Search Results (11,145)

The steel industry, a typical energy-intensive sector, experiences significant load power fluctuations, particularly during peak periods, posing challenges to power-grid stability. Traditional studies often overlook its unique production characteristics, limiting a comprehensive understanding of power fluctuations. Meanwhile, air conditioning (AC), as a flexible load, offers stable regulation with an aggregation effect. This study explores the potential for coordinated load dispatch between the steel industry and air conditioning clusters to enhance power system flexibility. A power characteristic model for steel loads was developed based on energy consumption patterns, while a physical ETP model aggregated air conditioning loads. To improve forecasting accuracy, a parallel LSTM-Transformer model predicts both steel and air conditioning loads. CEEMDAN-VMD decomposition reduces noise in steel-load data, and the QR algorithm computes confidence intervals for load responses. The study further examines interactions between electric-arc furnace control strategies and air conditioning demand response. Case studies using real-world data demonstrate that the proposed model enhances prediction accuracy, peak suppression, and variance reduction. These findings provide insights into steel industry power fluctuations and large-scale air conditioning load adjustments. Full article

High-precision angular contact ball bearings (ACBBs) are critical components in advanced manufacturing equipment, where rotation accuracy directly determines system performance and stability. Considering error superposition and equipment processing capability comprehensively, this study establishes an error analysis and control model of the ACBBs, studies the error transmission law, and puts forward a rotation accuracy control strategy for batch manufacturing of precision ACBBs. The ACBBs 7020C/P4, 7020AC/P4, 7020A/P4, and 7020B/P4 (four conventional contact angles of 15°, 25°, 30°, 40°) were taken as examples to verify the experiment. The error of the calculation compared with actual test results was not more than 7.5%, which had good accuracy and practicability. The research shows that the roundness error of bearing raceway, the thickness difference in bearing ring wall, and the parallelism error of raceway to end face were the main influencing factors of bearing rotation accuracy Kia, Sia, Kea, and Sea. The influence coefficient of raceway roundness error on the axial runout of bearing (Sia, Sea) decreased rapidly with the increase in contact angle, while the influence coefficient on radial runout (Kia, Kea) remained constant. The rotation accuracy error of the outer ring was always greater than that of the inner ring, and this law was not affected by the contact angle. Moreover, with the increase in contact angle, the radial runout of the inner and outer rings of the bearing increased. During actual machining, bearings with larger contact angle place lower demands on the equipment process capability index (Cp), particularly on the parameter Cer. This reduction in required capability is equivalent to an effective Cp improvement of about 30%. Full article

Under the context of “Energy Conservation and Emission Reduction,” low-sulfur fuel has become widely adopted in maritime operations, posing significant challenges to cylinder lubrication systems. Traditional oil injection strategies, heavily reliant on manual experience, suffer from instability and high costs. To address this, a lightweight image retrieval model for cylinder lubrication is proposed, leveraging deep learning and computer vision to support oiling decisions based on visual features. The model comprises three components: a backbone network, a feature enhancement module, and a similarity retrieval module. Specifically, EfficientNetB0 serves as the backbone for efficient feature extraction under low computational overhead. MobileViT Blocks are integrated to combine local feature perception of Convolutional Neural Networks (CNNs) with the global modeling capacity of Transformers. To further improve receptive field and multi-scale representation, Receptive Field Blocks (RFB) are introduced between the components. Additionally, the Convolutional Block Attention Module (CBAM) attention mechanism enhances focus on salient regions, improving feature discrimination. A high-quality image dataset was constructed using WINNING’s large bulk carriers under various sea conditions. The experimental results demonstrate that the EfficientNetB0 + RFB + MobileViT + CBAM model achieves excellent performance with minimal computational cost: 99.71% Precision, 99.69% Recall, and 99.70% F1-score—improvements of 11.81%, 15.36%, and 13.62%, respectively, over the baseline EfficientNetB0. With only a 0.3 GFLOP and 8.3 MB increase in model size, the approach balances accuracy and inference efficiency. The model also demonstrates good robustness and application stability in real-world ship testing, with potential for further adoption in the field of intelligent ship maintenance. Full article

