Search Results (5,418)

In this study, the distribution patterns of the nitrifying and denitrifying microbiome in a large-scale biofilter (587.24 m³) in a cold freshwater recirculating aquaculture system (RAS) was investigated. Previous studies have revealed that the water quality, nitrification, and denitrification rates in the front (BFF), middle (BFM), and back (BFB) of this biofilter are different. The results showed the highest diversity of the denitrifying microbiome in the BFB, followed by BFF and BFM, whereas nitrifying microbiome diversity remained consistent across different positions. Two genera, Nitrosomonas and Nitrosospira, dominated the nitrifying microbiome, while Pseudomonas, Thauera, Cupriavidus, Dechloromonas, Azoarcus, and Paracoccus comprised the top six denitrifying genera. Principal coordinate analysis indicated a distinct spatial distribution pattern of the denitrifying microbiome but not the nitrifying microbiome. The genera Pseudomonas and Dechloromonas were the biomarkers of the BFF and BFB, respectively. Redundancy analysis showed that nitrite, nitrate, dissolved oxygen, and soluble reactive phosphorus influenced the functional microbiome distribution pattern. Network correlation analysis identified one nitrifying hub (Nitrosospira) in the BFF, five denitrifying hubs (Aromatoleum, Dechloromonas, Paracoccus, Ruegeria, and Thauera) in the BFM, and three denitrifying hubs (Azoarcus, Magnetospirillum, and Thauera) in the BFB. Exclusively negative correlations were found between hubs and its adjacent nodes in the BFF and BFB. This study demonstrates that habitat can shape the distribution patterns of the nitrifying and denitrifying microbiome in the biofilter of the RAS, with the BFF exhibiting greater benefits for the nitrification process. Full article

To address the shortcomings of poor convergence and the ease of falling into local optima when using the traditional gold rush optimization (GRO) algorithm to solve the complex scheduling problem of a combined cooling, heating, and power (CCHP) microgrid system, an optimal scheduling model for a microgrid based on the improved gold rush optimization (IGRO) algorithm is proposed. First, the Halton sequence is introduced to initialize the population, ensuring a uniform and diverse distribution of prospectors, which enhances the algorithm’s global exploration capability. Then, a dynamically adaptive weighting factor is applied during the gold mining phase, enabling the algorithm to adjust its strategy across different search stages by balancing global exploration and local exploitation, thereby improving the convergence efficiency of the algorithm. In addition, a weighted global optimal solution update strategy is employed during the cooperation phase, enhancing the algorithm’s global search capability while reducing the risk of falling into local optima by adjusting the balance of influence between the global best solution and local agents. Finally, a t-distribution mutation strategy is introduced to improve the algorithm’s local search capability and convergence speed. The IGRO algorithm is then applied to solve the microgrid scheduling problem, with the objective function incorporating power purchase and sale cost, fuel cost, maintenance cost, and environmental cost. The example results show that, compared with the GRO algorithm, the IGRO algorithm reduces the average total operating cost of the microgrid by 3.29%, and it achieves varying degrees of cost reduction compared to four other algorithms, thereby enhancing the system’s economic benefits. Full article

