Search Results (19,088)

Battery cell manufacturing is highly energy intensive, with clean and dry rooms being among the largest consumers of electricity and thermal energy. Due to the moisture sensitivity of most advanced cathode materials (e.g., NMC 811) and sulfide-based solid-state materials, production environments must operate at extremely low humidity, requiring energy-intensive HVAC systems to remove moisture introduced mainly by workers and infiltration. To reduce energy consumption, a detailed understanding of the airflow patterns in the room is essential. Because of complex flow patterns (exhaust air demands, energy dissipation), tracer gas techniques using CO₂ as a marker provide an operation-integrated method for determining local air age. The studies presented in this paper apply tracer gas techniques for the first time to a room in which air is almost completely recirculated at high air change rates of approximately 27 h⁻¹, with the supply air being conditioned by removing all process-relevant contaminants such as moisture and particles. Measurements in a separate flow box show successful air age calculations that agree with simplified CFD simulations. For the clean and dry room, the empirical variable relative exposure (REX) was introduced. The measurements indicate an inhomogeneous air distribution inside the room, accompanied with short-circuit flows, partial displacement flow, and mixing, and therefore have the potential to provide a cost-effective first-hand insight into the prevailing airflow patterns. Nevertheless, the presented measurement technique must be further optimized and validated for rooms with air recirculation and high air change rates. Full article

This study investigates the transient mode-locking dynamics and parameter-sensitive pulse evolution in a ytterbium-doped mode-locked fiber laser under near-zero net-dispersion conditions. The influence of gain saturation energy E_s, modulation depth T₀, saturation power P_sat, and non-saturable loss P_ns on transient pulse evolution and mode-locking buildup is comparatively analyzed using the complex Ginzburg–Landau equation. Numerical results indicate that increasing the gain saturation energy E_s weakens the gain saturation effect and prolongs the transient buildup process of stable mode locking, while simultaneously promoting intracavity energy accumulation and spectral broadening through enhanced nonlinear phase evolution. Increasing the modulation depth T₀ accelerates mode-locking initiation through enhanced nonlinear transmission contrast, whereas saturation power P_sat mainly affects the transient intracavity energy accumulation process during pulse evolution. Increasing the non-saturable loss P_ns suppresses low-intensity fluctuations during pulse buildup and contributes to faster gain–loss stabilization inside the laser cavity. Under near-zero net-dispersion conditions, stable picosecond pulse evolution with consistent spectral and temporal characteristics is numerically obtained. The present results provide useful physical insight into gain–loss interaction mechanisms and transient dissipative-soliton dynamics in ultrafast fiber lasers. Full article

Co-firing biomass with coal in existing circulating fluidized bed (CFB) boilers is a promising strategy for reducing net CO₂ emissions and utilizing renewable energy. However, the impact of biomass-blending ratio on the complexity of multiphase flow, combustion characteristics, and pollutant formation inside a full-scale CFB boiler is not fully understood yet. This study developed Eulerian–Lagrangian Multiphase Particle-In-Cell (MP-PIC) model and this model was employed to simulate the co-combustion of coal and rice husk in a 72 MW industrial-scale CFB boiler. The pyrolysis kinetics of the coal and biomass were first measured experimentally via thermogravimetric analyzer and integrated into the model via source terms. The experimentally validated model was further used to investigate the effects of biomass-blending ratio (0–40 wt.%) on hydrodynamics, temperature distribution, and gaseous pollutant emissions (NO, SO₂). Results indicated that biomass addition has a negligible impact on the overall particle flow patterns and particle volume fraction distribution in the boiler. However, it significantly lowered the average furnace temperature due to the lower calorific value of biomass. A blending ratio of 40 wt.% biomass yielded the most substantial reduction in pollutant emissions at the outlet, with decreases of 51.99% for CO₂, 15.70% for NO, and 49.50% for SO₂ compared to single coal combustion. This study presents the MP-PIC model as an efficient numerical framework for optimizing co-firing operations and shows that a high ratio of biomass co-firing (40 wt.%) is technically feasible and environmentally advantageous in existing CFB boilers. Full article

