Search Results (313)

Introduction: Although anterior non-infectious uveitis affects the structures of the anterior segment of the eye, (inflammatory) disruption of the hemato–ocular barrier may lead to changes in the structures of the posterior segment of the eye. Objective: To evaluate functional retinal changes using multifocal electroretinography (mfERG) and their relationship with structural optical coherence tomography (OCT) parameters in patients with acute anterior non-infectious uveitis (AANU). Methods: This prospective study included 38 eyes of 19 patients diagnosed with unilateral AANU and age-matched healthy fellow eyes as controls. All subjects underwent comprehensive ophthalmological examination, including best-corrected visual acuity (BCVA), spectral-domain OCT, and mfERG testing at baseline, 3 months, and 6 months. mfERG parameters (amplitude and implicit times) were analyzed alongside central field thickness (CFT), macular volume (MV), and average macular thickness (AMT). Results: Eyes affected by AANU demonstrated a significant reduction in mfERG response amplitude in the central retinal region compared with control eyes, particularly during the acute phase. Although OCT parameters showed partial structural normalization during follow-up, functional recovery was less pronounced in selected retinal regions. Latency values showed minimal variation over time. These findings indicate a potential dissociation between electrophysiological function and structural morphology during disease resolution. Conclusions: Acute anterior uveitis is associated with measurable macular functional impairment detectable by mfERG, even when structural OCT parameters appear relatively stable. These results suggest that inflammatory processes in AAU may extend beyond the anterior segment and transiently affect retinal function. mfERG may therefore serve as a sensitive adjunct tool for detecting and monitoring subclinical macular dysfunction in AANU. Clinical Relevance: Functional retinal impairment may persist despite apparent structural recovery in acute anterior uveitis. Incorporating mfERG into clinical evaluation may improve the detection of subtle macular involvement and enhance understanding of disease dynamics beyond conventional imaging findings. Full article

Aviation maintenance is a high-risk work environment in which worker safety and operational safety must be managed simultaneously. This study develops and validates a dual-domain safety culture framework for aviation maintenance technicians (AMTs) employed by U.S. Part 121 airlines. The framework distinguishes between two complementary dimensions of safety culture: Maintenance Occupational Safety Culture (MOSC), which emphasizes AMTs’ physical safety and protection from workplace hazards, and Maintenance-Based Aviation Safety Culture (MASC), which focuses on organizational practices that prevent maintenance errors and support overall aviation safety. A quantitative survey of AMTs (n = 240) was administered, and data were analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). The measurement model demonstrated acceptable fit indices and reliability. SEM findings indicate that trust has a significant positive effect on both MOSC and MASC, whereas fear exerts a negative effect, though statistically non-significant. These results highlight the central role of trust in strengthening safety culture in aviation maintenance, while suggesting that fear may only marginally undermine safety-related perceptions. The validated framework further emphasizes the importance of psychological safety in enhancing both AMT well-being and operational safety. Overall, this research advances understanding of safety culture in aviation maintenance by treating occupational and aviation safety as distinct yet interrelated domains, offering practical guidance for industry leaders, safety managers, and regulators seeking to improve safety outcomes by cultivating trust. Full article

Background/Objectives: Dutch legislation sets requirements for the safe reporting of and learning from incidents. It also specifies the required competence of nurses in using medical technology. However, not all certified homecare nurses are adequately trained in patient safety. Patient safety management is reflected at different levels within homecare organisations. This study aimed to report on initial consensus among homecare nurses on responsibilities in quality and safety management at organisational, team and individual levels. It also explored nurses’ educational needs related to the use of advanced medical technologies (AMTs) in homecare. Methods: An exploratory qualitative study using consensus-oriented member checking was conducted. Building on research into incidents and safety management practices of AMTs, two semi-structured group interviews were conducted online with 11 homecare nurses from across the Netherlands. In a second round, feedback and comments were solicited on the resulting conclusions and statements in writing. Results: Distinguishing between high-risk and low-risk incident reports enhances the efficiency and effectiveness of safety management for AMTs in homecare. Team-based discussions increase the likelihood of incident reporting. Nurses advocate for periodic, mandatory assessments for technical homecare teams, conducted by an external body. They also emphasise individual responsibility for maintaining up-to-date knowledge and skills and taking action accordingly. Conclusions: In this study, key statements on which Dutch technical homecare nurses reached consensus are presented. The results underscore the importance of a safe organisational and team culture for incident reporting, as well as the need for an effective and efficient incident management system at a team level. An effective learning organisation contributes to enhancing patient safety. Full article

