Search Results (207)

For oil and gas reservoir characterization, permeability prediction is indispensable because it helps identify potential flow pathways and lowers risk. Estimating permeability in heterogeneous media is challenging due to the limited number of measurement tools, low-resolution sampling methods, and sampling bias. To combat these issues, we employed a probe permeameter to produce a high-resolution (4 in [10 cm] spacing) permeability dataset for cores from the Strawn Formation, Katz Field, Permian Basin, Texas, USA. We structured our sampling to record permeability changes related to facies variability and fluctuating bioturbation intensity. We compared probe permeameter data to wireline logs and core-plug porosity and permeability data recorded at larger spacings. The results show that permeability is affected by facies type, bioturbation intensity, and cementation. The effects of bioturbation are non-linear; in our study, moderate bioturbation enhances permeability by improving connections between sands while intense bioturbation decreases permeability by redistributing fines. Core-plug and probe measurements gave similar permeability values, but the number of core plugs taken in the finer-grained intervals was insufficient. The probe, however, provided better resolution and gave larger net-to-gross sand ratios than core-plug-based evaluations. Using only the core-plug porosity–permeability relationship with wireline density log porosities led to permeability predictions too large by a factor of three or more compared to averaged probe permeameter values. Full article

The growing demand for consumer-end electrical load is driving the need for smarter management of power sector utilities. In today’s technologically advanced society, efficient energy usage is critical, leaving no room for waste. To prevent both electricity shortage and wastage, electrical load forecasting becomes the most convenient way out. However, the conventional and probabilistic methods are less adaptive to the acute, micro, and unusual changes in the demand trend. With the recent development of artificial intelligence (AI), machine learning (ML) has become the most popular choice due to its higher accuracy based on time-, demand-, and trend-based feature extractions. Thus, we propose an Extreme Gradient Boosting (XGBoost) regression-based model—PredXGBR-1, which employs short-term lag features to predict hourly load demand. The novelty of PredXGBR-1 lies in its focus on short-term lag autocorrelations to enhance adaptability to micro-trends and demand fluctuations. Validation across five datasets, representing electrical load in the eastern and western USA over a 20-year period, shows that PredXGBR-1 outperforms a long-term feature-based XGBoost model, PredXGBR-2, and state-of-the-art recurrent neural network (RNN) and long short-term memory (LSTM) models. Specifically, PredXGBR-1 achieves an mean absolute percentage error (MAPE) between 0.98 and 1.2% and an $R^2$ value of 0.99, significantly surpassing PredXGBR-2’s $R^2$ of 0.61 and delivering up to 86.8% improvement in MAPE compared to LSTM models. These results confirm the superior performance of PredXGBR-1 in accurately forecasting short-term load demand. Full article

Gestational diabetes mellitus (GDM) represents a significant medical complication during pregnancy, with a global prevalence ranging from 2% to 26% and increasing by over 30% in recent decades. Therefore, the aim of our study is to assess the trends and distribution of published studies, as well as the contributions of countries, institutions, journals, and authors to the development of primary care for pregnant women with gestational diabetes. In this bibliometric analysis, we examine the role of primary health care in GDM from 1991 to 2024. The data were sourced from Scopus and Web of Science, encompassing 276 articles from 150 sources and involving 1375 authors. The analysis reveals a steady increase in publications, with a 4.29% annual growth rate. This study identifies the USA and UK as leading countries in GDM research, and there are significant international collaborations, with the USA having 17 joint articles with other countries. The University of Eastern Finland, Ohio State University, and Harvard University are noted as the most prolific institutions, with 23, 17, and 16 articles, respectively. Additionally, the journal Diabetes Care published the highest number of articles, totaling 635. Prominent authors such as Bernstein J. and McCloskey L., with seven articles each, have made substantial contributions to the field. Our work highlights the need to pay special attention to primary care for gestational diabetes, as many negative consequences of the disease can be prevented at this stage. Innovative approaches to screening for GDM can significantly improve treatment outcomes and reduce health risks, which will have long-term positive effects both for individual patients and society as a whole. Full article