In this work, charge characteristics of submicron heterogeneities (SMH) spontaneously formed in aqueous solutions of various biomolecules: seven amino acids of various types (nonpolar glycine, polar serine, hydrophobic valine, aromatic phenylalanine, sulfur-containing methionine, glutamic acid and basic arginine), ATP, monosaccharide glucose and disaccharide sucrose were studied. The isoelectric points of the SMH in the amino acid solutions determined turned out to be in the pH range from 2.4 to 4, being shifted to the acidic region relative to the isoelectric points of the amino acids themselves (except for glutamic acid). The zeta potential of the SMH was measured in solutions of all the biomolecules under conditions close to the intracellular environment at pH = 7 and basic K⁺ ion content 150 mM. The zeta potential appeared to be negative in all cases. Using these values of the zeta potential, the concentration of OH-anions inside the SMH was estimated, and the pH values corresponding to this concentration turned out to be in the range of 7–10. Since the cell cytosol is an aqueous solution of various biomolecules, SMH must also form inside cells. An analogy is drawn between SMH and membraneless organelles, many of which have been discovered recently. The presence of compact regions with alkaline pH inside the cell is a fundamentally new factor in cell biology, which may have important consequences. Full article

Ensuring the long-term serviceability of nearshore breakwaters constructed on weak seabeds is important for sustainable port infrastructure. This study investigates the wave-induced dynamic response of a vibro-compaction sand-pile composite foundation used in the Jinpai Port breakwater project in Lingao, Hainan, China. A coupled wave–structure–seabed numerical model was established using FssiCAS. Four representative monitoring points were selected inside and outside the structural influence zone and at different burial depths. The displacement, effective stress, shear stress, and pore water pressure responses were analyzed by combining full-field contour distributions with local time-history results. The results show that the foundation response is strongly location-dependent. The maximum horizontal displacement follows the order D > C > A > B, with values of approximately 10.8, 7.6, 0.5, and 0.3 mm, respectively. The final settlement follows the order A > B > C > D, with values of approximately 84, 43, 31, and 19 mm, respectively. Residual pore pressure is more significant beneath the breakwater, especially at Point B. The breakwater toes, structural boundaries, shallow seabed, and improved–natural foundation transition zones are identified as stability-sensitive zones, providing guidance for targeted monitoring, local reinforcement, drainage improvement, and maintenance planning. Full article

This study presents an experimental investigation of reinforced concrete T-beams strengthened using ultra-high-performance concrete (UHPC) with steel plates, and in some cases, UHPC with a geotextile layer. Ten reinforced concrete specimens with the same internal reinforcement but different strengthening methods were tested. These included a control specimen and nine strengthened specimens. Four of the strengthened specimens had grooves in the wooden formwork before pouring to secure the strengthening composite plates inside it, four had it directly attached to the RC beam surface, and the last had vertical lines 10 mm deep to enhance bonding. The external composite plate consisted of four types: the first type included a composite of UHPC and steel plates as strips with 220 × 150 mm at 105 mm, while the remaining types consisted of a plate along the shear zones made of UHPC with steel, geotextiles, or steel and geotextiles. This study also included increasing the number of steel plate layers and the direction of strengthening placement. The results showed that all the strengthened beams failed in flexure, unlike the control specimen, which failed in shear. The strengthening systems improved the load-bearing capacity and overall structural behavior of the tested beams. Among the investigated specimens, beam IR-2S90SS, strengthened with two layers of steel plates, showed the highest improvement, achieving a 39.2% increase in ultimate load compared to the control beam. Debonding was observed in some specimens and was identified as one of the governing failure mechanisms. Overall, the investigated strengthening techniques demonstrated their effectiveness in improving the structural performance of reinforced T-beams. Full article