Molecular mechanisms determining pathogenicity of the Dutch elm disease fungus Ophiostoma novo-ulmi are poorly understood. Prior identification of the pathogenicity locus pat1 prompted a chromosome walking approach to elucidate gene function in this region. Among 17 identified genes, ONUg0282 (amtA) was predicted to encode a high-affinity ammonium transporter. In silico analyses confirmed the presence of four additional amt genes (amtB, amtC, amtD, and amtE) in both O. novo-ulmi and the less aggressive O. ulmi and that amtA and amtB belong to the Saccharomyces cerevisiae mep2 clade. The predicted amtA gene product showed features of Mep2-type transceptors, including amino acid residues corresponding to His-168 and His-318 in Escherichia coli AmtB protein, 11 transmembrane helices, and a conserved 22 amino acid motif immediately downstream of the last transmembrane helix. A knockdown amtA mutant with 25% residual expression was significantly less aggressive than wild-type O. novo-ulmi strain H327 when infecting Ulmus americana × U. parvifolia saplings. Predicted AmtA transporters from two CRISPR-Cas9 knockout mutants contained only five intact transmembrane helices. The ΔamtA mutants retained several wild-type phenotypic traits, including yeast–mycelium dimorphism, but were significantly less aggressive than H327 towards U. americana saplings. We concluded that ONUg0282 is an important determinant of aggressiveness in O. novo-ulmi. Full article

Ammonium transporters (AMTs) are a class of membrane-associated proteins that play crucial roles in the uptake and transport of ammonium (NH₄⁺ or NH₃). In this study, an ammonium transporter-encoding gene VviAMT4;1 was isolated and identified from table grape ‘Yanpu No.2’. Notably, the expression level of VviAMT4;1 varied significantly across different organs or tissues of ‘Yanpu No.2’, and the highest expression level was detected in the roots of both tissue-cultured seedlings and 5-year-old mature trees. Expression of VviAMT4;1 was significantly up-regulated under NH₄⁺ depletion throughout the whole of tissue-cultured seedlings. Yeast mutant functional complementation indicates that the recombinant strain pYES2-VviAMT4;1/31019b restored growth under different pH conditions. ¹⁵N isotope-labeled uptake kinetics analysis demonstrated that VviAMT4;1 is a typical high-affinity ammonium transporter, with a Kₘ value of 49.58 ± 4.66 μmol·L⁻¹ and a Vₘₐₓ value of 3.29 μmoles·min⁻¹·μg⁻¹ cells. Moreover, VviAMT4;1 can mediate the weak uptake and utilization of methyl amine (MeA⁺) in yeast cells. The VviAMT4;1-mediated NH₄⁺ uptake process may suffer from feedback inhibition by endogenous NH₄⁺ enrichment. This study provides insights into understanding the molecular mechanisms of N transport and utilization in fruit trees. Full article

Automatic Music Transcription (AMT) plays a fundamental role in Music Information Retrieval (MIR) by converting raw audio signals into symbolic representations such as MIDI or musical scores. Despite advances in deep learning, accurately transcribing piano performances remains challenging due to dense polyphony, wide dynamic range, sustain pedal effects, and harmonic interactions between simultaneous notes. Existing approaches using convolutional and recurrent architectures, or autoregressive models, often fail to capture long-range temporal dependencies and global harmonic structures, while conventional Vision Transformers overlook the anisotropic characteristics of audio spectrograms, leading to harmonic neglect. In this work, we propose SpectTrans, a novel piano transcription framework that integrates a Spectral Gating Network with a multi-head self-attention Transformer to jointly model spectral and temporal dependencies. Latent CNN features are projected into the frequency domain via a Real Fast Fourier Transform, enabling adaptive filtering of overlapping harmonics and suppression of non-stationary noise, while deeper layers capture long-term melodic and chordal relationships. Experimental evaluation on polyphonic piano datasets demonstrates that this architecture produces acoustically coherent representations, improving the robustness and precision of transcription under complex performance conditions. These results suggest that combining frequency-domain refinement with global temporal modeling provides an effective strategy for high-fidelity AMT. Full article

