Search Results (73,077)

Background/Objectives: Pre-eruptive intracoronal resorption (PEIR) in impacted or unerupted teeth often remains undiagnosed. The aim of this study was to investigate the prevalence of PEIR with the aid of cone beam computed tomography (CBCT) and propose a new three-dimensional (3D) classification for the analysis of the lesions. Methods: A total of 164 unerupted teeth diagnosed in CBCT scans, derived from an equivalent number of patients, were examined for the presence of PEIR, tooth type, angulation and position. A novel 3D classification system was proposed and all PEIR lesions were further classified. The classification system was used to stage PEIR lesions according to their extend from the enamel level apically, the circumferential spread and their proximity to the pulp chamber. Descriptive statistics were used to assess the prevalence and type of resorption. The association between PEIR, demographics, tooth type, position and angulation were studied. The estimation of the multivariate relationship between PEIR, patient’s demographics and tooth characteristics was conducted with the multiple binary logistic regression model. Results: The prevalence of PEIR was 33.5%, affecting mostly maxillary canines, and maxillary and mandibular molars. The prevalence of PEIR in ages over 45 years was significantly higher (p < 0.001). The presence of PEIR was significantly associated with buccal position (p = 0.002) and buccal angulation (p = 0.016) of the tooth. Conclusions: Due to the high prevalence of PEIR, CBCT may improve detection and 3D characterization when imaging is already clinically indicated, and influence treatment planning in selected cases. Full article

Background/Objectives: Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by B-cell hyperactivation and excessive autoantibody production. Z-DNA binding protein 1 (ZBP1), an innate immune sensor involved in nucleic acid recognition and cell death signaling, has been implicated in antiviral and inflammatory responses. However, its role in B-cell dysregulation during SLE remains unclear. Methods: Integrative transcriptomic analyses were performed using public datasets (GSE61635, GSE235658, GSE136035, and GSE163497) to determine the expression pattern and biological functions of ZBP1 in SLE. Bulk RNA-seq and single-cell RNA-seq data were used to evaluate ZBP1 expression across B-cell subsets. Correlations between ZBP1 expression, disease activity, and immunological parameters were assessed. RNA-seq data following ZBP1 knockdown were analyzed to explore its potential downstream pathways and molecular networks. In addition, in vitro ZBP1 knockdown experiments were conducted to examine its effects on B-cell activation, plasma cell differentiation, and antibody production. Results: ZBP1 was significantly upregulated in peripheral blood and B cells from SLE patients and was enriched in pathways related to type I interferon signaling and cytokine-mediated immune responses. Single-cell transcriptomic profiling further revealed elevated ZBP1 expression across multiple B-cell subsets, including naïve B cells, memory B cells, age-associated B cells (ABCs), and plasma cells. Clinically, ZBP1 expression in peripheral B cells was positively correlated with CD86 mean fluorescence intensity (MFI), SLE Disease Activity Index (SLEDAI) scores, and serum IgG levels, suggesting a link between ZBP1 and B-cell activation. RNA-seq analysis following ZBP1 silencing demonstrated that ZBP1 regulates genes involved in the cell cycle, DNA replication, and p53 signaling, indicating its potential role in promoting B-cell proliferation and activation. Functionally, ZBP1 silencing impaired B-cell activation, reduced plasma cell differentiation, and decreased immunoglobulin production in vitro. Conclusions: Our study identifies ZBP1 as a molecule upregulated in SLE B cells and associated with B-cell activation and disease activity. Although direct causality remains to be established, the data indicate that ZBP1 may contribute to SLE pathogenesis by modulating cell cycle-related pathways and promoting aberrant B-cell responses, highlighting its potential as a biomarker and a candidate therapeutic target in SLE. Full article