Background: The giant keyhole limpet Megathura crenulata is a gastropod mollusk (Fissurella superfamily) that is endemic to the eastern Pacific coast from southern California, USA, to Baja California Sur, Mexico. M. crenulata is socioeconomically important as it produces a potent immune-stimulating protein, called Keyhole Limpet Hemocyanin, which is extracted in vivo and utilized for vaccine development. However, ecological studies are scarce and genetic knowledge of the species needs to be improved. Our objectives were to assemble and annotate the mitogenome of M. crenulata, and to assess its phylogenetic relationships with other marine gastropods and to evaluate its population genetic diversity and structure. Methods: Samples were collected for mitogenome assembly (n = 3) spanning its geographic range, Puerto Canoas (PCA) and Punta Eugenia (PEU), Mexico, and California (CAL), USA. Total DNA was extracted from gills sequenced using Illumina paired-end 150-bp-read sequencing. Reads were cleaned, trimmed, assembled de novo, and annotated. In addition, 125 samples from eight locations were analyzed for genetic diversity and structure analysis at the 16s rRNA and COX1 genes. Results: The M. crenulata mitogenomes had lengths of 16,788 bp (PCA) and 16,787 bp (PEU) and were composed of 13 protein-coding regions, 22 tRNAs, two rRNAs, and the D-Loop region. In terms of phylogeographic diversity and structure, we found a panmictic population that has experienced recent demographic expansion with low nucleotide diversity (0.002), high haplotypic diversity (0.915), and low φ_ST (0.047). Conclusions: Genetic insights into the giant keyhole limpet provides tools for its management and conservation by delimiting fishing regions with low genetic diversity and/or genetically discrete units. Full article

Surface coal mining and reclamation have greatly reshaped eastern Kentucky’s landscape affecting its socioeconomic, environmental and climatic aspects. This study examined the land-cover changes, trends and patterns in Floyd, Knott, Letcher, Magoffin, Martin, Perry, and Pike counties from 2004 to 2019. Using a random forest classifier, land cover was categorized into seven major classes, i.e., water, barren land, developed land, forest, shrubland, herbaceous, and planted/cultivated, majorly based on Landsat images. The Kappa accuracy ranged from 75 to 89%. The results showed a notable increase in forest area from 5052 sq km to 5305 sq km accompanied by a substantial decrease in barren land from 179 sq km to 91 sq km from 2004 to 2019. These findings demonstrated that reclamation activities positively impacted the forest expansion and reduced the barren land of the study area. Key land-cover transitions included barren land to shrubland/herbaceous, forest to shrubland, and shrubland to forest, indicating vegetation growth from 2004 to 2019. An autocorrelation analysis indicated similar land-cover types clustered together, showing effective forest restoration efforts. As surface coal mining and reclamation significantly influenced the landscapes of the coalfield counties in eastern Kentucky, this study provides a holistic perspective for understanding the repercussions of these transformations, including their effects on humans, society, and environmental health. Full article

Canopy foliar traits serve as crucial indicators of plant health and productivity, forming a vital link between plant conditions and ecosystem dynamics. In this study, the use of hyperspectral data and foliar traits for white pine needle damage (WPND) detection was investigated for the first time. Eastern White Pine (Pinus strobus L., EWP), a species of ecological and economic significance in the Northeastern USA, faces a growing threat from WPND. We used field-measured leaf traits and hyperspectral remote sensing data using parametric and non-parametric methods for WPND detection in the green stage. Results indicated that the random forest (RF) model based solely on remotely sensed spectral vegetation indices (SVIs) demonstrated the highest accuracy of nearly 87% and Kappa coefficient (K) of 0.68 for disease classification into asymptomatic and symptomatic classes. The combination of field-measured traits and remote sensing data indicated an overall accuracy of 77% with a Kappa coefficient (K) of 0.46. These findings contribute valuable insights and highlight the potential of both field-derived foliar and remote sensing data for WPND detection in EWP. With an exponential rise in forest pests and pathogens in recent years, remote sensing techniques can prove beneficial for the timely and accurate detection of disease and improved forest management practices. Full article