Complex interactions in soil carbon and nitrogen (C-N) synchronisation in tropical perennial orchards are highly responsive to fertiliser chemistry. However, the intensity and stage-specific dynamics of these interactions are not well quantified. Six nitrogen regimes, namely, urea (URT), ammonium (AMT), nitrate (NT), slow-release fertiliser (SRT), bio-organic fertiliser (BFT), and an unfertilised control, were assessed at the vegetative, flowering, fruit-set, and maturity stages of durian cultivated on highly weathered tropical soils. A two-way ANOVA indicated high to very high treatment × phenology interactions for almost all soil properties (p < 0.001), indicating that nutrient responses were highly stage-dependent. The highest soil organic carbon (SOC) and cation exchange capacity (CEC) values were consistently obtained with the BFT, which was often associated with significant differences compared with synthetic treatments. In contrast, the SRT showed the most consistent nutrient release behaviour, especially in flowering. On the other hand, soil pH did not differ significantly among the treatments during the vegetative and maturity stages. A significant decrease in pH was observed for the URT and NT treatments during the flowering stage, indicating temporary acidification at this stage and steep increases in nitrate nitrogen (NO₃^—N), indicating strong nitrification and attenuated carbon (C) stabilisation. Leaf nutrient responses were increased in phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) by 23% in response to the SRT and BFT. The NT and URT tended to enhance leaf nitrogen (N) primarily, and PCA (59–69% variance explained) clearly displayed clustering of the fertiliser effects, with the maximum difference at flowering, the peak period of nutrient demand in the crop. In general, fertiliser chemistry and phenophase jointly controlled the C-N partitioning, soil chemical paths, and nutrient yield correlations. The BFT and SRT showed the greatest significant gains in soil fertility and nutrient retention, making them the best high-performance alternatives in sustainable durian production in tropical systems. Full article

Optimizing stirring methods is crucial for enhancing the efficiency of the Electric Arc Furnace (EAF) production process. This study explores the mixing characteristics of a 150-ton Consteel EAF. The similarity ratio between the water model and the prototype is 1:8. The average mixing time (AMT) was employed as the criterion to evaluate various stirring methods, including the horizontal deflection angle of side-blowing, non-uniform bottom-blowing layouts, and their combinations. A new ice whose composition was a 35 wt% sugar solution was used to simulate the movement and bonding of scrap steel. The melting and temperature difference were compared in this way. The conclusions are as follows: (1) The side blowing lances with a certain angle of horizontal deflection are more conducive to the mixing of the molten pool. The preferred side-blowing lances’ horizontal deflection angle is 10°. (2) The preferred bottom blowing layout is EKO. The bottom blowing layout needs to pay attention to the offset between the bottom blowing nozzles. Bottom blowing nozzles cannot be too far or too close. Rational non-uniform layout of bottom blowing is better than uniform. (3) The preferred combined stirring layout is the EKN, combined with side blowing, with counterclockwise deflection of 10° in the horizontal direction. Gas injection of side blowing and bottom blowing exhibits complementary action zones, thereby achieving enhanced stirring uniformity in the molten bath. But it is necessary to consider the bottom-blowing and side-blowing positions to avoid the local kinetic energy loss caused by airflow offset. At the same time, the deflection angle of the side-blowing lances should be consistent with the direction of the circulation formed by the non-uniform bottom blowing. (4) Under the rational combined stirring method, the scrap steel moved faster, and the bonding phenomenon was significantly reduced. And the temperature difference decreased the fastest. In summary, the rational combined stirring method is the most preferred method for mixing. Full article

To address the technical challenges in exploring concealed high-grade iron deposits in China, this study focuses on Banded Iron Formation, BIF, which represents the largest reserves and hosts the greatest number of large-scale deposits in the country. The Gongchangling iron deposit, a typical high-grade iron deposit in the Anben region, was selected as the main study area. In situ measurements and statistical analysis of the geophysical parameters of rocks and ores were conducted, with an emphasis on evaluating their sensitivity to high-grade magnetite mineralization. Based on this analysis, an integrated gravity, magnetic, and electrical survey method was identified as the optimal exploration approach. Building on this foundation, high-precision gravity and magnetic surveys were performed to investigate the geophysical anomaly response mechanisms of the Gongchangling-type high-grade ores. Forward and inverse modeling were applied to identify deep-seated concealed iron ore bodies, with results further validated by audio-frequency magnetotellurics. This study enhances the methodological framework for mineral exploration, improves prospecting efficiency, and provides practical insights to support new breakthroughs in exploration initiatives. Full article