The efficient operation of the maintenance service system is key to achieving sustainable operations, with its core lying in the coordinated scheduling of spare parts production and maintenance personnel, as well as the holistic management of in-warranty and out-of-warranty demands. This approach optimizes resource allocation and enhances long-term service value. This paper investigates the integrated scheduling of distributed spare parts production and maintenance personnel with differentiated in-warranty and out-of-warranty demands (ISSPD). To solve the ISSPD, an improved non-dominated sorting genetic algorithm-II that uses Q-learning to adaptively select local search strategies (QLNSGA) is proposed, which incorporates a decoding strategy for differentiated order types, eight knowledge-driven local search strategies, and a Q-learning mechanism for the adaptive selection of key local search operators. Compared to random local search operators, the Q-learning mechanism achieves a 55% decrease in IGD metric and a 65% increase in HV metric. Through comparative experiments with four mainstream algorithms, QLNSGA outperforms RIPG by 58% in terms of the IGD index, and its HV index is generally superior to that of comparative algorithms such as MOEA/D. This indicates that QLNSGA exhibits superior performance in both computational efficiency and solution quality, effectively enhancing service levels and significantly reducing operational costs, thereby providing scientific decision support for service-oriented manufacturing enterprises. Full article

The integration of electric micromobility into urban transportation systems can significantly reduce the energy consumption and emissions associated with short-distance travel. However, quantitative energy-based assessments remain limited, particularly in complex environments such as port–city interfaces. This paper presents a scenario-based energy assessment framework combining survey data and energy modelling. Empirical data were collected through a user survey (n = 138) targeting port workers and nearby residents, providing information on trip distances, travel frequency, modal choice, and willingness to shift from private car use. These data were combined with an energy modelling framework based on mode-specific energy intensity values expressed in kWh per passenger-kilometre. Three scenarios were analysed: a baseline scenario without intervention, a modal shift scenario supported by basic infrastructure measures, and an integrated scenario including transport management measures and local photovoltaic energy coupling. Results indicate that a moderate modal shift of 35% from private cars to electric micromobility for short-distance trips can generate aggregated annual energy savings of approximately 30 MWh and reduce CO₂ emissions by around 7 t per year across the analysed cases. According to the proposed energy model, electric micromobility achieves up to a 95% reduction in energy use per passenger-kilometre compared to private car travel. Furthermore, photovoltaic coupling could supply between 55% and 85% of the annual charging demand. The proposed framework is transparent and transferable, supporting energy-efficient and electrified future mobility planning. Full article

Riverbed siltation in estuaries affects ecosystem functioning, water quality, and navigation. This study investigates the flow-regulated Osellino Canal, a freshwater tributary of the Venice Lagoon that crosses a largely urbanized area and is undergoing progressive siltation. High-resolution measurements of discharge (Q) and suspended sediment concentration (SSC) were performed using hydroacoustic instrumentation from September 2019 to December 2021. The analysis examined discharge dynamics, sediment transport, and rainfall-runoff relationships. Results indicate a mean annual discharge of 2.1 m³ s⁻¹ and an average annual suspended sediment load of ~2900 ± 330 t. Discharge patterns were strongly influenced by water management, resulting in anomalous runoff coefficients (δ > 1) during dry periods. Sediment export proved to be strongly event-driven: episodic high-flow events accounted for about 23% of the total load despite representing only a small fraction of the study period. Furthermore, a strong linear relationship between runoff and sediment load (R² = 0.94) confirms an advection-dominated regime, where net export is regulated primarily by hydrodynamic volume rather than fluctuations in sediment supply. Bathymetric comparisons (2011–2019) reveal a mean annual sediment retention of 400 ± 100 t yr-1, corresponding to a trapping efficiency of approximately 12 ± 3% relative to the gross sediment input. These findings, supported by SSL–runoff regression residuals, consistently indicate net sediment accumulation associated with the long-term malfunction of a miter-gate system that impedes efficient sediment export. This study provides a critical pre-rehabilitation baseline, establishing a benchmark to evaluate the effectiveness of ongoing restoration efforts initiated in March 2022 and the future hydromorphological recovery of the canal. Full article