Background/Objectives: The TOPAZ-1 phase III trial reported a survival benefit of using durvalumab, an anti-programmed death ligand 1 (anti-PD-L1) antibody, in combination with gemcitabine and cisplatin (GCD) treatment in patients with advanced biliary tract cancer. This retrospective study investigated the efficacy and safety of GCD treatment for advanced biliary tract cancer in real-world conditions. Methods: The study subjects were 52 patients with biliary tract cancer who received GCD therapy between January 2023 and May 2024. The observation parameters included the modified Glasgow Prognostic Score (mGPS), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), tumor markers (CEA, CA19-9), overall response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse events. Results: The cohort included 36 men and 16 women, with a median age of 73.0 years. There were 36 cases of cholangiocarcinoma (distal: 10, perihilar: 19, intrahepatic: 7), 13 cases of gallbladder cancer, and 3 cases of ampullary carcinoma. The stages were locally advanced in 30 cases and metastatic in 22 cases. Biliary drainage was performed in 30 cases. There were 38 cases receiving first-line therapy and 14 cases receiving second-line or later treatments. The median values at the start of GCD therapy were ALB 3.7 g/dL, CRP 0.39 mg/dL, NLR 2.4, PLR 162.5, CEA 4.8 ng/mL, and CA19-9 255.9 U/mL. The mGPS distribution was 0:23 cases, 1:18 cases, and 2:11 cases. The treatment outcomes were ORR 25.0% (CR 2 cases, PR 11 cases), DCR 78.8% (SD 28 cases, PD 10 cases, NE 1 case), median PFS 8.6 months, and median OS 13.9 months. The PLR was suggested to be useful for predicting PFS. A decrease in CEA at six weeks after the start of treatment was a significant predictor of PFS and OS. Gallbladder cancer had a significantly poorer prognosis compared to other cancers. The immune-related adverse events included hypothyroidism in two cases, cholangitis in one case, and colitis in one case. Conclusions: The ORR, DCR, and PFS were comparable to those in the TOPAZ-1 trial. Although limited by its retrospective design and small sample size, this study suggests that GCD therapy is an effective treatment regimen for unresectable biliary tract cancer in real-world clinical practice. Full article

To reduce carbon emissions in the shipping industry, the energy management problem of the ship-integrated energy system (S-IES) is analyzed in this paper. Firstly, a marine environmental risk field model is constructed to quantify the degree of hazard when designing the sailing route. Meanwhile, an energy management model that considers both economic and environmental benefits is developed to enhance the penetration rate of renewable resources. Subsequently, a distributed energy management algorithm based on finite-time consensus theory is proposed to ensure a rapid and accurate response to load demand. Moreover, a mathematical analysis is provided to demonstrate the algorithm’s effectiveness. Finally, the sea area between Singapore Port (Singapore) and Penang Port (Malaysia) is chosen as the simulation environment. The experimental results demonstrate the effectiveness of energy management for the S-IES. Full article

Background/Objectives: The expansion of National Health Insurance (NHI) coverage for dental implants in South Korea has substantially increased implant placements among older adults. While implants offer functional and esthetic benefits, their lack of periodontal ligaments alters occlusal force distribution, potentially increasing biomechanical stress on adjacent or opposing teeth. This study aimed to investigate the association between the increased number of dental implants and the incidence of cracked teeth following the introduction of implant insurance. Methods: A retrospective analysis was conducted using the Clinical Data Warehouse of Seoul St. Mary’s Dental Hospital. Patients who underwent molar crown restorations between 2014 and 2022 were included. The incidence and clinical features of cracked teeth were compared before (2014–2015) and after (2016–2022) the introduction of implant insurance. Statistical analyses assessed differences in symptom presentation, pulp status, and treatment outcomes. Results: Among 5044 molars restored with crowns, 1692 were diagnosed with cracks. The incidence of cracked teeth significantly increased after NHI coverage for implants (25.5% vs. 32.6%, p < 0.001). Cases after insurance implementation showed fewer signs and symptoms at initial presentation (67.4% vs. 50.0%, p < 0.001), reduced irreversible pulpitis (37.2% vs. 25.8%, p < 0.001), and increased preservation of pulp vitality (46.9% vs. 57.8%, p < 0.001). These shifts may reflect changes in occlusal adjustment practices and earlier clinical intervention. Conclusions: The findings suggest a temporal link between increased implant placement and the rising incidence of cracked teeth. Implant-induced occlusal changes may contribute to this trend. Careful occlusal evaluation and follow-up are essential after implant placement, and further prospective studies are warranted to confirm causality and refine prevention strategies. Full article

