of early infection or reactivation), are associated with an increased risk of periodontitis (odds ratio [OR]: 1.27 [1.09-1.47],p=6.05×10-3) and demonstrate a significant genetic correlation (p=4.11×10-3). This pathogenesis may involve the high-confidence causal gene RNASEK located in 17p13.1. Genetically predicted early-life anti-EBV immunoglobulin G (IgG) levels are correlated to a reduced periodontitis risk (OR: 0.89 [0.82-0.97],p=1.76×10-3). The present study highlights the impact of life-course EBV exposure and its genetic hallmark on periodontitis, providing novel perspectives into the underlying pathogenesis and management strategies for EBV-related periodontitis. These findings underscore diverse clinical and public health implications, encompassing antiviral therapies, viral vaccination strategies, and tailored interventions for individualized periodontitis management. Further research is required to validate and expand upon our findings. Periodontitis is a chronic inflammatory disease driven by interactions between microbial pathogens and the host immune system. While bacteria have traditionally been the focus of research, recent studies highlight the significance of virus-bacteria interactions, particularly the role of Epstein-Barr virus (EBV)-a herpesvirus infecting over 90% of the global population-in the development of periodontitis. However, the underlying causal and genetic mechanisms remain unclear. Our study employed genome-wide multi-omics approaches to investigate the link between EBV exposure and periodontitis. We found that recent EBV infection or reactivation increases the risk of periodontitis, whereas early-life exposure, possibly enabling immune resistance, may reduce it. Essential genes were identified as potential mediators, including CRTC3-AS1, HLA-DQA1, and RNASEK. These findings provide novel insights into the EBV-periodontitis connection. For example, viral testing and control could benefit patients unresponsive to standard bacterial treatments, and early viral exposure via vaccination might reduce the risk of periodontitis. Further clinical studies are required to elucidate these underlying mechanisms and the contribution of virus-bacteria interactions.

30 years of terrestrial insect richness patterns across elevation: What have we learned? A global meta-analysis.

Understanding elevation variation in biodiversity is a classic question in ecology and has implications for understanding climate change impacts on mountain ecosystems. While insects are the largest group of animals, the global trend in insect species richness with elevation is unknown. To date, single studies and taxa-specific syntheses have provided no single picture, finding variable patterns of insect richness with elevation. A global synthesis across systems would provide a better understanding of how insect species richness changes with elevation and the possible environmental correlates of those patterns. We used published studies of terrestrial insect elevation gradients from 1990 to 2020 to ask: How do insect species richness change with elevation, and which environmental variables best explain this relationship statistically? With 1486 sites spanning 151 species richness-elevation gradients from 80 studies from four diverse insect taxonomic groups and five biomes, we found that overall proportional richness reached a low-elevation plateau and then decreased. We also show that mean annual temperature and seasonality best explain this trend. We suggest best practices and areas of interest for the future of insect richness-elevation studies, including underrepresented groups, geographic areas, and more standardized methods.

The Effect of Diesel Vehicle Regulation on Air Quality in Seoul: Evidence from Seoul’s Low Emission Zone

This study investigates the effect of the low emission zone (LEZ), designed to restrict old diesel vehicles, on air quality in Seoul, Republic of Korea, using the regression discontinuity in time (RDiT) approach. While previous studies have examined LEZ impacts using traditional econometric models such as time series and panel data approaches, our research uniquely integrates high-frequency daily weather data to better control for confounding environmental variables and captures time-of-day effects on pollutant concentrations. Our findings reveal that the LEZ policy effectively reduced NO2 and SO2 concentrations by 4.7% and 11.6%, respectively. Notably, during daytime hours, when traffic is heaviest, NO2, SO2, and PM10 concentrations decreased by 7.1%, 14.8%, and 13.6%, respectively. These results suggest that the observed improvements can be attributed not only to reduced diesel vehicle registrations but also to significant declines in overall traffic volume.

Analisis Pengaruh Stres Kerja, Beban Kerja, dan Lingkungan Kerja terhadap Motivasi Kerja dan Kinerja Karyawan di UMKM XYZ

UMKM XYZ is a small-scale business that specializes in the production of krupuk. UMKM XYZ faces various challenges, including issues related to the work environment, workload, work stress, and their impact on employee motivation and performance. Thus, this study seeks to gain insights into the factors that impact the motivation and performance of employees at UMKM XYZ. By actively supporting the growth of the MSME sector in the production of krupuk. Researchers are studying the factors that impact the motivation and performance of employees at UMKM XYZ. The Partial Least Squares (PLS) method is a data analysis method that can be highly relevant depending on the characteristics of the data and the purpose of the study. The Partial Least Squares (PLS) method can be quite useful in determining the variables that have the greatest impact on explaining variability in the data. The findings of the analysis research indicated that the work environment had a notable impact on employee motivation in UMKM XYZ. The initial sample value of 0.479 indicates a significant correlation between work environment variables and work motivation. Furthermore, the T-Statistics value is 2.540 with p Values of 0.011, indicating a noteworthy finding. It is worth noting that work stress has a positive and significant influence on employee performance. The initial sample value of 0.389 indicates a significant correlation between work stress variables and employee performance. In addition, the T-Statistics value is 2.943 with p Values of 0.003.