Accurately locating and reliably diagnosing insulation defects in oil-immersed transformers remains challenging. To overcome this, a micro-robot is employed to autonomously identify partial discharge (PD)-induced carbon traces on the insulation surface of the core components. Accurately capturing the multi-scale complex features of surface-discharge carbon traces under low-illumination conditions is critical for effective defect detection. Therefore, to address the obscurity of carbon trace features caused by insufficient illumination inside oil-immersed transformers, a Retinex-based image enhancement algorithm with superimposed illumination estimation is proposed. By transforming the original image into the HSI color space and integrating negative-image illumination fusion, this algorithm decouples brightness from chromaticity and preserves dark-region details, thereby reducing color distortion and enhancing carbon trace features. Furthermore, to handle the significant scale variations in carbon traces, a C2f module integrated with spatial and channel synergistic attention (SCSA) is designed. This module employs multi-scale depthwise separable convolutions and wide-channel self-attention to enhance cross-scale feature representation and reduce redundancy. Moreover, to address the feature resolution degradation in the fast spatial pyramid pooling module, which hinders the accurate perception of tiny carbon traces, a poly kernel inception atrous spatial pyramid pooling module (PKI-ASPP) is adopted. This preserves precise morphological details and minimizes the missed and false detection rates for tiny carbon traces. Finally, to tackle the difficulties in fusing complex morphological features, a deformable large kernel attention (DLKA) module is introduced into the neck network. This adapts to irregular carbon trace shapes, significantly improving the localization and learning of complex morphologies. Experiments on a transformer PD carbon trace dataset demonstrate that the proposed model significantly improves perceptual capabilities for carbon traces with massive scale variation. The improved model outperforms the baseline across all evaluation metrics, with mAP50 improved by 2.7% and mAP50-95 improved by 7.9%. These results indicate that the proposed method is highly reliable, providing solid technical support for internal surface discharge intensity detection and insulation condition assessment in oil-immersed transformer maintenance. Full article

Resource-constrained electromagnetic interference (EMI) management requires a frequency-domain feedback path, while FFT-based full-spectrum processing introduces redundant computation, storage, and data movement for decision tasks. This paper proposes a limit-aware sparse frequency-domain decision engine for internal EMI risk feedback. The engine redefines EMI analysis from spectrum reconstruction to selective exceedance verification and uses randomized spectral reordering, flat-window bucket aggregation, and folded sampling to compress the length-N spectral search into bucket-level observations. Then, by comparing bucket-level amplitude envelopes with local limit envelopes, the method excludes risk-negative buckets, and only uncertain buckets are further refined through phase localization and sequential verification. Degradation experiments involving continuous background uplift, main-harmonic sidebands, and parasitic resonance clusters clarify the applicability boundary of the proposed method, and measured GaN power-converter spectra acquired through an in situ EMI sensing chain remain inside the empirical usable region. RTL evaluation at 100 MHz shows that the proposed design achieves an average decision latency of 6.031 ms. Compared with two FFT baseline implementations, it reduces BRAM usage by 95.17% and 97.59%, dynamic power by 54.0% and 83.0%, and per-decision dynamic energy by 46.3× and 33.3×, respectively. The results show that the proposed decision engine reduces hardware overhead for frequency-domain EMI risk feedback in resource-constrained systems. Full article