This study investigates the prospects for implementing hydrogen mobility in Bulgaria within the broader context of transport decarbonization. Using a three-dimensional framework—policy, technology, and geography—it combines analysis of European and national strategic documents, technological feasibility assessment, and a pilot case study in the city of Ruse. The pilot scenario includes a regional hydrogen ecosystem with a photovoltaic-powered electrolyzer, two refueling stations, deployment of 20 hydrogen buses, and retrofitting of a river vessel with fuel cell propulsion. Results indicate that hydrogen technologies can significantly reduce transport-related emissions, particularly where battery-electric solutions face operational constraints. Total Cost of Ownership (TCO) analysis shows that hydrogen buses remain more expensive than diesel or battery-electric alternatives under current conditions, even with locally produced green hydrogen. Sensitivity analysis demonstrates that cost competitiveness may be achieved after 2030 with large-scale investments, policy support, and reduced hydrogen prices. The study highlights the importance of coherent national strategies, public–private partnerships, and targeted financial instruments to enable sustainable integration of hydrogen in urban and river transport systems. Full article

This study evaluates the feasibility of continuous indoor pollutant monitoring as an indirect method for assessing extended ventilation performance in residential buildings. This research addresses key limitations of conventional short-term tracer-gas methods, which cannot account for occupant lifestyle, environmental fluctuations, and extended ventilation variability. The study employs a diffusion-based framework to interpret pollutant-concentration equalization across the residential space over extended monitoring periods. We conducted field experiments in an apartment unit equipped with both ducted and non-ducted ventilation systems. Pollutants (PM_2.5, CO₂, HCHO, and aromatic VOCs (BTEX + styrene)) were uniformly emitted. PM_2.5 and CO₂ were continuously monitored at six spatially distributed points using calibrated sensors, while HCHO and aromatic VOCs were quantified by repeated active sampling and laboratory analysis. Under ducted ventilation, average pollutant reduction rates reached 86.8% for PM_2.5, 58.3% for CO₂, and 53.6% for HCHO. Simultaneously, spatial concentration variance decreased by up to 71% within 120 min, indicating strong diffusion-driven equalizations. These results support the feasibility of extended ventilation performance monitoring using continuous pollutant sensing, with implications for IAQ management, energy optimization, and future integration with data-driven predictive models. Full article

Hazard recognition on construction sites is crucial for ensuring worker safety. Traditional methods widely rely on expert assessments, on-site inspections, and checklists, which can be time-consuming and susceptible to human error. The integration of multimodal Large Language Models (LLMs), such as GPT-based systems, offers a promising opportunity to overcome these limitations. Therefore, this study evaluates the effectiveness of GPT-4o in recognizing workplace hazards from image inputs, with a specific focus on construction sites. The results indicate that the model can serve as a valuable decision-support tool for safety professionals by providing scalable and real-time insights. However, the study also highlights key limitations, including the model’s reliance on general visual features rather than domain-specific safety knowledge, and the continued need for human supervision. Additionally, ethical concerns, including bias in AI-generated hazard assessments, data privacy, and the risk of over-reliance on AI, must be carefully managed to ensure these tools contribute responsibly and effectively to proactive risk management strategies. Full article

Electric mobility plays a key role in promoting climate-friendly transportation. Beyond technical development, the transition to electric mobility critically depends on early understanding, acceptance, and system literacy among future users and engineers. This manuscript positions hands-on engineering education as a complementary contribution to electric vehicle research. It demonstrates how core EV concepts can be introduced to children aged 12–15 through a structured, construction-based learning format. Many school students have had little opportunity to explore energy and electricity through hands-on learning. The eMobility for Kids (eM4K) workshop integrates the assembly and operation of light electric vehicles with curriculum-aligned physics instruction. The instructional focus includes vehicle kinematics as well as fundamental concepts of electricity and energy. Over a two-day course, students build a four-wheeled electric vehicle in small teams and apply their understanding through guided driving and reflection activities. Results from multiple workshop implementations between 2023 and 2025 are presented. In addition, a short exploratory snapshot survey was conducted in parallel among participating school students. The results provide indicative insights into attitudes toward future individual electric mobility, including interest in driving a small electric vehicle at the age of 15. To the authors’ knowledge, this study represents one of the first documented and systematically described educational approaches. It explores the use of real electric vehicle systems in hands-on learning for school students. Full article

