Search Results (815)

This research proposes a novel multi-objective optimization framework for virtual power plants (VPPs) operating in day-ahead electricity markets. The VPP integrates diverse distributed energy resources (DERs) such as wind turbines, solar photovoltaics (PV), fuel cells (FCs), combined heat and power (CHP) systems, and microturbines (MTs), along with demand response (DR) programs and energy storage systems (ESSs). The trading model is designed to optimize the VPP’s participation in the day-ahead market by aggregating these resources to function as a single entity, thereby improving market efficiency and resource utilization. The optimization framework simultaneously minimizes operational costs, maximizes system flexibility, and enhances reliability, addressing challenges posed by renewable energy integration and market uncertainties. A new flexibility index is introduced, incorporating both the technical and economic factors of individual units within the VPP, offering a comprehensive measure of system adaptability. The model is validated on IEEE 24-bus and 118-bus systems using evolutionary algorithms, achieving significant improvements in flexibility (20% increase), cost reduction (15%), and reliability (a 30% reduction in unsupplied energy). This study advances the development of efficient and resilient power systems amid growing renewable energy penetration. Full article

Background/Objectives: Some patients undergoing vitreoretinal surgery (VRS) require general anesthesia (GA), despite the possibility of developing intolerable postoperative pain perception (IPPP). Intraoperative rescue opioid analgesia (IROA) administration during GA poses a risk of perioperative nausea and vomiting (PONV), which may result in suprachoroidal hemorrhage with permanent visual impairment. Adequacy of Anesthesia (AoA) optimizes intraoperative IROA titration. Intravenous preemptive analgesia (IPA) with cyclooxygenase-3 (COX-3) inhibitors is added to GA to reduce the IROA dose. In this additional analysis, we assessed the impact of preemptive analgesia with COX-3 inhibitors, administered alongside GA with AoA-guided IROA, on the incidence of PONV, oculocardiac reflex (OCR), and oculoemetic reflex (OER) in patients undergoing VRS as secondary outcomes. Methods: A total of 165 patients scheduled for VRS were randomly assigned to receive AoA-guided GA combined with IPA at a single dose of 1 g of paracetamol (acetaminophen) or 2.5 g of metamizole or both. A total of nine patients were excluded due to technical problems with the intraoperative surgical pleth index (SPI) measurement, inability to report postoperative pain, and postoperative arousal resulting in a loss of follow-up in Stage 5. Results: Regardless of the group assignment, AoA guidance of GA resulted in PONV in 4%, OCR in 10%, and OER in 0% of the 153 analyzed patients undergoing VRS. No significant differences were observed between the groups regarding the type of IPA. PONV was observed in 2.11% (3/142) of patients with zero, one, or two risk factors of PONV, as compared to 27% (3/11) of patients with at least three PONV risk factors, assessed using the Apfel score. Conclusions: IPA with both paracetamol and metamizole did not demonstrate a benefit in reducing the analyzed adverse events compared with their single use in patients undergoing VRS under AoA guidance during GA. Surprisingly, PONV was hardly observed in patients with zero, one, or two PONV risk factors assessed by the Apfel score who underwent AoA-guided VRS during GA with IPA using one or two COX-3 inhibitors. Full article

Low-Altitude and Slow-Speed Small (LSS) targets pose significant challenges to air defense systems due to their low detectability and complex maneuverability. To enhance defense capabilities against low-altitude targets and assist in formulating interception decisions, this study proposes a new threat assessment algorithm based on multisource data fusion under visible-light detection conditions. Firstly, threat assessment indicators and their membership functions are defined to characterize LSS targets, and a comprehensive evaluation system is established. To reduce the impact of uncertainties in weight allocation on the threat assessment results, a combined weighting method based on bias coefficients is proposed. The proposed weighting method integrates the analytic hierarchy process (AHP), entropy weighting, and CRITIC methods to optimize the fusion of subjective and objective weights. Subsequently, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Dempster–Shafer (D-S) evidence theory are used to calculate and rank the target threat levels so as to reduce conflicts and uncertainties from heterogeneous data sources. Finally, the effectiveness and reliability of the two methods are verified through simulation experiments and measured data. The experimental results show that the TOPSIS method can significantly discriminate threat values, making it suitable for environments requiring rapid distinction between high- and low-threat targets. The D-S evidence theory, on the other hand, has strong anti-interference capability, making it suitable for environments requiring a balance between subjective and objective uncertainties. Both methods can improve the reliability of threat assessment in complex environments, providing valuable support for air defense command and control systems. Full article

