Search Results (1,930)

Shielding gas flow in metal Laser Powder Bed Fusion (PBF-LB/M) removes ejecta and byproducts from the build plate and the optical path, preventing laser interference and loss of part quality. Previous research conducted on an EOS M290 used Magnetic Resonance Velocimetry (MRV) to resolve the three-component, three-dimensional flow field and identified a region of recirculation below the lower vent. The present work demonstrates the correction of this recirculation through practical chamber modifications: raising the build platform and optical assembly, and redesigning the recoater and the lower inlet to reflect the new build plate position. MRV was leveraged to generate flow distribution maps and velocity profiles of the modified configuration, showing a marked change in the overall flow field. Plate scans across the build area characterized the impact of gas flow improvements on process response. Specimens from the original configuration showed progressively shallower melt pools toward the vent, whereas those from the modified configuration exhibited a ~10% higher average melt pool depth in the region most affected by prior recirculation. Qualification artifacts built under both conditions provided preliminary evidence of improved part performance via enhanced gas flow distribution. These results highlight potential benefits of uniform gas flow distribution across the build plate through simple EOS M290 chamber modifications. Full article

The rapid increase in global data generation has intensified the demand for magnetic storage systems with substantially higher areal density. Double-layer bit-patterned media recording (DLBPMR), which integrates the benefits of bit-patterned media recording (BPMR) and double-layer magnetic recording (DLMR), provides a promising pathway by combining nanoscale patterned islands with multilayer recording structures. However, severe two-dimensional intersymbol interference (ISI) within each layer, together with interlayer interference (ILI) between stacked layers, continues to present significant challenges for reliable data detection. To address these issues, this work investigates and advances the structure of DLMR to improve signal separation and recovery. In particular, we emphasize that detection plays a crucial role in mitigating both ISI and ILI. Accordingly, we propose a maximum a posteriori (MAP) detection scheme derived for a newly developed generalized two-layer partial-response (PR) model that accurately characterizes intra-layer ISI and cross-layer interference coupling. A parallel detection architecture is designed and employed for the upper and lower layers of the DLMR system, enabling the exchange of extrinsic information and enhancing MAP detection performance. Simulation results demonstrate that the proposed PR modeling and MAP-based detection framework achieves significant bit error rate (BER) improvements over existing detection methods, highlighting its strong potential for next-generation ultra-high-density DLBPMR systems. Full article

This paper proposes a coordinated planning method for distribution network lines considering geographical constraints and load distribution, aiming to improve the economy and engineering feasibility of distribution network planning. First, a hierarchical system of geographical constraints based on the Interval Analytic Hierarchy Process (IAHP) is established to systematically quantify the influence weights of spatial factors such as terrain undulation, ecological protection zones, and construction obstacles. Second, the density peak clustering algorithm and load complementarity coefficient are introduced to generate equivalent load nodes, and a spatially continuous load density grid model is constructed to accurately characterize the distribution and complementary characteristics of the load. Third, an improved A-star algorithm is adopted, which integrates a heuristic function guided by geographical weights and load density to dynamically avoid high-cost areas and approach high-load areas. Additionally, Bézier curves are used to optimize the path, reducing crossings and obstacle interference, thus enhancing the implementability of line layout. Verification via a real distribution network case study in a certain area of Guangdong Province shows that the proposed method outperforms traditional planning strategies. It significantly improves the economy, safety, and engineering feasibility of the path, providing effective decision support for distribution network line planning in complex environments. Full article