This study presents a statistical modeling approach for predicting the operational reliability of induction motors used in dump truck drives. The proposed method uses censored data, including both time to failure and data on properly operating engines, to assess reliability indicators, such as uptime based on Weibull and lognormal distributions. A generalized “life curve” of the stator and bearing unit is constructed, which makes it possible to determine interval estimates of the service life and residual service life. The model is implemented as software for calculating distribution parameters and visualizing reliability dependencies. Approbation based on the operational data of quarry transport confirmed the applicability of the proposed approach for diagnosing and optimizing the maintenance system of induction motors of heavy equipment. Full article

Background: After imipenem was introduced in clinical practice, neurologic adverse effects led to recommendations against its use in patients with neurologic conditions. However, these conclusions were drawn without considering pharmacokinetic variations in such patients. Furthermore, animal studies lack the use of clinically relevant doses and supporting morphological studies in both naïve and disease models. Objectives: We aim to study the effects of imipenem in the hippocampus of naïve animals, evaluating potential behavioral and morphological alterations. Methods: Naïve Wistar rats received a 10-day course of intraperitoneal imipenem (40 mg/kg) while controls received a saline injection. After that, they were put through the Morris water maze, elevated plus maze, open-field test, and then euthanized. We analyzed neurogenesis (using doublecortin immunoreactivity), astrogliosis, and the γ-Aminobutyric acid (GABA)ergic system (using parvalbumin (PV), calretinin (CR) and calbindin (CB) immunoreactive (IR) neurons) in the hippocampus. Results: Interestingly, our results showed no significant alterations in both short and long-term memory, nor in anxiety. There were also no significant changes in the neuronal density of doublecortin-immunoreactive (IR) neurons nor in astrogliosis. Furthermore, the areal density of PV- and CR-IR was preserved in all hippocampal subfields. The density of CB-IR neurons also showed no changes in the dentate gyrus, CA3, and subiculum; however, a significant increase was found in the CA1 region. Conclusions: Our results indicate that in naïve individuals, a clinically relevant dose of imipenem does not seem to cause overt behavioral deficits or widespread morphological alterations in the hippocampus. However, a specific increase in the CB-IR neuronal population in the CA1 region highlights a localized cellular alteration/plasticity induced by the imipenem. Hence, pharmacokinetic factors seem to be the potential contributors of imipenem side effects. Further studies should focus on this as a possible cause and focus on individuals with brain diseases. Full article

This paper examines differences in agri-environmental climate and energy performance across the 27 European Union (EU) Member States. An integrated methodological framework was applied, combining the Shannon Entropy Index for objective weighting of indicators with the PROMETHEE–GAIA multi-criteria decision-making approach to rank EU countries according to their relative performance. The analysis focuses on four key indicators: (1) Climate: greenhouse gas emissions from agriculture (GHG) and (2) Energy: (1) gross available energy (GAE), (2) renewable energy primary production (REPP), and (3) gross inland consumption (GIC)—expressed as intensity measures (ktoe per million euro of agricultural gross value added), and covers the period 2017–2023. The results reveal a reduction in cross-country dispersion for greenhouse gas emission intensity, reflected in a decline in entropy values, suggesting partial convergence in climate-related performance. In contrast, energy-related intensity indicators (GAE, GIC, and REPP) remain highly heterogeneous, indicating persistent structural differences in energy efficiency, energy mix and agricultural systems across Member States, despite modest signs of convergence for selected indicators. The PROMETHEE ranking identified Romania, Italy, Greece, Spain and Poland as leading performers, reflecting favourable combinations of lower emission intensity and more efficient energy use per unit of agricultural value added. Conversely, structurally constrained economies such as Malta, Cyprus, and Luxembourg consistently ranked among the lowest-performing countries, primarily due to high energy and emission intensities relative to agricultural output. The findings point to selective and indicator-specific convergence rather than uniform long-term convergence across the EU, underscoring the need for differentiated policy approaches to support a more balanced and sustainable energy transition in agriculture. Full article