Background: Human care represents the essence of nursing but faces challenges from increasing technological advancement and healthcare system bureaucratization. Objective: To understand how nursing students balance technical demands with human aspects of care during pre-professional practice experiences. Methods: An interpretive phenomenological study was conducted with 17 nursing students (12 women, 5 men) in their eighth and ninth semesters from a public university in northern Ecuador. The data were collected through focused interviews during the first quarter of 2025. Analysis followed a four-stage phenomenological process: epoché, phenomenological reduction, eidetic reduction, and transcendental reduction, culminating in phenomenological interpretation. Data saturation was achieved, and methodological rigor criteria were applied including triangulation with external analysts. Results: Six main strategies emerged that students develop to balance technical demands with humanized care: Time Management and Optimization, Integration of Human and Technical Dimensions, Patient Communication About Time Constraints, Emotional Regulation and Boundary Setting, Resistance to Dehumanization, and Institutional Context Adaptation. Students transform technical procedures into therapeutic opportunities and develop resilient competencies that preserve nursing’s humanistic values. Conclusions: Nursing students develop integrative competencies that balance technical excellence with human sensitivity. Curriculum modifications are needed to include specific competencies in emotional regulation, therapeutic communication, and dehumanization resistance strategies. Full article

Soil salinity and water scarcity are major challenges limiting agricultural productivity in arid and semi-arid regions. Quinoa (a climate-resilient crop) offers potential for sustainable food production under these harsh conditions; however, its growth and yield are often constrained by salt and water stress. This study evaluated the role of plant-growth-promoting rhizobacteria (PGPR) in enhancing Chenopodium quinoa Willd performance under deficit irrigation (DI) with saline water. A greenhouse pot experiment was conducted with four irrigation levels (40%, 60%, 80%, and 100% of the growth water requirement, GWR) and two water qualities (fresh water, EC = 0.8 dS m⁻¹; and saline water, EC = 6.0 dS m⁻¹), each tested with and without PGPR inoculation. The results showed that PGPR application significantly (p < 0.05) improved quinoa tolerance to salinity, leading to higher biomass, yield, and crop water productivity (CWP) under saline irrigation. Yield reductions were most severe at 40% GWR (53.9% and 82.6% under saline and fresh water, respectively), but PGPR inoculation mitigated yield losses, with increases of 83.3% and 130.8% under 40% and 100% GWR saline irrigation, respectively. Notably, PGPR did not show a clear effect with freshwater irrigation. In addition, inoculated plants exhibited improved nutrient uptake and reduced heavy metal accumulation. Overall, PGPR demonstrated strong potential to enhance salinity resilience and water-use efficiency in quinoa. Future studies should extend these findings under field conditions and investigate the long-term impacts of PGPR on sustainable crop production in saline- and water-limited environments. Full article

Accurate forecasting of cellular traffic in non-stationary environments remains a formidable challenge, as real-world traffic patterns dynamically evolve, emerge, and vanish over time. To tackle this, we propose a novel meta-learning framework, GMM-SCM-DCM, which features a Dynamic Component Management (DCM) mechanism. This framework employs a Gaussian Mixture Model (GMM) for probabilistic meta-feature representation. The core innovation, the DCM mechanism, enables online structural evolution of the meta-learner by dynamically splitting, merging, or pruning Gaussian components based on a bimodal similarity metric, ensuring sustained alignment with shifting data distributions. A Single-Component Mechanism (SCM) is utilized for precise base learner initialisation. To ensure a rigorous and realistic validation, we reconstructed the Telecom Italia Milan dataset by applying unsupervised clustering and meta-feature engineering to identify and label four distinct functional zones: residential, commercial, mixed use, and crucially, non-stationary areas. This curated dataset provides a critical testbed for non-stationary forecasting. Comprehensive experiments demonstrate that our model significantly outperforms traditional methods and meta-learning baselines, achieving a 9.3% reduction in MAE and approximately 70% faster convergence. The model’s superiority is further confirmed through extensive ablation studies, robustness tests across base learners and data scales, and successful cross-dataset validation on the Shanghai Telecom dataset, showcasing its exceptional generalization capability and practical utility for real-world network management. Full article