Background: Non-small cell lung cancer (NSCLC) remains one of the leading causes of cancer-related mortality worldwide over the past decade. Single-cell sequencing loses spatial location information and potential cell–cell interactions, making it difficult to interpret molecular features or biological phenomena. Tertiary lymphoid structures (TLSs) inherently require such spatial immune cell distribution information. Although associations between TLS and response to immune checkpoint inhibitors (ICIs) or chemotherapy have been reported, the relationship between TLS and neoadjuvant therapy (ICI combined with chemotherapy) remains unclear. Methods: We performed spatial transcriptomics on NSCLC samples (including one lung squamous cell carcinoma (LUSC) and one lung adenocarcinoma (LUAD)). Multiplex immunohistochemistry (mIHC) was used to identify the TLS, while immunohistochemistry staining (IHC) was used to identify the TLS status and cell characteristics. We evaluated the associations between (mature) TLS density, area proportion and patients’ responses in 66 patients. Results: Heterogeneity of immune cells in NSCLC was found. Gene ontology analysis and cell score comparison identified TLS with activated B and T cells inside, while plasma cells and macrophages were mainly distributed outside TLS. Four genes from antigen-presenting machinery (TAP1, TAP2, B2M, TAPBP) were more highly expressed inside TLS than outside them. Also, TLS exhibited heterogeneity, with both mature and immature TLS. Mature TLS showed an average area of 62,387.43 μm², while the immature TLS showed 51,189.90 μm². The Spearman correlation coefficient of B-cell number and mTLS area showed r = 0.900. TLS density and mature TLS (mTLS) density in the tumor bed were 1.95 ± 0.95 TLS/10 mm² (mean ± SD, n = 34) and 1.13 ± 0.77 mTLS/10 mm², significantly higher than that in the non-responder group (1.18 ± 1.15 TLS/10 mm², 0.70 ± 0.90 mTLS/10 mm², mean ± SD, n = 32) separately. B cells belonging to TLS had a significantly higher density (71.32 ± 55.71 cells/mm², mean ± SD, n = 34) in the responder group than the non-responder group (61.33 ± 111.95 cells/mm², mean ± SD, n = 32) normalized to the tumor bed area. Conclusions: Spatial transcriptomics reveals immune cell heterogeneity and distribution patterns in the NSCLC tumor bed, with activated B and T cells localized inside and plasma cells/macrophages outside. Antigen-presenting machinery (APM)-related genes were highly expressed in TLS accompanied by a high expression of upstream and downstream genes of MHC class I. mTLS have a larger area by mainly containing more B cells. The responder group had a significantly higher (mature) TLS density and larger (mature) TLS area proportion compared with the non-responder group, suggesting their potential function in anti-tumor effect in neoadjuvant treatment. Full article

As a critical insulation component in cable systems, the cable terminal is susceptible to defects caused by human and environmental factors during manufacturing, installation, and service. Such defects may lead to local electric-field distortion and insulation weaknesses at the cable terminal, posing a severe threat to the safe operation of the cable system. In this study, an electric-field simulation model of a 10 kV cable terminal was implemented to investigate the effects of various defects, such as insufficient stress-cone overlap, axial scratch, ring-cut defect, and moisture ingress on the cable terminal. The results show that insufficient stress-cone overlap produces a severe field distortion, and the distortion level is strongly correlated with the misalignment distance. For mechanical damage defects, axial scratches and ring-cut defects mainly distort the electric field inside the air gap, and defect position induces a stronger distortion level than that of defect depth. With increasing ring-cut depth, the maximum value of distorted electric field first decreases and then rises slightly. For moisture defects, the distorted field primarily occurs at the angle between the water-film tip and the stress cone, where the maximum value appears near the XLPE/SIR interface. These results provide a theoretical basis for defect diagnosis, structural optimization, and assembly process control of cable terminals. Full article

Magnetically actuated microrobots have exhibited broad application prospects in biomedical fields. To advance their clinical application, extensive research has attempted to enhance the navigation robustness of microrobots in the body. In the vascular environment, microrobots are easily obscured by blood cells and disturbed by fluid flow, leading to the failure of external sensors and the formation of navigation blind zones. However, most existing navigation methods are based on ideal environment assumptions and struggle to address the challenges posed by navigation blind zones. The study proposes a navigation framework integrating Extended Kalman Filter (EKF) and a Proportional–Integral–Derivative (PID) controller. The EKF fuses sensor measurements and the microrobot kinematic model to sustain continuous state estimation when sensors fail inside blind zones. The simulation results show that this navigation framework achieves pixel-level positioning accuracy under ideal conditions and a 100% navigation success rate. In the presence of blind zone interference, this navigation framework can effectively suppress the divergence of position errors and significantly improve navigation robustness. The study proposes a theoretical framework for microrobot navigation in vascular blind zones. Further physical prototype experiments are required to verify its practical performance. Full article