Background: First-Line Nurse Managers (FLNMs) have been recognised as key contributors to achieving organisational objectives, serving as vital intermediaries between management, staff, and patients. Assessing whether the Span of Control (SOC) is appropriate and providing the necessary support for FLNMs to fulfil their responsibilities poses a considerable challenge for healthcare organisations. No tool exists in Spain to guide decisions regarding FLNM’s SOC and resource needs. The aim of this study is to design a tool for assessing the span of control of first-line nurse managers in hospitals. Methods: This study employed a tool development and content validation design to create the EASOC-Nursing instrument (Eliges Aragón SOC tool). The study was conducted in three stages: an integrative literature review, followed by a national Delphi study with 43 experts in nursing management, and finally, focus group discussions. Results: A tool was created to assess first-line nurse managers’ (FLNM) span of control (SOC) using 13 key indicators, organised into four categories: unit (operations and resources, conflicts, and logging and monitoring of activities), professional (staff and competencies), FLNM (autonomy, education, and leadership), and organisation (support systems, education, and research). It includes a total of 31 items and determines SOC adequacy by establishing cut-off points that classify it as below acceptable, appropriate, or excessive. When the SOC is inadequate, the tool provides specific recommendations for support measures, such as the provision of administrative personnel or the appointment of a co-leader. Conclusions: The EASOC-Nursing tool offers a comprehensive evaluation of the core dimensions of the FLNM role and its responsibilities in Spain. Furthermore, it delivers practical guidance on the most suitable types of support to facilitate the attainment of optimal outcomes for both patients and healthcare organisations. In light of the global nursing shortage, the availability of a robust and context-sensitive instrument to assess the SOC enables hospital nursing management to allocate resources more strategically, thereby enhancing working conditions for professionals and contributing to improved patient care outcomes. Full article

Most existing ultra-deep gas wells are characterized by high temperature, high pressure, and high sulfur content. During development, they face serious challenges such as unclear mechanisms of acid gas-induced blowouts and difficulties in wellbore pressure inversion, posing significant challenges to well control operations. To reveal the reasons behind the tendency of acidic gases to trigger blowouts and to clarify the impact of different concentrations of acidic gases on the flow behavior of annular fluids, this study considers the effects of solubility and phase changes on the physical properties of acidic gases. A method replacing critical parameters with pseudo-critical parameters is used to analyze the variation trends of gas density, solubility, and other properties along the well depth. A mathematical model for the annular flow of acidic gas overflow incorporating solubility phase change effects is established. The model is numerically solved using a four-point difference scheme, exploring the essential characteristics of gas flow in the annulus after overflow, and discussing the distribution patterns of physical properties of acidic gases, as well as dynamic parameters such as wellbore pressure and temperature along the well depth. Numerical simulations show that the physical properties of acidic gases change significantly with well depth: the more acidic gas present in the wellbore, the smaller the deviation factor, and the greater the density and viscosity, with parameter changes exceeding 40% near the pseudo-critical point for binary mixtures with 40% H₂S. Compared to pure methane, mixed fluids containing acidic gas experience more than 20% volume expansion near the wellhead for ternary mixtures with 20% CO₂ and 20% H₂S, and the flow velocity increases by more than 10% for mixtures with ≥30% acidic gas content, leading to a higher risk of a sudden pressure drop during well control. This study clarifies the migration patterns of acidic gas overflow in HPHT (high pressure, high temperature) gas wells, providing valuable guidance for optimizing well control design, improving well control emergency plans, and developing well-killing measures. Full article