Laying hens in the late laying period often experience reduced productivity and declining egg and meat quality, which limits breeding efficiency and resource utilization. This study aimed to evaluate the effects of multi-component Botanical Crude Extracts (BCEs) on egg and meat quality, metabolic health, and gut microbiota in aged laying hens. A total of 4320 hens were supplemented with 0.3% BCEs for 100 days, with evaluations at 60 and 100 days. BCE supplementation significantly enhanced egg flavor by promoting aromatic and fat-soluble volatiles and reducing odorous compounds (p < 0.05). BCEs improved yolk nutrition by enriching n-3 polyunsaturated fatty acids, especially docosahexaenoic acid (DHA), and optimizing the n-6/n-3 ratio (p < 0.05). A moderate reduction in amino acids was observed, which may reduce bitterness and ammonia burden (0.05 ≤ p < 0.10, trend). In muscle, BCEs improved protein–fat distribution, increased intramuscular fat, and enhanced flavor-related metabolites, significantly improving meat quality of culled hens (p < 0.05). BCEs also reshaped gut microbiota, reducing harmful taxa and promoting short-chain fatty acid and aromatic metabolite biosynthesis (p < 0.05). Serum metabolomics revealed modulation of AMPK, calcium, and cholesterol pathways, improving antioxidant capacity and lipid regulation (p < 0.05). Correlation analyses linked beneficial bacteria and metabolites with yolk DHA levels and flavor (p < 0.05). Overall, BCEs enhanced egg and meat quality and physiological health, providing guidance for functional feed strategies in aged laying hens. Full article

Driving in snowy conditions challenges both human drivers and autonomous systems. Snowfall and ice accumulation impair vehicle control and affect driver perception and performance. Road markings are often obscured, forcing drivers to rely on intuition and memory to stay in their lane, which can lead to encroachment into adjacent lanes or sidewalks. Current lane detectors assist in lane keeping, but their performance is compromised by visual disturbances such as ice reflection, snowflake movement, fog, and snow cover. Furthermore, testing these systems with users on actual snowy roads involves risks to driver safety, equipment integrity, and ethical compliance. This study presents a low-cost virtual reality simulation for evaluating winter lane detection in controlled and safe conditions from a human-in-the-loop perspective. Participants drove in a simulated snowy scenario with and without the detector while quantitative and qualitative variables were monitored. Results showed a 49.9% reduction in unintentional lane departures with the detector and significantly improved user experience, as measured by the UEQ-S (p = 0.023, Cohen’s d = 0.72). Participants also reported higher perceived safety, situational awareness, and confidence. These findings highlight the potential of vision-based lane detection systems adapted to winter environments and demonstrate the value of immersive simulations for user-centered testing of ADASs. Full article

The prolonged retention of senescent branches and needles (canopy litter) in Cunninghamia lanceolata canopies is an evolutionary adaptation, yet its impacts on stand microenvironment and understory succession remain poorly quantified. To address this gap, we conducted a 5-year field experiment across six planting densities (1800, 2400, 3000, 3600, 4200, and 4800 trees·ha⁻¹), aiming to evaluate the effects of canopy litter removal on canopy structure, forest light environment, and understory biodiversity. Results demonstrated that leaf area index (LAI) and mean tilt angle of the leaf (MTA) significantly increased with density (p < 0.05), leading to marked reductions in photosynthetic photon flux density (PPFD) and light transmittance (T). Canopy litter removal significantly reduced LAI across all densities after 4–5 years (p < 0.05) and consistently enhanced PPFD and transmittance (p < 0.01). MTA and light quality parameters (red:blue and red:far-red ratios) both exhibited variable responses to litter removal, driven by density and time interactions, with effects diminishing over time. Understory vegetation diversity exhibited pronounced temporal dynamics and density-dependent responses to canopy litter removal, with increases in species richness (S), Simpson diversity (D), and Shannon–Wiener diversity (H), while Pielou Evenness (J) responded more variably. The most notable increase in species richness occurred in the 4th year, when 21 new species were recorded, largely due to the expansion of light-demanding bamboos (e.g., Indocalamus tessellatus and Pleioblastus amarus), heliophilic grasses (e.g., Lophatherum gracile) and pioneer ferns (e.g., Pteris dispar and Microlepia hancei). Correlation analyses confirmed PPFD as a key positive driver of all diversity indices (p < 0.01), whereas LAI was significantly negatively correlated with PPFD, light transmittance, and understory diversity (p < 0.01). These findings demonstrate that strategic management of canopy litter incorporating stand density regulation can improve understory light availability, thereby facilitating heliophilic species recruitment and biodiversity enhancement in subtropical coniferous plantations. Full article