There are more than 260 million people of Slavic descent worldwide, who reside mainly in Eastern Europe but also represent a noticeable share of the population in the USA and Canada. Slavic populations, particularly Eastern Slavs and some Western Slavs, demonstrate a surprisingly high degree of genetic homogeneity, and, consequently, remarkable contribution of recurrent alleles associated with hereditary diseases. Along with pan-European pathogenic variants with clearly elevated occurrence in Slavic people (e.g., ATP7B c.3207C>A and PAH c.1222C>T), there are at least 52 pan-Slavic germ-line mutations (e.g., NBN c.657_661del and BRCA1 c.5266dupC) as well as several disease-predisposing alleles characteristic of the particular Slavic communities (e.g., Polish SDHD c.33C>A and Russian ARSB c.1562G>A variants). From a clinical standpoint, Slavs have some features of a huge founder population, thus providing a unique opportunity for efficient genetic studies. Full article

The morphology, internal architecture, and emplacement mechanisms of the Central Atlantic Magmatic Province (CAMP) lava flows of the Hartford and Deerfield basins (USA) are presented. The Talcott, Holyoke, and Hampden formations within the Hartford basin constitute distinct basaltic units, each exhibiting chemical, mineralogical, and structural differences corresponding to flow fields. Each flow field was the result of several sustained eruptions that produced both inflated pahoehoe flows and subaquatic extrusions: 1–5 eruptions in the Talcott formation and 1–2 in Holyoke and Hampden basalts, where simple flows are dominant. The Deerfield basin displays the Deerfield basalt unit, characterized by pillow lavas and sheet lobes, aligning chemically and mineralogically with the Holyoke basalt unit. Overall, the studied flow fields are composed of thick, simple pahoehoe flows that display the entire range of pahoehoe morphology, including inflated lobes. The three-partite structure of sheet lobes, vertical distribution of vesicles, and segregation structures are typical. The characteristics of the volcanic pile suggest slow emplacement during sustained eruptive episodes and are compatible with a continental basaltic succession facies model. The studied CAMP basalts of the eastern United States are correlated with the well-exposed examples on both sides of the Atlantic Ocean (Canada, Portugal, and Morocco). Full article

Until now, no study has examined the future range dynamics of major invasive wasp species to assess their future impacts on global apiculture. Here, we developed 12 species distribution models to calibrate the future range dynamics of 12 major invasive Vespidae wasp species under a unified framework. An increase in their habitat suitability was identified in more than 75% of global land. Substantial range expansions were detected for all 12 species, and they were primarily induced by future climate changes. Notably, Polistes dominula and Vespa crabro had the largest potential ranges under all scenarios, suggesting their greater impact on global apiculture. Polistes chinensis and Vespa velutina nigrithorax had the highest range expansion ratios, so they warrant more urgent attention than the other species. Polistes versicolor and P. chinensis are expected to exhibit the largest centroid shifts, suggesting that substantial shifts in prioritizing regions against their invasions should be made. Europe and the eastern part of the USA were future invasion hotspots for all major invasive wasp species, suggesting that apiculture might face more pronounced threats in these regions than in others. In conclusion, given their substantial range shifts, invasive wasps will likely have increasingly negative impacts on global apiculture in the future. Full article