Biofilms are communities of microorganisms that pose a problem in many areas, including the food industry, drinking water treatment, and medicine, because they can contain pathogens and are difficult to eliminate. For this reason, the possibility of biofilm reduction by ultraviolet (UV) or visible light was investigated using data from published reports. Results for different applications, spectral ranges, and microorganisms were compared by performing MANOVA tests. Approximately 140 publications were found that dealt with the irradiation of water or surfaces for biofilm reduction or reduction in biofilm formation. Irradiation of surfaces with UV or visible light in the spectral range 200–525 nm had a positive effect on biofilm reduction and reduction in biofilm formation, although the results for irradiation of water were conflicting. Most investigations were carried out on P. aeruginosa biofilms, but other Gram-positive and Gram-negative bacteria, as well as some fungi and their biofilm sensitivities to irradiation, were also analyzed. Limited data were available for the UVB (280–315 nm) and UVA (315–400 nm) range. Most experiments to date have been carried out in the UVC (100–280 nm) or in the visible violet/blue spectral (400–500 nm) range, with the UVC range being 2–3 orders of magnitude more efficient in terms of applied irradiation dose. Other quantitative statements were difficult to make as the results from the different working groups were highly scattered. Irradiation can reduce the microorganisms in biofilms but does not completely remove biofilms. New biofilm formation can at least be delayed by surface irradiation. Whether it is also possible to prevent the formation of new biofilms in the long term is open to question. Which irradiation wavelengths are optimal for anti-biofilm measures is also still unclear. Full article

Catalysis plays a pivotal role in green chemistry practices, particularly in reducing waste generated during chemical synthesis. Decatungstate (DT) emerges as a potent photocatalyst for Type I oxidations, exhibiting remarkable resilience to oxygen quenching, a characteristic that sets it apart from other excited triplet state photocatalysts. While homogeneous DT catalysis demonstrates effectiveness, its solubility poses challenges for its separation and recycling. To address these limitations, we focus on the development and comparison of heterogeneous DT photocatalysts, aiming to optimize their yield, recovery, and reusability. We synthesized tetrabutylammonium decatungstate (TBADT)-supported catalysts using silica, alumina, titanium dioxide, and glass wool and characterized them using diffuse reflectance measurements. Subsequently, we evaluated their photocatalytic performance by monitoring the oxidation of 1-phenylethanol and cyclohexanol under UVA irradiation. Our findings reveal that TBADT@silica emerges as the most effective catalyst, achieving approximately 20% conversion of cyclohexanol and 50% conversion of 1-phenylethanol with good reusability. Interestingly, we observed that 3-aminopropyl-triethoxysilane (APTES) treatment, intended to enhance DT anchoring, unexpectedly quenches the ³DT* triplet state, reducing catalytic activity. This unexpected finding underscores the importance of careful consideration in designing robust and recyclable heterogeneous decatungstate catalysts. Our research contributes significantly to the advancement of heterogeneous photocatalysis, paving the way for future applications in flow photochemistry. Further, we share a Python code (Google 3.12.11) to correct spectra obtained in Cary spectrometers. Full article

This research evaluates the vulnerability of public infrastructure in San Luis parish, Riobamba canton, Ecuador, to the flood risk posed by the Chibunga River under return period scenarios of 10, 50, 100, and 500 years. The main objective was to identify the most exposed systems—such as drinking water, sewerage, power grid, and utility poles—in order to prioritize mitigation measures. The methodology combined hydrometeorological analysis, hydraulic modeling using HEC-HMS and Iber, and the estimation of economic losses through the DaLA methodology. The results reveal that the low vulnerability of the drinking water system, as less than 0.08% of the network’s length, is at risk in the high-to-very-high range, even in a scenario with a 500-year return period. On the other hand, there is evidence of high exposure of the sewerage network in extreme scenarios, considering that 49.15% is at high-to-very-high risk in the worst-case scenario. Furthermore, as the return period increases, there is a growing impact on the electrical network, where the proportion of assets at high-to-very-high risk increases from 0.60% to 6.88% for high voltage, 0.00% to 18.03% for low voltage, and 0.00% to 1.18% for streetlights for a return period of 10 to 500 years. It should be noted that the estimated direct economic losses amount to USD 84,162.86 when taking into account the worst-case scenario. In this regard, the novelty of this study lies in the integration of technical, hydraulic, and economic analyses for a scarcely studied rural Andean area, providing crucial data for preventive risk management. It concludes that investment in prevention is more cost-effective than post-disaster reconstruction, recommending the strengthening of the sewerage system’s hydraulic capacity and the optimization of electrical infrastructure protection. Full article