Background: Cochlear implantation (CI) in pediatric patients with cochlear nerve deficiencies (CND) remains controversial due to a highly variable clinical population, lack of evidence-based guidelines, and mixed research findings. This study assessed current clinical perspectives and practices regarding CI candidacy in children with CND among hearing healthcare professionals in the USA. Methods: An anonymous 19-question online survey was distributed to CI clinicians nationwide. The survey assessed professional background, experience with aplasia and hypoplasia, and perspectives on CI versus auditory brainstem implant (ABI) candidacy, including imaging practices and outcome expectations. Both multiple-choice and open-ended responses were analyzed to identify trends and reasoning. Results: Seventy-two responses were analyzed. Most clinicians supported CI for hypoplasia (60.2%) and, to a lesser extent, for aplasia (41.7%), with audiologists more likely than neurotologists to favor CI. Respondents cited lower risk, accessibility, and the potential for benefit as reasons to attempt CI before ABI. However, many emphasized a case-by-case approach, incorporating imaging, electrophysiological testing, and family counseling. Only 22.2% considered structural factors the best predictors of CI success. Conclusions: Overall, hearing health professionals in the USA tend to favor CI as a first-line option, while acknowledging the limitations of current diagnostic tools and the importance of individualized, multidisciplinary decision-making in CI candidacy for children with CND. Findings reveal a high variability in clinical perspectives on CI implantation for pediatric aplasia and hypoplasia and a lack of clinical consensus, highlighting the need for more standardized assessment and imaging protocols to provide greater consistency across centers and enable the development of evidence-based guidelines. Full article

This conceptual position is based on the diagnosis that artificial intelligence (AI) accentuates existing economic and geopolitical divides in communities in the Global South, which provide data without receiving rewards. Based on bioethical precedents of fair distribution of genetic resources, it is proposed to transfer the principle of benefit-sharing to the emerging algorithmic governance in the context of AI. From this discussion, the study reveals an algorithmic concentration in the Global North. This dynamic generates political, cultural, and labor asymmetries. Regarding the methodological design, the research was qualitative, with an interpretive paradigm and an inductive method, applying documentary review and content analysis techniques. In addition, two theoretical and two analytical categories were used. As a result, six emerging categories were identified that serve as pillars of the studied principle and are capable of reversing the gaps: equity, accessibility, transparency, sustainability, participation, and cooperation. At the end of the research, it was confirmed that AI, without a solid ethical framework, concentrates benefits in dominant economies. Therefore, if this trend does not change, the Global South will become dependent, and its data will lack equitable returns. Therefore, benefit-sharing is proposed as a normative basis for fair, transparent, and participatory international governance. Full article

To address the substantial disparities in operational characteristics between social vehicles and dedicated bus lanes, as well as the sub-optimal coordination control effects, a comprehensive approach is proposed. This approach integrates social vehicle arterial coordination with bus priority control in dedicated bus lanes. Initially, an analysis of the differences in travel time distribution on both types of roads is conducted. The likelihood of buses passing through upstream and downstream intersections without stopping is also assessed. This analysis aids in determining the correlated traffic states and the corresponding signal adjustment strategies for arterial coordination. Subsequently, an incentive mechanism is established by quantitatively analyzing vehicle delay losses and bus priority benefits based on the signal adjustment strategy. Finally, a deep reinforcement learning framework is proposed to solve, in real-time, the optimal signal adjustment strategy. Simulation experiments indicate that, in comparison to the arterial coordination of social vehicles and dedicated bus arterial coordination control, this method significantly reduces the average per capita delay by 38.63% and 27.43%, respectively, under conventional traffic flow scenarios. This is in contrast to the separate arterial coordination for social vehicles and dedicated bus lanes. Furthermore, it leads to a reduction of 52.17% in the number of bus stops at intersections when compared solely with the arterial coordination of social vehicles. In saturated traffic flow scenarios, this method achieves a reduction in average per capita delay by 29.7% and 9.6%, respectively, while also decreasing the number of bus stops at intersections by 39.5% and 8.7%, respectively. Full article