To address interlayer interference during multi-layer commingled production in gas reservoirs with pressure differences, this study investigates the low-permeability gas reservoir in the central Linxing area of the Ordos Basin. High-temperature, high-pressure physical simulation experiments were conducted to systematically study single-layer, two-layer, and three-layer commingled production under different pressures (13, 15, and 17 MPa). A large-scale physical simulation system, capable of withstanding 100 °C and 50 MPa, was constructed for the dynamic monitoring of multi-layer commingled production. This system accurately characterized the instantaneous gas production, cumulative gas production, and pressure drop behavior of individual layers under both single-layer and commingled production conditions. The results indicate that significant interlayer interference occurs during multi-layer commingled production. This interference is primarily manifested as a capacity inhibition effect, where the high-pressure layer suppresses the production of the low-pressure layer. Typical phenomena accompanying this effect include ‘backflow’ and ‘staggered production peaks’. Quantitative analysis indicates that the cumulative gas production for two-layer and three-layer commingled production is 3.2% and 9.06% lower, respectively, than the summed production from equivalent single-layer operations. Notably, in the three-layer commingled production scenario, the productivity of the low-pressure layer (Q5) was reduced by 19.87%, a significantly greater loss compared to the 4.39% reduction observed in the high-pressure layer (T2). Furthermore, the study demonstrates that the severity of interlayer interference is positively correlated with the interlayer pressure difference. Additionally, as the number of commingled layers increases, the interference effect exhibits a superimposed enhancement characteristic. Full article

Synthetic cathinones such as 3,4-methylenedioxypyrovalerone (MDPV) are potent psychostimulants with high abuse potential, yet their systemic toxicity and neurobehavioral effects remain poorly characterized during early development. Using Danio rerio (zebrafish) embryos and larvae, we performed an integrated assessment of the cardiotoxic, behavioral, and molecular effects of MDPV. Acute exposure of 3 days post-fertilization (dpf) embryos produced a marked, concentration-dependent bradycardia and atrioventricular (AV) conduction block, leading to reduced ventricular activity and complete AV dissociation at the highest concentrations (EC₅₀ = 228 µM). Quantitative analysis of ventricular motion revealed a significant decrease in cardiac output (CO) at all tested concentrations and a reduction in ejection fraction (EF) only at 480 µM, while fractional shortening (FS) and stroke volume (SV) remained unchanged, indicating predominant chronotropic and conduction effects with secondary contractile impairment. In 5 dpf larvae, MDPV caused a sustained, concentration-dependent decrease in basal locomotor activity (EC₅₀ = 2.51 µM) but did not affect prepulse inhibition (PPI) of the acoustic startle response (ASR), unlike dextroamphetamine, which enhanced PPI via dopaminergic D₂ receptor activation. Short-term (2 h) exposure of 3 dpf embryos to 0.4–400 µM MDPV induced transcriptional changes in dopaminergic and stress-responsive genes, whereas expression of major repolarizing potassium channel genes (kcnh6a and kcnq1) remained unaltered. Collectively, these results demonstrate that MDPV exerts potent negative chronotropic effects likely through direct functional interference with cardiac repolarization, while neurobehavioral effects occur at concentrations nearly two orders of magnitude lower than cardiotoxic thresholds, supporting zebrafish as a predictive model for the integrative assessment of psychostimulant toxicity. Full article

Background: Infections caused by the multidrug-resistant pathogen Mycobacterium abscessus (Mab) are notoriously difficult to treat. The novel β-lactamase inhibitor durlobactam, in combination with β-lactams, shows potent bactericidal activity against Mab, but the potential for acquired resistance remains a clinical concern. Objectives: To identify and characterize mechanisms of acquired resistance to durlobactam in Mab. Methods: In vitro single-step resistance selection was performed by plating wild-type Mab ATCC 19977 and by transcriptional silencing using a CRISPR interference (CRISPRi) system. Minimum inhibitory concentrations (MICs) were determined by both an agar-based method and broth microdilution. Results: Whole-genome sequencing of durlobactam-resistant mutants identified loss-of-function mutations in ponA1, a gene encoding a class A penicillin-binding protein involved in cell wall synthesis. Targeted deletion of ponA1 (ΔponA1) and CRISPRi-mediated knockdown of ponA1 expression both recapitulated the resistance phenotype, resulting in a significant increase in the durlobactam MIC on solid agar media. Strikingly, broth microdilution MICs remained largely unaffected. Conclusions: Inactivation of the peptidoglycan synthase PonA1 is a novel mechanism of resistance to durlobactam in Mab that is phenotypically expressed only during growth on solid surfaces. This finding identifies a specific genetic pathway for resistance and highlights that standard broth-based susceptibility testing could miss clinically relevant resistance mechanisms. Full article