To address the problem of real-time coordinated control in gear selection and power distribution for hybrid energy storage systems, an adaptive real-time optimal control strategy is proposed in this study. Firstly, a vehicle dynamics model with a hybrid energy storage system and a two-speed mechanical automatic transmission (2AMT) is constructed. Next, a nonlinear optimization problem aiming to minimize battery energy consumption is established. To address the challenge of high computational complexity, polynomial fitting and variable substitution are employed to transform the original nonlinear problem into a convex optimization framework. This transformation enables the control variables to be directly obtained through efficient matrix operations with a global optimal analytical solution, thereby significantly improving computational efficiency. The real-time adaptive control strategy achieves forward-looking coordinated optimization of power distribution and gear selection. The simulation results show that the proposed method can achieve an effect similar to that of dynamic programming (DP) in terms of energy consumption but gains much higher computational efficiency. Compared with the rule-based strategy, the battery energy consumption is reduced by approximately 10%. The method demonstrates advantages both in terms of economy and real-time performance. Full article

As a primary macronutrient, nitrogen is integral to plant growth and regulates their development; ammonium transporters (AMTs) mediate nitrogen absorption and its involvement in metabolism. In this study, nine BcAMT genes were identified in flowering Chinese cabbage (Brassica campestris) and were systematically categorized into two subfamilies. Their evolutionary relationships, conserved motifs, chromosomal distribution, cis-regulatory elements, and expression profiling were systematically characterized. RNA sequencing and quantitative real-time PCR (qRT-PCR) analyses demonstrated that BcAMT1.1 was abundantly expressed in roots, leaves, and stems of flowering Chinese cabbage and was markedly upregulated under nitrogen deficiency. Assessing subcellular location using GFP fusion demonstrated that BcAMT1.1 localized to the plasma membrane. Functional assays identified heterologous expression in the yeast mutant strain 31019b, and transgenic Arabidopsis validated that BcAMT1.1 acted as a functional ammonium transporter. Compared with the wildtype, overexpressing BcAMT1.1 promoted seedling growth, enhanced NH₄⁺ influxes and NO₃⁻ effluxes under low-nitrogen conditions, and significantly increased the transcription levels of key nitrogen assimilation genes (i.e., AtGLN1.1, AtGLN2, AtGDH2). Collectively, our findings enhance the fundamental understanding of BcAMT gene functions and highlight BcAMT1.1 as a crucial component in nitrogen uptake and assimilation under low-nitrogen conditions, providing valuable genetic resources for improving nitrogen efficiency in vegetable crops. Full article

Background: Ammonium nitrogen (NH₄⁺) serves as a vital nitrogen source, playing pivotal regulatory roles in plant growth, development, and high-yield formation. Ammonium transporters (AMTs), encoded by the AMT gene family, are central to NH₄⁺ transport. However, the functional roles of AMT genes in wheat remain poorly understood. Methods: A comprehensive genome-wide analysis of the TaAMT gene family numbers was conducted, encompassing investigations into gene structure, protein motif composition, gene duplication events, collinearity relationships, and cis-acting regulatory elements. Furthermore, the expression patterns of distinct TaAMT members were examined under varying ammonium supply conditions and pathogen stress. Results: In this study, a total of 21 TaAMT members were identified. Additionally, all TaAMT proteins were localized to the plasma membrane. Phylogenetic analysis clustered these genes into four distinct subgroups. Comparative analyses of gene structure and conserved motifs revealed conserved domain composition and motif organization within each subgroup. Interspecific synteny analysis highlighted evolutionary conservation across species. Promoter region analysis identified multiple cis-regulatory elements associated with hormone signaling, light responsiveness, and abiotic stress adaptation. Expression profiling demonstrated that TaAMT members exhibit both tissue-specific and constitutive expression patterns across developmental stages. RT-qPCR further revealed that the expression of TaAMT members responds to varying concentrations of ammonium nitrogen supply, as well as infection stresses caused by stripe rust and powdery mildew. Conclusions: Collectively, this study uncovered the functional diversity of TaAMT members, offering novel molecular targets and theoretical foundations for breeding wheat varieties with enhanced nitrogen use efficiency and disease resistance. Full article