Combined Cycle Power Plants (CCPP) suffer from drops in power and efficiency due to summer time ambient conditions. This power reduction is especially important in regions with extreme summer ambient conditions. Given the substantial investment and labor involved in the establishment and operation of these power plants, mitigating power loss using various methods emerges as a promising solution. In this context, the integration of Concentrated Solar Power (CSP) technologies has been proposed in this research not primarily to improve the overall performance efficiency of power plants as other recent studies entail, but to ensure continuous power generation throughout summer days, improving stability. This research aims to address this issue by conducting an extensive study covering the different scenarios in which Concentrated Solar Power (CSP) can be integrated into the power plant. Multiple scenarios for integration were defined including CSP integration in the Heat Recovery Steam Generator, CSP-powered chiller for Gas Turbine Compressor Cooling and Gas Turbine Combustion Chamber Preheating using CSP, and scenarios with inlet air fog cooling and hybrid scenarios were studied. This systematic analysis resulted in the selection of the scenario where the CSP is integrated into the combined cycle power plant in the HRSG section as the best case. The selected scenario was benchmarked against its equivalent model operating in Seville’s ambient conditions. By comparing the final selected model, both Yazd and Seville experience a noticeable boost in power and efficiency while reaching the maximum integration capacity at different reflector lengths (800 m for Seville and 900 m for Yazd). However, both cities reach their minimum fuel consumption at an approximate 300 m total reflector length. Full article

Background: Managing pain with intrathecal infusion pumps has significantly improved the treatment of individuals whose pain is uncontrollable by other methods. Using ultrasound to locate the refill port of these infusion pumps may offer an improvement over traditional methods. Objective: The objective of this systematic review is to update existing knowledge on the use of ultrasound for locating the refill port in intrathecal infusion pumps. Methods: The PRISMA review protocol was followed, and the review was registered in PROSPERO under registration number CRD 42024595671. Results: The main findings indicate that this technique is primarily used only in complex cases where access is difficult. Pain assessment, patient satisfaction, and recharge time compared to the traditional method are crucial factors for selecting the type of process to implement. Conclusions: No conclusive data are presented regarding the technique’s effect on pain reduction, patient satisfaction, reduction in time spent refilling the pump, or the prior experience level of the professional performing it, but notable improvements in these aspects are observed in certain situations. Full article

Open reduction and internal fixation (ORIF) for mandibular condyle fractures remains a controversial and challenging issue, with the exception of basal and low-neck fractures. Currently, there is a consensus that fractures causing irreparable malocclusion or dislocation, when the fracture line runs through the base or lower neck of the condyle, require ORIF. Due to the different characteristics of fractures, various surgical approaches and their modifications are available. The use of a minimally invasive intraoral approach during endoscope-assisted procedures is considered safer for the facial nerve and provides good esthetic results without facial scarring. This study aimed to compare two surgical approaches—retromandibular and intraoral—to examine post-operative outcomes and to guide surgical decision-making in the treatment of simple fractures of the base and low-neck condylar process of the mandible. Forty-nine patients (thirteen female, thirty-six male) were analyzed: eighteen were treated with the intraoral approach, and thirty-one with the retromandibular approach. There were no statistical differences in the duration of surgery, but intraoperative blood loss was significantly lower in patients treated endoscopically compared with those treated with an extraoral approach. Post-operative facial nerve and TMJ function were comparable in both groups. The endoscope-treated patients were at a higher risk of fracture non-union, but these findings should be considered with connection with the small sample size. The intraoral approach is a valuable option for basal or low-neck fractures but demands significant surgical experience due to its technical complexity. Full article