The indoor low-voltage power line network is characterized by highly irregular interferences, where background noise coexists with bursty impulsive noise originating from household appliances and switching events. Traditional noise models, which are considered monofractal models, often fail to reproduce the clustering, intermittency, and long-range dependence seen in measurement data. In this paper, a Multifractal Random Walk (MRW) framework tailored for Power Line Communication (PLC) noise modelling is developed. MRW is a continuous time limit process based on discrete-time random walks with stochastic log-normal variance. As such, the formulated MRW framework introduces a stochastic volatility component that modulates Gaussian increments, thus generating heavy-tailed statistics and multifractal scaling laws which are consistent with the measured PLC noise data. Empirical validation is carried out through structure function analysis and covariance of log-amplitudes, both of which reveal scaling characteristics that align well with MRW-simulated predictions. This proposed model captures both the bursty nature and correlation structure of impulsive PLC noise more effectively as compared to the conventional monofractal approaches, thereby providing a mathematically grounded framework for accurate noise generation and the robust system-level performance evaluation of PLC networks. Full article

Pine wilt disease (PWD), caused by the pine wood nematode (PWN) Bursaphelenchus xylophilus, is a devastating pine disease that is characterized by rapid transmission, high lethality, and limited control options. In our previous study, the fucosyltransferase gene (fut) which encoded fucosyltransferase (FUT) was found to be a putative virulence determinant in PWN, which regulates pathogenicity of nematodes. To investigate the functional role of the fut gene in PWN, a comprehensive analysis was conducted to understand its molecular structure and biological activity. The full-length open reading frame (ORF) of fut was amplified using reverse transcription PCR (RT-PCR) and successfully ligated into the pET-28a expression vector. Heterologous expression of the recombinant FUT was achieved in Escherichia coli Rosetta (DE3) through induction with 1.0 mM isopropyl-β-D-thiogalactoside (IPTG), followed by purification via nickel-nitrilotriacetic acid (Ni-NTA) affinity chromatography. Biochemical characterization revealed that the recombinant FUT exhibited optimal enzymatic activity at 30 °C and pH 8.0, respectively. Furthermore, RNA interference (RNAi) validated by RT-qPCR was used to explore the biological functions of fut in PWN, and results indicated that downregulation of the fut gene could significantly reduce the vitality, reproduction, pathogenicity, development, and lifespan of PWN. Furthermore, gallic acid as an inhibitor of FUT displayed a strong inhibitory effect on recombinant FUT activity and nematicidal activity against PWNs in vitro and could alleviate the wilt symptom of pine seedlings inoculated with PWNs at a concentration of 100 μg/mL, indicating that it has the potential to be a novel nematicide. Collectively, these results establish fut as a critical virulence determinant in PWN and highlight its potential as a molecular target for controlling pine wilt disease. Full article

We describe two new species of Paradraconema from subtidal sediments of Korean waters: P. tamraense sp. nov. from Jeju Island and P. gangchii sp. nov. from Dokdo Island. Although the epithet tamraense had appeared previously in the literature, it was treated as a nomen nudum and therefore lacked nomenclatural availability under the ICZN. In this study, the species is newly and validly established based on a critical reassessment of the original material, supported by new line drawings and detailed observations using differential interference contrast (DIC) and scanning electron microscopy (SEM). Paradraconema amraense sp. nov. is characterized by a slender body; pharyngeal annules bearing weakly developed longitudinal bars with smooth margins; a narrow lateral field at midbody; abundant and relatively long somatic setae; a head capsule partially covered with vacuolated ornamentation; an amphidial fovea that is elongate loop-shaped in males and circular, unispiral in females; eleven cephalic adhesion tubes (CAT); and comparatively long sublateral adhesion tubes (SlAT) and subventral adhesion tubes (SvAT). Paradraconema gangchii sp. nov. is characterized by a slender body; cuticle ornamentation with numerous longitudinal bars bearing finely crenulated margins in the pharyngeal region; sparse and short somatic setae; a head capsule fully covered with vacuolar ornamentation (reticulate under SEM); an amphidial fovea that is elongate loop-shaped in males and circular, unispiral, slightly over one coil in females; relatively short spicules (36–46 µm); eleven CAT; and relatively short SlAT and SvAT. SEM revealed several fine morphological features not previously documented in the genus, including the precise number and arrangement of CAT and detailed structures of the cuticle ornamentation and lip region. This study provides comprehensive SEM-based documentation for Paradraconema, increases the number of valid species in the genus to thirteen, and enhances our understanding of draconematid diversity in the northwestern Pacific. Full article