Objectives: There is a critical need for effective focal therapies for patients with inoperable or anatomically complex tumors where conventional ablation techniques pose high risk or are ineffective. Integrated Nanosecond Pulsed Irreversible Electroporation (INSPIRE) is a novel non-thermal ablation modality which uses real time temperature feedback during pulse delivery to safely treat tumors near critical structures. This study evaluated the impact of exposed electrode length on ablation zone size, reproducibility, and cardiac safety in a large animal model. Methods: INSPIRE treatments were performed in an in vivo healthy porcine liver model. All treatments administered 6000 V 1000 ns pulses with a 45 °C temperature set point. Treatments were administered percutaneously via an electrode and grounding pad approach using an internally cooled electrode applicator. The exposed electrode region at the distal end of the applicator was set to either 0.5, 1.0, 1.5, or 2.0 cm. Ablation zones were assessed via ultrasound, contrast-enhanced CT, and gross pathology one week post-treatment. Cardiac safety was evaluated by measuring pre- and post-treatment serum Troponin levels. Results: All treatments were completed without adverse events. Troponin levels remained stable (pre: 0.249 ng/mL; post: 0.224 ng/mL), indicating no measurable cardiac injury. The 1.5 cm exposure length produced the largest and most consistent ablation volumes, with a mean volume of 12.8 ± 2.6 cm³ and average dimensions of 3.7 × 2.7 cm in under 6 min. Increasing exposure length beyond 1.5 cm introduced greater variability and reduced treatment volumes. Conclusions: INSPIRE enables safe, large-volume, single-applicator ablation without a need for electrical pulse synchronization with R wave in cardiac rhythm. The 1.5 cm exposure length offers optimal balance between energy delivery and treatment consistency. These findings support further clinical investigation of INSPIRE for non-thermal ablation of inoperable tumors. Full article

With the significant increase in solar power generation’s proportion in power systems, the uncertainty of its power output poses increasingly severe challenges to grid operation. In recent years, solar forecasting models have achieved remarkable progress, with various developed models each exhibiting distinct advantages and characteristics. To address complex and variable geographical and meteorological conditions, it is necessary to adopt a multi-model fusion approach to leverage the strengths and adaptability of individual models. This paper proposes a photovoltaic power prediction framework based on multi-stage ensemble learning, which enhances prediction robustness by integrating the complementary advantages of heterogeneous models. The framework employs a three-level optimization architecture: first, a recursive feature elimination (RFE) algorithm based on LightGBM–XGBoost–MLP weighted scoring is used to screen high-discriminative features; second, mutual information and hierarchical clustering are utilized to construct a heterogeneous model pool, enabling competitive intra-group and complementary inter-group model selection; finally, the traditional static weighting strategy is improved by concatenating multi-model prediction results with real-time meteorological data to establish a time-period-based dynamic weight optimization module. The performance of the proposed framework was validated across multiple dimensions—including feature selection, model screening, dynamic integration, and comprehensive performance—using measured data from a 75 MW photovoltaic power plant in Inner Mongolia and the open-source dataset PVOD. Full article