The spatial variation of forest ecosystem services at regional scales remains poorly understood, and few studies have explicitly analyzed how ecosystem services are distributed across different forest management types. This study assessed the spatial overlap between forest management types and ecosystem service hotspots in the Southeastern United States (SEUS) and the Pacific Northwest (PNW) forests. We used the InVEST suite of tools and GIS to quantify carbon storage and water yield. Carbon storage was estimated, stratified by forest group and age class, and literature-based biomass pool values were applied. Average annual water yield and its temporal changes (2001–2020) were modeled using the annual water yield model, incorporating precipitation, potential evapotranspiration, vegetation type, and soil characteristics. Ecosystem service outputs were classified to identify hotspot zones (top 20%) and to evaluate the synergies and tradeoffs between these services. Hotspots were then overlaid with forest management maps to examine their distribution across management types. We found that only 2% of the SEUS and 11% of the PNW region were simultaneous hotspots for both services. In the SEUS, ecological and preservation forest management types showed higher efficiency in hotspot allocation, while in PNW, production forestry contributed relatively more to hotspot areas. These findings offer valuable insights for decision-makers and forest managers seeking to preserve the multiple benefits that forests provide at regional scales. Full article

Background/Objectives: Phase II oncology trials often rely on single-arm designs to test $H_0:\pi ={\pi }_0$ versus $H_a:\pi >{\pi }_0$, especially when randomized trials are infeasible due to cost or disease rarity. Traditional approaches, such as the exact binomial test and Simon’s two-stage design, tend to be conservative, with actual Type I error rates falling below the nominal $\alpha$ due to the discreteness of the underlying binomial distribution. This study aims to develop a more efficient and flexible method that maintains accurate Type I error control in such settings. Methods: We propose a convolution-based method that combines the binomial distribution with a simulated normal variable to construct an unbiased estimator of $\pi$. This method is designed to precisely control the Type I error rate while enabling more efficient trial designs. We derive its theoretical properties and assess its performance against traditional exact tests in both one-stage and two-stage trial designs. Results: The proposed method results in more efficient designs with reduced sample sizes compared to standard approaches, without compromising the control of Type I error rates. We introduce a new two-stage design incorporating interim futility analysis and compare it with Simon’s design. Simulations and real-world examples demonstrate that the proposed approach can significantly lower trial cost and duration. Conclusions: This convolution-based approach offers a flexible and efficient alternative to traditional methods for early-phase oncology trial design. It addresses the conservativeness of existing designs and provides practical benefits in terms of resource use and study timelines. Full article

Blasting operations in surface mining pose a risk of flyrock, which is a critical safety concern for both personnel and infrastructure. This study presents the use of unmanned aerial vehicles (UAVs) and photogrammetric techniques to improve the accuracy of blast design, particularly in relation to controlling burden values and reducing flyrock. The research was conducted in a basalt quarry in Lower Silesia, where high rock fracturing complicated conventional blast planning. A DJI Mavic 3 Enterprise UAV was used to capture high-resolution aerial imagery, and 3D models were created using Strayos software. These models enabled precise analysis of bench face geometry and burden distribution with centimeter-level accuracy. The results showed a significant improvement in identifying zones with improper burden values and allowed for real-time corrections in blasthole design. Despite a ten-fold reduction in the number of images used, no loss in model quality was observed. UAV-based surveys followed software-recommended flight paths, and the application of this methodology reduced the flyrock range by an average of 42% near sensitive areas. This approach demonstrates the operational benefits and enhanced safety potential of integrating UAV-based photogrammetry into blasting design workflows. Full article

This paper presents a comparative analysis of electric field (E-field) mitigation in inductive power transfer (IPT) systems. It focuses on how distributed capacitor placement interacts with coil topology to influence E-field emissions. The study compares traditional sequential-winding coils and the alternating voltage phase coil (AVPC), which employs a sequential inversion winding (SIW) structure to enforce a 180° phase voltage opposition between adjacent turns. While capacitor segmentation is a known method for E-field reduction, this work is the first to systematically evaluate its effects across both conventional and phase-inverted coils. The findings reveal that capacitor placement serves as a topology-dependent design parameter. Finite Element Method (FEM) simulations and experimental validation show that while capacitor placement has a moderate influence on traditional coils due to in-phase voltage relationships, AVPC coils are highly sensitive to segmentation patterns. When capacitors align with the SIW phase structure, destructive interference significantly reduces E-field emissions. Improper capacitor placement disrupts phase cancellation and negates this benefit. This study resolves a critical design gap by establishing that distributed compensation acts as a tuning mechanism in conventional coils but becomes a primary constraint in phase-inverted topologies. The results demonstrate that precise capacitor placement aligned with the coil topology significantly enhances E-field mitigation up to 60% in AVPC coils, greatly outperforming traditional coil configurations and providing actionable guidance for high-power wireless charging applications. Full article