Accurate analysis of trace elements in particulate matter (PM) emitted by brake systems critically depends on the filter selection and handling processes, which can significantly impact analytical results due to contamination and elemental interference from filter elemental composition. This study systematically evaluated two widely used filter types, EMFAB (borosilicate glass microfiber reinforced with PTFE) and Teflon (PTFE), for their suitability in the trace element determination of brake-wear PM₁₀ collected using a tribometer set-up. A total of twenty-three PM₁₀ samples were analyzed, encompassing two different friction materials, to thoroughly assess the performance and analytical implications of each filter type. Filters were tested for their chemical background, handling practicality and potential contamination risk through extensive elemental analysis by inductively coupled plasma–optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS). Additionally, morphological characterization of both filter types was conducted via scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS) to elucidate structural features affecting particle capture and subsequent analytical performance. Significant differences emerged between the two filters regarding elemental interferences: EMFAB filters exhibited substantial background contribution, particularly for alkali and alkaline earth metals (Ca, Na, Mg and K), complicating accurate quantification at trace levels. Conversely, Teflon filters demonstrated considerably lower background but required careful manipulation due to their structural fragility and the necessity to remove supporting rings, potentially introducing analytical variability. Statistical analysis confirmed that the filter material significantly affects elemental quantification, particularly when the collected PM₁₀ mass is limited, highlighting the importance of careful filter selection and handling procedures. Recommendations for optimal analytical practices are provided to minimize contamination risks and enhance reliability in trace element analysis of PM₁₀ emissions. These findings contribute to refining analytical methodologies essential for accurate environmental monitoring and regulatory assessments of vehicular non-exhaust emissions. Full article

This study addresses the challenges associated with transmission electron microscopy (TEM) image analysis of supported nanoparticles, including low signal-to-noise ratio, poor contrast, and interference from complex substrate backgrounds. This study proposes an automated segmentation and particle size analysis method based on a large-scale deep learning model, namely segment anything model (SAM). Using Ru/TiO₂ and related materials as representative systems, the pretrained SAM is employed for zero-shot segmentation of nanoparticles, which is further integrated with a custom image processing pipeline, including optical character recognition (OCR) module, morphological optimization, and connected component analysis to achieve high-precision particle size quantification. Experimental results demonstrate that the method retains robust performance under challenging imaging conditions, with a size estimation error between 3% and 5% and a per-image processing time under 1 min, significantly outperforming traditional manual annotation and threshold-based segmentation approaches. This framework provides an efficient and reliable analytical tool for morphological characterization and structure–performance correlation studies in supported nanocatalysts. Full article

This study applied a guided culturomics workflow to isolate and characterize gut-associated yeasts as probiotic candidates. Culture conditions were optimized using Dixon agar and Modified Schädler Agar with a moderate antibiotic cocktail (colistin, chloramphenicol, vancomycin) to suppress bacteria without impairing yeast growth, combined with incubation at 37 °C under anaerobic conditions to mimic the intestinal environment. From three healthy donors, 305 isolates were recovered (MSA: 193; Dixon: 112). After excluding pseudohyphal morphotypes and PCR positive Candida isolates, 127 non-Candida strains remained. Safety screening (hemolysis, DNase, coagulase) reduced the pool to 26 safe isolates. Simulated gastrointestinal stress tests showed that 20 out of 26 exhibited at least 50 percent survival under pH 2.0 or 0.5% bile salts. Functional assays revealed strain-specific antimicrobial activity against Staphylococcus aureus, Escherichia coli including O157:H7 and Salmonella species, with several isolates (Y6, Y22, Y42, Y48, Y55, Y56, Y73, Y105, Y127) showing broad and strong inhibition. Two isolates Y44 and Y55 further demonstrated robust bile and acid tolerance (>50% survivability) in both conditions. All isolates displayed intracellular but not extracellular bile salt hydrolase activity, indicating a viability dependent cholesterol lowering potential. Overall, the workflow minimized bacterial interference while enriching for safe and functional yeasts. Full article