Low Nitrogen Use Efficiency (NUE) remains a critical agricultural challenge, as an estimated 50–70% of applied nitrogen (N) is lost, resulting in negative environmental impacts and reduced crop production. To elucidate molecular mechanism controlling NUE in tomato (Solanum lycopersicum), we conducted a comprehensive genomic, transcriptomic, and functional analysis of the NPF, NRT2, and AMT transporter families under high-N commercial supply conditions. Our integrated analysis identified a shoot-to-root signaling mechanism where the plant’s metabolic performance systematically regulates N transport capacity. Under N sufficiency, the shoot exhibited reduced N assimilation, evidenced by NO₃⁻ accumulation (increased by 55.7%) and reduced Nitrate Reductase (NR) and Glutamine Synthetase (GS) activities (54.0% and 43.2% reduction, respectively), which correlated with a 42.3% reduction in chlorophyll synthesis capacity. This reduction in metabolic demand systematically triggered the downregulation of the key long-distance SlNPF transporters, SlNPF2.13 and SlNPF7.3, restricting N translocation and promoting significant root N accumulation (increased by 41.8%). Our data established that the leaf metabolic state is the systemic regulator of N transport and identified SlNPF2.13 and SlNPF7.3 as pivotal molecular checkpoints. These findings indicate that the manipulation of these transporters could serve as a valuable tool in molecular breeding programs to significantly enhance NUE in commercial tomato varieties. Full article

In this study, we develop a methodology to quantitatively integrate well resistivity logs and audio-magnetotelluric (AMT) sounding in the context of groundwater investigations. The experiments were conducted in a complex Quaternary depositional environment within a region of intensive groundwater use. A synthetic resistivity model was constructed from well resistivity log data and used for forward modelling to generate synthetic AMT responses, which were then inverted using Occam’s algorithm. The AMT-derived resistivity model was subsequently compared with the model obtained from the inversion of the field AMT sounding using the Pearson correlation coefficient (r) and the root mean square error (RMSE). A scalar shift factor (k) was introduced to optimize the match between both models. The comparison between the AMT-derived resistivity model and the well resistivity logs yielded a Pearson correlation coefficient of 0.669 and an RMSE of 0.1911. The optimal scalar shift factor was k = 1.1854, with a 95% confidence interval of [1.1470, 1.2246], indicating only a minor discrepancy. These results demonstrate that AMT can successfully recover a resistivity structure consistent with well resistivity logs. The proposed quantitative integration and validation workflow provides a robust framework to reduce the inherent ambiguity in AMT interpretation and highlights its potential as a direct hydrogeophysical tool for groundwater studies. Full article

In modern industrial systems, diagnosing faults in the rolling bearings of high-speed rotating machinery remains a considerable challenge due to the scarcity of reliable fault samples and the inherent complexity of the diagnostic task. To address these limitations, this study proposes an intelligent fault diagnosis method that integrates a generative adversarial network (GAN) with a convolutional block attention mechanism (CBAM). First, after systematically evaluating several loss functions, a GAN based on the Wasserstein distance loss function was adopted to generate high-quality synthetic vibration samples, effectively augmenting the training dataset. Subsequently, a convolutional block attention mechanism-based convolutional neural network (CBAM-CNN) was developed. By adaptively emphasizing salient features through channel and spatial attention modules, the CBAM-CNN improves feature extraction and recognition performance under limited-sample conditions. To validate the proposed method, an experimental platform for a two-speed automatic mechanical transmission (2AMT) of an electric vehicle was developed, and diagnostic experiments were conducted on high-speed rolling bearings. The results indicate that, under extremely severe conditions, CBAM-CNN achieves a diagnostic accuracy of 96.64% for rolling element pitting defects using only 10% of authentic samples. For composite faults, the model maintains an average accuracy above 97%, demonstrating strong generalization capability. These findings provide solid theoretical support and practical engineering guidance for rolling bearing fault diagnosis under few-shot conditions. Full article