Background/Objectives: Gingival recession poses significant challenges in periodontal therapy, particularly in procedures aimed at achieving predictable root coverage and long-term stability of grafts. Conditioning of the root surface plays a crucial role in improving biomaterial adhesion and facilitating periodontal regeneration. This in vitro study aimed to evaluate the morphological and microroughness alterations of root cementum following different mechanical and chemical conditioning protocols commonly used in mucogingival surgery. Methods: Forty extracted human single-rooted teeth were randomly allocated into eight groups: untreated control, mechanical scaling alone, and scaling combined with ethylenediaminetetraacetic acid (EDTA), citric acid, phosphoric acid, tetracycline, doxycycline, or saline. Surface roughness was measured using contact profilometry, while structural modifications were analyzed via scanning electron microscopy. Results: Statistically significant intergroup differences (p < 0.05) were observed. Baneocin treatment produced the most conservative changes, with limited surface roughness and minimal structural alteration, whereas phosphoric acid, tetracycline, and EDTA caused pronounced demineralization and surface porosity. Citric acid and doxycycline induced moderate alterations, with partial preservation of cementum integrity. The null hypothesis assuming no surface or morphological changes was rejected. Conclusions: These findings indicate that low-aggressiveness agents may achieve an optimal balance between surface decontamination and cementum preservation, which is critical for enhancing graft integration and improving clinical outcomes in root coverage surgery. Full article

The process of social globalization and urbanization has developed rapidly in China, and the tension between economic development and the eco-environment is becoming increasingly tense, posing a major challenge to the sustainable development strategy of the Shandong Peninsula Urban Agglomeration (SPUA). Coordination development between economic development and habitat quality has become essential for preserving ecological stability and advancing long-term regional sustainability. This study constructed the optimal regression model to measure GDP density using night-time lighting data and economic statistical data and calculated habitat quality at the grid scale with the InVEST model. The spatiotemporal dynamics and driving factors of the coupling coordination between economy and habitat quality (EHCCD) were revealed using the coupling coordination degree model and the Geo-detector model. The results show that (1) between 2000 and 2020, the spatial pattern of GDP density has evolved from a single-core to a multi-core networked development. (2) The habitat quality of the SPUA exhibited a spatial pattern high in the east and low in the west, showing a downward trend. (3) The synergistic effect between GDP density and habitat quality was strengthened continuously, showing an overall strengthening tendency. (4) Driving factors’ influence on the EHCCD showed evident differences; socio-economic factors such as built-up area especially had greater explanatory power for the EHCCD; the interaction factors had shifted from socio-economic dominance to synergistic dominance of natural and human factors. This study not only overcomes the limitations imposed by administrative boundaries on assessing inter-regional coupling coordination but also provides fundamental data support for cross-regional cooperation, thereby advancing the sustainable development goal of the SPUA. Full article

Background/Objectives: Influenza poses a substantial global public health challenge, disproportionately affecting vulnerable populations. Vaccination is the most effective preventive measure, and recent strategies in Italy emphasize the principle of “appropriateness”—the alignment of specific vaccine formulations (e.g., adjuvanted or high-dose) with targeted risk groups to optimize protection. Nevertheless, challenges persist in ensuring the consistent administration of the most suitable vaccine, particularly among high-risk individuals who would benefit most. Methods: A retrospective descriptive study was conducted using data from the 2023–2024 and 2024–2025 influenza vaccination campaigns of the Local Health Authority of Catania. Vaccination data were analyzed by age group and vaccine type, based on national immunization guidelines. Population categories included individuals ≥ 65 years, adults 60–64 years, adults 18–59 years (with/without chronic conditions), children, and pregnant/postpartum women. Vaccine types analyzed were aQIV, QIV-HD, QIV-SD, QIVcc, and LAIV. Descriptive statistics were used, and Relative Risk (RR) with 95% Confidence Intervals (CI) was calculated using the 60–64 age group as a reference. Analyses were performed with Stata 18.0. Results: In 2023–2024, 78.8% of individuals ≥ 65 received recommended vaccines, compared to 100% in the 60–64 group (RR = 0.23; 95% CI: 0.225–0.231). Adults 18–59, children, and pregnant/postpartum women showed ≥99% adherence. In 2024–2025, appropriateness in the ≥65 group improved to 96.1% (RR = 0.12; 95% CI: 0.118–0.128). All other groups maintained high adherence (≥99%), except for 6.2% of children aged 6 months–2 years who inappropriately received LAIV. Conclusions: Despite dramatically improved vaccination appropriateness in the elderly, a persistent and critical safety issue--inappropriate administration LAIV use in 6.2% of young children—highlights the need for targeted interventions to ensure complete patient safety. Full article