A new rhodamine-based fluorescent probe (RDC, rhodamine-based derivative) was rationally designed and synthesized for the highly selective, sensitive, and quantitative detection of Cu²⁺. The probe demonstrated outstanding specificity toward Cu²⁺, even in the presence of competing metal ions (e.g., Al³⁺, Fe³⁺, Cr³⁺, Na⁺, and K⁺), exhibiting negligible interference and confirming its robust anti-interference capability. A spectroscopic analysis revealed that Cu²⁺ induced spirocyclic ring cleavage, resulting in a colorless-to-pink colorimetric transition and enhancement of the yellow–green fluorescence at 590 nm. Upon addition of Cu²⁺, the fluorescence spectrum showed a linear response in the concentration range of 0.4–20 μM, with a correlation coefficient (R²) of 0.9907 and the limit of detection (LOD) calculated to be 0.12 μM. Meanwhile, Job’s plot analysis verified that the binding stoichiometry between RDC and Cu²⁺ was 1:1. The probe exhibits rapid response kinetics (<5 min) and non-destructiveness properties, enabling in vivo imaging. Under stress conditions, Cu²⁺ accumulated predominantly in root tips (its primary target tissue), with the following distribution hierarchy: root tips > maturation zone epidermis > xylem vessels > cortical cell walls. In conclusion, RDC is a well-characterized, high-performance tool with high accuracy, excellent selectivity, and superior sensitivity for plant Cu²⁺ studies, and this work opens new technical avenues for rhodamine-based probes in plant physiology, environmental toxicity monitoring, and rational design of phytoremediation strategies. Full article

Sparse Distributed Memory (SDM) provides a biologically inspired mechanism for associative and online learning. Transformer architectures, despite exceptional inference performance, remain static and vulnerable to catastrophic forgetting. This work introduces Continual Associative Learning Model (CALM), a conceptual framework that defines the theoretical base and integration logic for the cognitive model seeking to establish continual, lifelong adaptation without retraining by combining SDM system with lightweight dual-transformer modules. The architecture proposes an always-online associative memory for episodic storage (System 1), as well as a pair of asynchronous transformer consolidate experience in the background for uninterrupted reasoning and gradual model evolution (System 2). The framework remains compatible with standard transformer benchmarks, establishing a shared evaluation basis for both reasoning accuracy and continual learning stability. Preliminary experiments using the SDMPreMark benchmark evaluate algorithmic behavior across multiple synthetic sets, confirming a critical radius-threshold phenomenon in SDM recall. These results represent deterministic characterization of SDM dynamics in the component level, preceding the integration in the model level with transformer-based semantic tasks. The CALM framework provides a reproducible foundation for studying continual memory and associative learning in hybrid transformer architectures, although future work should involve experiments with non-synthetic, high-load data to confirm scalable behavior in high interference. Full article

Civilian Global Navigation Satellite Systems (GNSS) play a crucial role in critical infrastructure and safety-critical applications, where their low signal power and open descriptions make them vulnerable to threats such as jamming and spoofing. To address these major challenges and growing concerns, NovAtel’s OEM7 receivers are equipped with an advanced GNSS Resilience and Integrity Technology (GRIT) to identify and respond to GNSS threats effectively. This includes Interference Toolkit (ITK), Spoofing Detection Toolkit (SK) and Robust Dual-Antenna Receiver (RoDAR), which employ a range of countermeasures, from jamming detection and characterization to spoofing detection and mitigation, ensuring solution integrity and reliability. The newly developed Galileo Open Service Navigation Message Authentication (OSNMA) module also offers an additional layer of protection by checking for the authenticity of the navigation message for Galileo E1 signals. This paper evaluates the performance of NovAtel’s OEM7 receivers in detecting and mitigating jamming and spoofing using real event data. Effective jamming detection was achieved through spectrum monitoring across all GNSS bands. The effectiveness of GRIT’s anti-jamming and anti-spoofing technologies was demonstrated in advanced test cases. OSNMA results are discussed, highlighting its role as a complementary protection layer for enhanced GNSS security. Full article