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Biodegradation of insecticide residue by lactic acid bacteria
Interfacial-active green surfactants from sugarcane bagasse and its biochar for enhanced oil recovery
A fast, accurate and oscillation-free spectral collocation solver for high-dimensional transport problems
Abstract Transport phenomena—describing the movement of particles, energy, or other physical quantities—are fundamental in various scientific disciplines, including nuclear physics, plasma physics, astrophysics, engineering, and the natural sciences. However, solving the associated seven-dimensional transport equations poses a significant computational challenge due to the curse of dimensionality. We introduce the Tensor Train Superconsistent Spectral ( $${\hbox {T}}^2{\hbox {S}}^2$$ ) solver to address this challenge, integrating Spectral Collocation for exponential convergence, Superconsistency for stabilization in transport-dominated regimes, and Tensor Train format for substantial data compression. $${\hbox {T}}^2{\hbox {S}}^2$$ enforces a dimension-wise superconsistent condition compatible with tensor structures, achieving extremely low compression ratios, such as $$\mathscr {O}(10^{-12})$$ , while preserving spectral accuracy. Numerical experiments on linear problems demonstrate that $${\hbox {T}}^2{\hbox {S}}^2$$ can solve high-dimensional transport problems in minutes on standard hardware, making previously intractable problems computationally feasible. This advancement opens new avenues for efficiently and accurately modeling complex transport phenomena.
Individual variation in play in young chickens – assessment and connection to affective state and personality
Abstract The extent of individual variation in play frequency, and its association with affective state and personality is unexplored. We evaluated two different methods to study individual variation: video stimulation and individual consistency across different group constellations. In both cases, the birds were moved from the home pen to identical play arenas, and the play sessions were video recorded. Furthermore, a cognitive judgement bias test was performed, and in one group, personality tests were also performed. Large variation in individual play frequency was observed with both methods. Video stimulation did elicit some play behaviour, but the play frequency was lower than expected, and no social play was observed. Individual play frequency was relatively consistent across test days when chicks were allowed to play in different groups, suggesting a possible genetic influence on play motivation. No connection between individual play frequency and affective state was found, suggesting that play is weakly associated with fundamental state of affect in chicks. Furthermore, the results revealed a negative correlation between food exploration and total play in females, and between food exploration and affective state in males. This suggests that food motivation was greater in females who played less and in males exhibiting greater optimism.
Effect of horse sleep behavior on performance in a field-side spatial reversal learning test
Abstract Reduced rapid-eye-movement (REM) sleep is associated with impaired learning in many species. We developed a reversal learning test (RLT) suitable for field conditions to explore this association in 16 healthy horses. Nocturnal REM-like sleep behavior was recorded five times for 48 h over a six-week period. The horses performed a target training task followed by an RLT using two objects. When the horses reached a predefined frequency of touching the object, the spatial location was reversed. Mean test parameters were statistically analysed using GENLIN models, longitudinal continuous variables were analysed using linear repeated measures models, and dichotomous repeated measures were analysed using GEE models and Kaplan-Meier method. Altogether 15/16 horses completed RLT by reversing three or more times. Most errors occurred before the second and third reversals. Overall, REM sleep duration (mean ± SE) was 46.1 ± 8.7 min. However, there were ten horses that exhibited REM-like sleep for less than 30 min (10.6 ± 2.2 min, range 0.0–28.0 min), while six horses exhibited REM-like sleep for at least 30 min (42.3 ± 4.8 min, range 36.6–65.8 min). Longer REM sleep was associated with a greater number of reversals ( p = 0.04), while no relationship was found with error rate. Survival analysis further indicated a significant difference in progression probability between groups, with horses with shorter REM sleep having a 50% chance of progressing after five reversals, compared to six reversals for longer REM sleepers ( p < 0.05). We present here a method to test horses’ reversal learning ability on site over a single day. We found that short REM-like sleep duration without clinical signs of sleep disturbances in horses was associated with poorer performance and lower perseverance during the RLT.
Dissolution and physical characterization of oral nicotine pouch products
Abstract In this study, we conducted a comprehensive analysis of seven commercially available nicotine pouch products, including on! , Zyn , Velo , Dryft , Rogue , Volt , and Loop nicotine pouches. Analyses include nicotine content, nicotine dissolution release, particle size, imaging (bulk filler and outer pouch material), bulk density (tapped and untapped), true density, crystallinity, solubility, oven volatiles (OV as measured by percent moisture content, % MC), pH of aqueous extracts, water activity, and extract viscosity. The nicotine dissolution profiles showed a faster release for on! , Zyn , and Rogue when compared to Velo , Dryft , Volt , and Loop nicotine pouches. When all nicotine pouches release profiles were compared to on! , only Zyn and Rogue were found equivalent. Particle size analysis revealed Gaussian-like distributions for on! , Rogue , and Zyn nicotine pouches. The remaining products displayed bimodal particle size distributions. Tapped and untapped bulk densities were measured to assess the flowability of the filler in all seven nicotine pouches. Rogue and Loop nicotine pouches exhibited the highest and lowest flowabilities, respectively. Solubility data indicated that Zyn nicotine pouches had the highest percentage of soluble components, whereas Rogue nicotine pouches had the lowest. Rheology results from the nicotine pouch extracts in artificial saliva showed the highest viscosity for Loop and lowest viscosity for Volt and Rogue nicotine pouches. All products were found to have crystalline structures with both high and low temperature melting points. Our results indicate that nicotine pouch products exhibit differences and similarities in their physicochemical properties, providing valuable insights into understanding their formulation and development.