Accurate monitoring of canopy nitrogen content in wolfberry (Lycium barbarum L.) is essential for optimizing fertilization management, improving crop yield, and promoting sustainable agriculture. However, the sparse, architecturally complex canopy of this perennial shrub—featuring coexisting branches, leaves, flowers, and fruits across maturity stages—poses significant challenges for canopy spectral-based nitrogen assessment. This study integrates methods across canopy spectral acquisition, transformation, feature spectral selection, and model construction, and specifically explores the potential of hyperspectral remote sensing, integrated with spectral mathematical transformations and machine learning algorithms, for predicting canopy nitrogen content in wolfberry. The overarching goal is to establish a feasible technical framework and predictive model for monitoring canopy nitrogen in wolfberry. In this study, canopy spectral measurements are systematically collected from densely overlapping leaf regions within the east, south, west, and north orientations of the wolfberry canopy. Spectral data undergo mathematical transformation using first-derivative (FD) and continuum-removal (CR) techniques. Optimal spectral variables are identified through correlation analysis combined with Recursive Feature Elimination (RFE). Subsequently, predictive models are constructed using five machine learning algorithms and three linear regression methods. Key results demonstrate that (1) FD and CR transformations enhance the correlation with nitrogen content (max correlation coefficient (r) = −0.577 and 0.522, respectively; p < 0.01), surpassing original spectra (OS, −0.411), while concurrently improving model predictive capability. Validation tests yield maximum R² values of 0.712 (FD) and 0.521 (CR) versus 0.407 for OS, confirming FD’s superior performance enhancement. (2) Nonlinear machine learning models, by capturing complex canopy-light interactions, outperform linear methods and exhibit superior predictive performance, achieving R² values ranging from 0.768 to 0.976 in the training set—significantly outperforming linear regression models (R² = 0.107–0.669). (3) The Random Forest (RF) model trained on FD-processed spectra achieves the highest accuracy, with R² values of 0.914 (training set) and 0.712 (validation set), along with an RPD of 1.772. This study demonstrates the efficacy of spectral transformations and nonlinear regression methods in enhancing nitrogen content estimation. It establishes the first effective field monitoring strategy and optimal predictive model for canopy nitrogen content in wolfberry. Full article

Background: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and acute respiratory failure (ARF) are leading causes of hospitalization and functional decline in Italy, posing a significant burden on the healthcare system. In 2024, new national guidelines mandated the use of Intensive Care Rehabilitation Units (ICRUs) within MDC4 to provide structured post-acute respiratory rehabilitation. Objective: This study aimed to evaluate functional outcomes in patients with AECOPD and ARF treated in a single ICRU, assessing the effectiveness of guideline-based rehabilitation protocols. Methods: A retrospective audit was conducted on patients admitted in 2024 to a dedicated ICRU. Functional outcomes were assessed using the Barthel Index, Six-Minute Walking Test (6MWT), and Rehabilitation Complexity Index (RCI-e13). Correlation analyses were performed to explore relationships between baseline status, rehabilitation progression, and discharge outcomes. Results: Thirty-six patients were included. Significant improvements were observed across all scales from admission to discharge. The Barthel Index showed a strong positive correlation between initial and final scores (r = 0.72), while the 6MWT indicated a similarly robust correlation (r = 0.73). Greater functional gains were noted among patients with lower baseline scores, especially in mobility. The RCI-e13 reflected decreased clinical complexity by discharge, with moderate correlations to baseline severity. Age moderately correlated with length of stay (r = 0.30), but not with outcome scores. Conclusions: The implementation of early, intensive rehabilitation in an ICRU setting—aligned with Italy’s 2024 national guidelines—led to measurable functional improvements in patients with AECOPD and ARF. These findings support the utility of structured outcome monitoring and reinforce the role of ICRUs in optimizing post-acute care pathways within respiratory rehabilitation services. Full article