Background/Objectives: Trophoblast cell surface antigen 2 (Trop2), a transmembrane glycoprotein overexpressed in a broad spectrum of epithelial malignancies but minimally expressed in normal tissues, has emerged as a clinically relevant prognostic biomarker and therapeutic target, particularly in breast cancer. This study aims to develop an enhanced way of targeting Trop2 expression in tumors and blocking it using extracellular vesicles (EVs) bioengineered to express a nanobody sequence against Trop2 (NB60 E). Methods: Here, a plasmid construct was designed to express the Trop2 sequence, NB60, flanked with HA tag and myc epitope and a PDGFR transmembrane domain in the C-terminal region, and was transfected into HEK293T cells for EVs isolation. The potency of NB60 E to knock down Trop2 in letrozole-resistant breast cancer cells (LTLT-Ca and MDA-MB-468 cells) was initially investigated. Thereafter, the effects of NB60 E on the cell viability and downstream signaling pathway of Trop2 via MTT assay and Western blotting were determined. Lastly, we also examined whether NB60 E treatment in Jurkat T cells affects IL-6, TNF-α, and IL-2 cytokine production by enzyme-linked immunosorbent assay (ELISA). Results: Results revealed treatment with NB60 E significantly reduced surface Trop2 expression across both cell lines by 23.5 ± 1.5% in MDA-MB-468, and 61.5 ± 1.5% in LTLT-Ca, relative to the HEK293T-derived control EVs (HEK293T E). NB60 E treatment resulted in a marked reduction in LTLT-Ca cell viability by 52.8 ± 0.9% at 48 h post-treatment. This was accompanied by downregulation of key oncogenic signaling molecules: phosphorylated ERK1/2 (p-ERK 1/2) decreased by 30 ± 4%, cyclin D1 by 67 ± 11%, phosphorylated STAT3 (p-STAT3) by 71.8 ± 1.6%, and vimentin by 40.8 ± 1.4%. ELISA analysis revealed significant decreases in IL-6 (−57.5 ± 1.5%, 7.4 ± 0.35 pg/mL) and TNF-α (−32.1 ± 0.3%, 6.1 ± 1.2 pg/mL) levels, coordinated by an increase in IL-2 secretion (22.1 ± 2.7%, 49.2 ± 1.1 pg/mL). Quantitative analysis showed marked reductions in the number of nodes (−45 ± 4.4%), junctions (−55 ± 3.5%), and branch points (−38 ± 1.2%), indicating suppression of angiogenic capacity. In vivo experiment using near-infrared Cy7 imaging demonstrated rapid and tumor-selective accumulation of NB60 E within 4 h post-administration, followed by efficient systemic clearance by 24 h. The in vivo results demonstrate the effectiveness of NB60 E in targeting Trop2-enriched tumors while being efficiently cleared from the system, thus minimizing off-target interactions with normal cells. Lastly, Trop2 expression in LTLT-Ca tumor xenografts revealed a significant reduction of 41.0 ± 4% following NB60 E treatment, confirming efficient targeted delivery. Conclusions: We present a first-in-field NB60 E-grafted EV therapy that precisely homes to Trop2-enriched breast cancers, silences multiple growth-and-invasion pathways, blocks angiogenesis, and rewires cytokine crosstalk, achieving potent antitumor effects with self-clearing, biomimetic carriers. Our results here show promising potential for the use of NB60 E as anti-cancer agents, not only for letrozole-resistant breast cancer but also for other Trop2-expressing cancers. Full article