Objectives: Ramadan, a significant month for Muslims, presents unique challenges, particularly in the context of the USA. This study aimed to explore the relationship between mental health factors (depression, anxiety, and stress), sleep quality, and psychological well-being (subjective happiness and life satisfaction) during the month of Ramadan among participants and by gender. Methods: This study enlisted 163 participants (74% female, 25.7% male), with an average age of 36.8 years (SD = 13.1), mostly of Middle Eastern descent. Recruitment was conducted via flyers at local community mosques, social media, and outreach through local religious leaders. Data collection took place in the last three weeks of Ramadan, utilizing a Qualtrics survey that included the Depression Anxiety and Stress Scale (DASS-21), the Subjective Happiness Scale (SHS), Satisfaction with Life Scale (SWLS), and the Pittsburgh Sleep Quality Index (PSQI). Data were analyzed by means of descriptive statistics and multiple linear regression models using SPSS version 28. Results: The study indicates that while mental health and psychological well-being remained within normal levels during Ramadan, sleep scores indicated significant sleep disturbance among participants. Multiple linear regression models revealed that subjective happiness, sleep duration, and the global PSQI score were significant predictors of stress for the total sample (F = 9.816, p = 0.001). Life satisfaction was the only significant predictor of anxiety (F = 7.258, p = 0.001), and it, alongside subjective happiness, significantly predicted depression (F = 12.317, p = 0.001). For men, subjective happiness alone predicted stress, while life satisfaction was a predictor for both anxiety and depression (F = 4.637, p = 0.001). In women, sleep duration and medication usage were linked to stress but not anxiety. Life satisfaction and subjective happiness were, however, predictors of depression (F = 6.380, p = 0.001). Conclusion: Fostering positive affective states can serve as a protective mechanism against the potential psychological distress associated with altered sleep patterns and lifestyle changes that accompany Ramadan. This study highlights that Ramadan is a tool for bolstering happiness and life satisfaction, thereby lowering levels of stress, anxiety, and depression. In non-Muslim majority contexts like the USA, there is a need for accommodations to safeguard against potential psychological distress. Full article

Several configurations of the Canadian Precipitation Analysis system (CaPA) currently produce precipitation analyses at Environment and Climate Change Canada (ECCC). To improve CaPA’s performance during the winter season, the impact of assimilating the IMERG V06 product (IMERG: Integrated Multi-satellitE Retrievals for GPM—Global Precipitation Measurement mission) into CaPA is examined in this study. Tests are conducted with CaPA’s 10 km deterministic version, evaluated over Canada and the northern part of the United States (USA). Maps from a case study show that IMERG plays a contradictory role in the production of CaPA’s precipitation analyses for a synoptic-scale winter storm over North America’s eastern coast. While its contribution appears to be physically correct over southern portions of the meteorological system, and early in its intensification phase, IMERG displays unrealistic spatial structures over land later in the system’s life cycle when it is located over northern (colder) areas. Objective evaluation of CaPA’s analyses when IMERG is assimilated without any restrictions shows an overall decrease in precipitation, which has a mixed effect (positive and negative) on the bias indicators. But IMERG’s influence on the Equitable Threat Score (ETS), a measure of CaPA’s analyses accuracy, is clearly negative. Using IMERG’s quality index (QI) to filter out areas where it is less accurate improves CaPA’s objective evaluation, leading to better ETS versus the control experiment in which no IMERG data are assimilated. Several diagnostics provide insight into the nature of IMERG’s contribution to CaPA. For the most successful configuration, with a QI threshold of 0.3, IMERG’s impact is mostly found in the warmer parts of the domain, i.e., in northern US states and in British Columbia. Spatial means of the temporal sums of absolute differences between CaPA’s analyses with and without IMERG indicate that this product also contributes meaningfully over land areas covered by snow, and areas where air temperature is below −2 °C (where precipitation is assumed to be in solid phase). Full article