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. The explicit model—calibrated for variable penetration depth and absorptivity—generates synthetic melt pool data, augmenting 36 experimental samples across conduction, transition, and keyhole regimes for 316 L stainless steel. Three ML methods—Multilayer Perceptron (MLP), Random Forest, and XGBoost—are trained using fivefold cross-validation. The hybrid approach significantly improves prediction accuracy, especially in unstable transition regions (D/W ≈ 0.5–1.2), where morphological fluctuations hinder experimental sampling. The best-performing model (MLP) achieves R² > 0.98, with notable reductions in MAE and RMSE. The results highlight the benefit of incorporating physically consistent, nonlinearly distributed synthetic data to enhance generalization and robustness. This physics-augmented learning strategy not only demonstrates scientific novelty by integrating mechanistic modeling into data-driven learning, but also provides a scalable solution for intelligent process optimization, in situ monitoring, and digital twin development in metal additive manufacturing. Full article

Flexible energy sources such as electric vehicles and the battery energy storage systems of intelligent distribution systems can provide system-wide auxiliary services such as frequency regulation for power systems. This paper proposes an optimal method for operating the local energy community that is based on two-stage scheduling. Firstly, the basic concepts of the local energy community and flexible service are introduced in detail. Taking LEC as the reserve unit of artificial frequency recovery, an energy information interaction model among LEC, balance service providers, and the power grid is established. Then, a two-stage scheduling framework is proposed to ensure the rationality and economy of community energy scheduling. In the first stage, day-ahead scheduling uses the energy community management center to predict the up/down flexibility capacity that LEC can provide by adjusting the BESS control parameters. In the second stage, real-time scheduling aims at maximizing community profits and scheduling LEC based on the allocation and activation of standby flexibility determined in real time. Finally, the correctness of the two-stage scheduling framework is verified through a case study. The results show that the control parameters used in the day-ahead stage can significantly affect the real-time profitability of LEC, and that LEC benefits more in the case of low BESS utilization than in the case of high BESS utilization and non-participation in frequency recovery reserve. Full article

Background: The implementation of intravenous thrombolysis (IVT) and mechanical thrombectomy (MT) in acute ischemic stroke (AIS) has proven effective, offering significant benefits for patient outcomes. We therefore investigated trends in the implementation of IVT and MT in Germany between 2015 and 2023. Methods: We conducted a retrospective analysis using German Diagnosis-Related Group (DRG) statistics from 2015 to 2023. Treatment numbers were analyzed annually based on OPS codes. We examined the age and sex distribution of patients undergoing these treatments. Additionally, we analyzed all hospital cases coded with ICD-10 for acute ischemic stroke (AIS). Results: Between 2015 and 2023, the number of AIS cases in Germany slightly declined from 250,802 to 248,107 (−1.1%), with the largest annual decrease (−4.3%) occurring during the COVID-19 pandemic (2019–2020). Despite this, the use of IVT increased from 40,766 cases (16.25%) in 2015 to 48,378 (19.50%) in 2023. MT usage rose even more sharply, from 7840 cases (3.13%) to 22,445 (9.05%). Among MT recipients, the proportion of patients aged ≥80 years rose significantly, from 27.2% to 42.1%. In this age group, women consistently comprised the majority of MT patients—65.4% in 2015 and 65.5% in 2023. Conclusions: Despite a stable stroke incidence, the use of IVT—and particularly MT—continued to increase in Germany from 2015 to 2023, even during the COVID-19 pandemic. MT usage nearly tripled, especially among patients aged ≥80 years. These trends highlight a resilient stroke care system and underscore the need for future planning to meet the rising demand for endovascular treatment in an aging population. Full article