Osteoarthritis (OA) is a degenerative joint disorder characterized by progressive articular cartilage degradation, leading to pain, stiffness, and impaired mobility. This study investigated the anti-osteoarthritic effects of Lindera obtusiloba (LO) leaf extract in primary cultured chondrocytes and a mouse model of destabilization of the medial meniscus (DMM)-induced OA. Mouse primary chondrocytes were treated with IL-1β and various concentrations of LO leaf extract (50–150 μg/mL), and analyzed by RT-PCR, Western blotting, and ELISA. For the in vivo experiments, male C57BL/6 mice underwent DMM surgery and were administered LO leaf extract (50–200 mg/kg/day) for eight weeks, followed by micro-CT, histological, and immunohistochemical analyses. LO leaf extract exhibited no cytotoxicity in chondrocytes. In interleukin-1β-induced inflammatory chondrocytes, LO leaf extract significantly suppressed the expression of OA-associated catabolic factors, including cyclooxygenase-2 (Cox-2), matrix metalloproteinases (MMP3 and MMP13), and phosphorylated nuclear factor-kappa B (NF-κB). It also reduced the production of destructive mediators, such as prostaglandin E₂ (PGE₂) and collagenase, in a dose-dependent manner. In vivo, LO leaf extract-treated mice demonstrated significant reductions in articular cartilage degradation, subchondral bone sclerosis, and the expression of catabolic and inflammatory mediators. Additionally, LO leaf extract administration significantly decreased systemic pro-inflammatory cytokine levels in DMM-induced mice. Collectively, these findings indicate that LO leaf extract attenuates OA progression by suppressing both local and systemic inflammatory responses, supporting its potential as a natural therapeutic agent for the prevention and treatment of OA. Full article

Hydrogen-assisted fatigue cracking presents a critical challenge to the structural integrity of legacy carbon steel natural gas pipelines being repurposed for hydrogen transport, posing a major barrier to the deployment of hydrogen infrastructure. This study systematically evaluates the fatigue crack growth (FCG) behavior of API 5L X60 pipeline steel under varying hydrogen–natural gas (H₂–NG) blending conditions to assess its suitability for long-term hydrogen service. Experiments are conducted using a custom-designed autoclave to replicate field-relevant environmental conditions. Gas mixtures range from 0% to 100% hydrogen by volume, with tests performed at a constant pressure of 6.9 MPa and a temperature of 25 °C. A fixed loading frequency of 8.8 Hz and load ratio (R) of 0.60 ± 0.1 are applied to simulate operational fatigue loading. The test matrix is designed to capture FCG behavior across a broad range of stress intensity factor values (ΔK), spanning from near-threshold to moderate levels consistent with real-world pipeline pressure fluctuations. The results demonstrate a clear correlation between increasing hydrogen concentration and elevated FCG rates. Notably, at 100% hydrogen, API X60 specimens exhibit crack propagation rates up to two orders of magnitude higher than those in 0% hydrogen (natural gas) conditions, particularly within the Paris regime. In the lower threshold region (ΔK ≈ 10 MPa·√m), the FCG rate (da/dN) increased nonlinearly with hydrogen concentration, indicating early crack activation and reduced crack initiation resistance. In the upper Paris regime (ΔK ≈ 20 MPa·√m), da/dNs remained significantly elevated but exhibited signs of saturation, suggesting a potential limiting effect of hydrogen concentration on crack propagation kinetics. Fatigue life declined substantially with hydrogen addition, decreasing by ~33% at 50% H₂ and more than 55% in pure hydrogen. To complement the experimental investigation and enable predictive capability, a modular machine learning (ML) framework was developed and validated. The framework integrates sequential models for predicting hydrogen-induced reduction of area (RA), fracture toughness (FT), and FCG rate (da/dN), using CatBoost regression algorithms. This approach allows upstream degradation effects to be propagated through nested model layers, enhancing predictive accuracy. The ML models accurately captured nonlinear trends in fatigue behavior across varying hydrogen concentrations and environmental conditions, offering a transferable tool for integrity assessment of hydrogen-compatible pipeline steels. These findings confirm that even low-to-moderate hydrogen blends significantly reduce fatigue resistance, underscoring the importance of data-driven approaches in guiding material selection and infrastructure retrofitting for future hydrogen energy systems. Full article