Two species of Psilochalcis wasps (P. minuta and P. quadratis) were recently described from Utah’s eastern Great Basin. The extent of their known distributions is extremely limited, based on few data points. We developed species distribution models (SDMs) using Maxent modeling software for each Psilochalcis species to identify areas of probable suitable habitat for targeted collecting to improve our knowledge of their distributions. We used six occurrence data points for P. minuta and eight occurrence data points for P. quadratis, along with ten environmental variables as inputs into the Maxent modeling software. Model-predicted areas with a potential suitable habitat value greater than 0.69 were mapped using ArcGIS Pro to help select locations for model accuracy assessment. Employing Malaise traps, eighteen sites were sampled to evaluate each SDM’s ability to predict the occurrence of Psilochalcis species. Psilochalcis minuta occurred at eight of nine juniper-dominated sample sites that were predicted as having high suitability by the model for this species. Likewise, P. quadratis occurred at two of four cheatgrass-dominated sample sites predicted by the model. Psilochalcis minuta occurred at three of nine sampled sites that were not predicted by the model, and P. quadratis occurred at seven of fourteen non-predicted sites. The Maxent SDM results yielded an AUC value of 0.70 and p-value of 0.02 for P. minuta and 0.68 and 0.02. for P. quadratis. These results were reflected in our model accuracy assessment. Of the selected environmental variables, aspect, historic fire disturbance, and elevation yielded the greatest percent contributions to both species’ models. Sympatric distributions were observed for P. minuta and P. quadratis. Elevation, vegetation type, NDVI, and soil type are the most important environmental variables in differentiating areas of optimal suitable habitat for the two species. Full article

This study examined the second-order schema domains of Early Maladaptive and Adaptive Schemas based on recent trends and compared them with the five theoretical second-order schema domains commonly used in schema therapy. Using six international Eastern and Western community samples—Singapore (n = 628), Malaysia (n = 229), USA (n = 396), South Africa (n = 390), Nigeria (n = 364), India (n = 306)—confirmatory factor analysis showed that the four second-order domains of EMSs and EASs, which ran almost parallel with each other, were the most robust models calling into question the validity of the five domain model. Given the hypothesized links between schemas and needs, these four categories of EMSs and EASs represent four categories of toxic experiences and core emotional needs, respectively. These categories were supported empirically and are useful to parents as well as to clinicians as they approach child rearing and the treatment of clients in schema therapy from the vantage point of needs. These four categories of psychological core emotional needs, as well as toxic experiences, were found, as expected, to be linked with various measures of well-being and ill-being. Full article

As some of the most threatened ecosystems in the world, the declining condition and coverage of coastal habitats results in the loss of the myriad ecosystem services they provide. Due to the variability in physical and biological characteristics across sites, it is imperative to increase location-based information to inform local management projects, which will potentially help to reestablish functions of coastal habitats. Since oysters are often used in restoration projects, this study quantified spatial and temporal patterns in eastern oyster spat settlement in a bar-built estuary in northeast Florida, USA that is host to a robust population of intertidal oyster reefs. Spat settlement was found to occur from April to October with small peaks in the spring and large ones around September. Inter-annual differences in spat settlement were likely influenced by existing environmental conditions and heavily affected by large-scale events such as tropical cyclones. Variations in regional spat settlements are possibly driven by the residence times of the watersheds, the density of adult populations, and the location of the spat collectors. The results of this study illustrate place-based variability in oyster settlement patterns and underscore the importance of local monitoring for oyster resource management, restoration, and research. Full article

Several species of lady beetle native to North America have declined in abundance in the last few decades, often accompanied by contractions in their geographic ranges. Coleomegilla maculata lengi is a lady beetle native to North America that is an important predator of pests in various agroecosystems. Its reported range spans the eastern half of the USA, with no sustained decline in abundance or contraction of its range reported. Indeed, we recently collected several individuals of this lady beetle in central USA roughly 500 km beyond the western edge of its reputed range. We hypothesized that new records could indicate either that previous range characterization failed to include pre-existing collection records further west or that C. maculata lengi has recently expanded its geographic range. To test these hypotheses, we searched several institutional insect collections and digital databases for records and found many earlier records of C. maculata lengi beyond its reputed geographic range, clearly showing that the previous characterization of its geographic distribution in North America was substantially underestimated. In addition, we report a new state record of C. maculata lengi from Wyoming, USA, that further indicates its geographic range expansion in North America. We discuss new records of C. maculata lengi in light of declines in native coccinelline lady beetle species in North America. Full article