Utilizing AI CAD for early pandemic screening in chest radiographs
Enhanced tetracycline degradation via photo-activated potassium persulfate catalyzed by cobalt ferrite/carbon nanocomposite
Effects of diacylglycerol-enriched alpha-linolenic acid oil on skin properties in mild skin discomfort: a randomized, double-blind, placebo-controlled study
Abstract Skin barrier function impairment and inflammation promote allergen invasion through the skin, leading to sensitization and exacerbation of allergic diseases. Intake of linseed oil, an oil rich in alpha-linolenic acid (ALA), suppresses inflammation and allergic symptoms. To our knowledge, the effects of diacylglycerol-enriched ALA (ALA-DAG) oil intake on skin properties and allergic symptoms have not been evaluated. We performed a double-blind, randomized, placebo-controlled, parallel-group study of 60 individuals aged 20–59 years with mild skin discomfort, including dryness, itching, and redness, to investigate the effects of ALA-DAG intake on skin and allergic symptoms. Participants were divided into two groups treated with either 2.5 g/day of ALA-DAG or placebo oil for 8 weeks. The skin properties were measured at baseline and at 8 weeks. Allergic symptoms were measured at 4 and 8 weeks. Compared with placebo oil intake, ALA-DAG intake increased skin hydration in the cheek, reduced nasal congestion and nose itchiness, and decreased mite-specific immunoglobulin E in the blood. Subgroup analysis showed that participants who were positive for mite allergen sensitization had reduced facial redness after ingesting ALA-DAG. These findings suggest that ALA-DAG intake improves skin properties and alleviates allergic symptoms.
Multi-objective economic energy management strategy in thermal and electrical grids with energy hubs including renewable units and storage systems
A comprehensive characteristic of Anastatica hierochuntica
Development of a FHIR-based Korean IPS Data Pipeline and User-Centered UI Design
Abstract The International Patient Summary (IPS) is a minimal data standard enabling rapid access to essential health information across institutions and borders. Korea provides Fast Healthcare Interoperability Resources (FHIR) data through the “My Health Record” application, which utilizes an implementation guide (IG) inheriting from the KR Core FHIR profiles. However, a standardized workflow for transforming these domestic FHIR resources into IPS-compliant data has not yet been established. This study aimed to assess the feasibility of implementing an IPS-compliant patient summary in Korea using existing FHIR-based resources and national profiles. First, a literature review confirmed IPS as a global standard supporting interoperability and patient-centered care. Second, a gap analysis revealed that six of the seven IPS-required and recommended components successfully mapped to ten KR Core profiles. However, the Device component and the MedicationStatement profile remained unmapped due to the lack of corresponding definitions in the KR Core. Third, real-world FHIR data from three individuals were transformed using ChatGPT-4o into IPS-compatible formats and validated via HAPI FHIR and SMART FRED tools. Fourth, user requirements were identified through personas and expert consultations, highlighting the need for summary and timeline-based UI elements. Fifth, a user interface was developed using Figma based on these requirements. Overall, approximately 86% of required IPS data elements were represented using existing Korean FHIR-based resources. These findings demonstrate the technical feasibility of IPS implementation in Korea, while also highlighting current gaps in terminology coverage and profile alignment. Future work should focus on multi-site validation, increased automation of mapping processes, and governance frameworks to support scalable and reproducible IPS deployment.
Acid mine drainage control in mining areas: identification of groundwater recharge pathways and source reduction strategies
Estimated predator composition using environmental DNA analyses and color patterns of male guppies in introduced rivers
Characterization and comparative analysis of urinary bacterial microbiome profiling in healthy cats and cats with feline idiopathic cystitis
Forecasting photovoltaic power in high-latitude regions via support vector machine optimized by meta-heuristics
Abstract Machine-learning techniques are widely used across many disciplines, including electricity generation forecasting. In this study, the Support Vector Machine (SVM) based models, one of the machine learning techniques, were developed for daily PV power forecasting. To improve model performance, models were tuned with four metaheuristic optimizers, including the Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Daily PV power and temperature data from 2020 to 2023 were obtained for the Stavanger, Oslo, and Kristiansand regions which located in southern Norway. One of the innovative aspects of this study is the investigation of the performance of SVM (Support Vector Machine) combined with various optimization methods across four alternative input configurations. To examine the different feature combinations, four different input configurations were created through the Minimum-Redundancy Maximum-Relevancy (MRMR) method. The analysis results obtained with SVM were further enhanced using all optimization techniques. Among those, the SVM-PSO-M04 ( r = 0.7707, NSE = 0.5748, KGE = 0.7092, PI = 0.2964 and RMSE = 0.6513) method produced the most effective results (improving the correlation coefficient (r) to 0.7707 (approximately a 19% increase over the untuned SVM)) among the tested hybrid configurations obtained in our experiments. Moreover, coupling temperature data alongside PV power as model input also tends to improve forecasting skill. Results of this study provide a case-study benchmark for researchers, institutions, and other stakeholders engaged in renewable energy planning and management in high-latitude regions.