Dental caries is an example of an oral infectious disease that affects many people worldwide, but it is not well studied in deterministic mathematical modeling. Therefore, we are interested in studying the dynamics of tooth cavity disease using a deterministic modeling approach. We propose a delay differential equation system (DDEs) to describe the phenomenon. The breakthrough of the constructed model is the formulation of the recovery rate as a saturation function constrained by healthcare capacity and the plausibility of caries reformation. In addition, we consider two controls, such as a health campaign and a post-treatment intervention. The mathematical analysis yields equilibrium solutions and their stability, which is determined by the basic reproduction number (\({\Re_0}\)). Furthermore, backward bifurcation occurs as the medical facility’s capacity decreases, driven by an increasing infectious population. The sensitivity analysis results indicate that both considered controls are the most influential parameters. The optimal control problem is formulated using the Pontryagin Maximum Principle to obtain an optimal solution in suppressing the number of caries formation cases. At the end, a numerical simulation shows that interventions reduce the risk of transmission and suppress the number of infectious individuals. The constructed model has excellent future potential, such as generating a function for relapse cases or other preventive actions into an optimal control problem. Full article

Aims: To assess the impact of systemic afterload reduction on cardiorespiratory health in infants with a severe bronchopulmonary dysplasia (BPD)–systemic hypertension–left heart dysfunction (LHD) phenotype. Methods: Ten-year data were prospectively collected and analysed. The cohort included extremely preterm infants with severe BPD–systemic hypertension–LHD pathophysiology, treated with systemic afterload reduction with captopril. Main outcome measures included improvement in oxygenation and echocardiographic measures of LHD. Results: Twenty-six infants with gestation of 26.5 ± 2 weeks and median (interquartile range) birthweight of 900 (582, 1083) g were administered captopril at the corrected gestation median (range) of 40 weeks (37–67). On reassessment after five weeks, oxygen requirements (43 ± 16% to 26 ± 7%, p = 0.0001) and paired pCO₂ decreased (64 ± 9 to 53 ± 9 mm Hg, p = 0.0001). Significant improvements were seen in cardiac indices (diastolic: trans-mitral E/A ratio [1 ± 0.07 to 0.94 ± 0.07, p = 0.0004] and iso-volumic relaxation time [ms] [65 ± 3 to 56 ± 4, p < 0.0001], and systolic: mean velocity of circumferential fibre shortening [circ/s] [1.6 ± 0.2 to 1.9 ± 0.2, p < 0.0001] and left ventricular output [mL/kg/min] [177 ± 34 to 230 ± 54, p = 0.0002]). This coincided with improved aortic pulsatility (40 ± 13 to 50 ± 11 µm, p = 0.005). Conclusions: Systemic hypertension–LHD pathology amongst infants with severe BPD may be under-recognised. Systemic afterload reduction is physiologically suited in a subset of infants with severe BPD. Full article

Severe equine asthma (SEA) is a chronic inflammation of airways affecting ~14–20% of adult horses in the Northern Hemisphere. SEA is characterized by a mixed phenotype of T helper cell responses with marked neutrophilia in the bronchoalveolar lavage fluid (BALF) of affected horses. Human studies have demonstrated the impact of gut microbiota in many diseases, including asthma susceptibility and severity. However, the potential role of the gut–lung axis in the development and persistence of SEA remains to be determined. This study aimed to identify key bacterial, archaeal, and fungal microbiota alterations in the feces of horses with severe neutrophilic asthma (n = 4) compared to healthy horses (n = 8). Archaea alpha diversity was lower in the feces of SEA-affected horses, but with high abundance of archaea genus Candidatus Nitrosocosmicus, which impacts hydrogen metabolism in horses with SEA. Other key bacterial and fungi species differences lower in SEA included Blautia and Alternaria, respectively. Blautia is associated with positive metabolic health due to its fibrolytic capabilities. Overall, our findings indicate that horses experiencing severe neutrophilic asthma have an imbalance in the intestinal microbiota that may exacerbate systemic inflammatory responses through the gut–lung axis. Full article