Insider threats continue to be the most persistent and most destructive threat to cybersecurity; malicious or negligent users work only in the real-time restricted area of the organization and are gradually breaking the boundaries of company norms. Conventional rule-based and statistical detection methods have difficulty detecting inconspicuous, context-dependent, and ever-changing behavior, leading to detection delays and high false-positive rates. Our paper introduces an explainable AI-based Insider-Threat Detection (AIB-ITD) model that integrates enterprise telemetry—including email, web, logon/VPN, and file events—into a unified behavioral framework. The effectiveness of combining heterogeneous behavioral indicators observed in AIB-ITD is consistent with recent behavioral analytics implementations that have demonstrated the value of multimodal user-behavior profiling for insider-threat identification in enterprise environments. The proposed AIB-ITD framework is based on anomaly-driven processing, unsupervised models (Isolation Forest, PCA reconstruction, and Autoencoder) are combined with sequential modeling (with an LSTM Autoencoder) to model both static and temporal deviations in behavior. An ensemble strategy is applied to combine the outputs of these models to yield a probabilistic insider risk score. To improve transparent analysis and to help the analyst gain trust, SHapley Additive Explanations (SHAP) is used to keep every detection outcome transparent and interpretable using the features. It also integrates feature correlation analysis, static vs sequential-model comparisons, and SHAP stability assessment to validate methodological robustness and reproducibility. An experimental review of the hybrid ensemble using the SEI/CMU CERT Insider Threat Dataset reveals that it performs better than single models for anomaly detection and stability, especially with the inclusion of temporal patterns. The assessment prioritizes anomaly score consistency and reliable risk ranking, rather than classification accuracy, to better reflect real deployment scenarios. In addition, an Automated Response and Privilege Containment (ARPC) feature automatically converts risk scores to multilevel mitigation actions that serve to protect the privacy of the user as the least privileged policies are enforced promptly. The proposed model showed superior robustness, stability, and operational effectiveness to classical methods, especially in the presence of scarce labeled data. Through hybrid anomaly recognition, explainable AI and automated response, AIB-ITD is a practical and scalable solution for next-generation insider-threat detection in enterprise systems. Full article

Automated assessment of coronary artery disease (CAD) severity from invasive X-ray angiography is important for diagnostic accuracy, but there are limitations due to limited label data and privacy issues in multi-institutional collaboration. This research proposes a Federated Graph-Transformer Network (FGTN) that models coronary vessel compositions as graphs and uses a transformer unit of measurement to encode global anatomic circumstances for severity scaling. The publicly available X-ray angiography images and SYNTAX-Score dataset will be used, consisting of 232 X-ray coronary angiography images with analogous clinically calculated SYNTAX tons and angiographic factors from 231 patients, manually annotated by a competent cardiologist. The vascular tree is a primary segment that transforms inside the node-edge graph representing bifurcation and vessel sections, continuing topological features, and then processes by graph convolutions integrated with transformer self-attention to capture simultaneously the local stenosis features and global vessel relationships. A Horizontal Federated Learning Strategy allowing collaborative model training on clinical sites without sharing raw data. The intended FGTN achieved overall accuracy of 99.4%, precision of 97.6%, recall of 98.8%, and F1-score of 98.2%, exceeding the usual CNNs, Attention-UNet, and Capsule Connection baselines by a margin of 4–7%. For non-obstructive, mild, moderate, and severe stenosis classes, the AUC values were 0.98, 0.97, 0.96, and 0.95, respectively. Moreover, the Federated Learning framework shows firm convergence with lower, compared to 1.8% performance degradation, when compared to centralized training, and confirms robustness via heterogeneous data distribution. These results show that the proposed solution automatically calculates the CAD severity grading from coronary angiography images. Full article

A Large Language Model-based search for controller synthesis can yield UAV controllers with strong trajectory-tracking performance. However, low tracking error does not necessarily demonstrate closed-loop stability. This study presents a Lyapunov stability assessment of an automatically generated UAV controller produced through a Large Language Model-based search process. The closed-loop system is numerically linearised about the hover equilibrium, yielding a local closed-loop state matrix $A_d$.Eigenvalue analysis is then used to determine whether $A_d$ is Schur stable, corresponding to all eigenvalues lying inside the unit circle $\rho \left(A_d\right)<1$. A quadratic Lyapunov function is constructed by solving the discrete-time Lyapunov equation $A_d^{T}P{A}_d-P=-Q$. The positive definiteness of the resulting matrix provides a local Lyapunov certificate for the linearised closed-loop system. To connect this local certificate to dynamic flight behaviour, the Lyapunov function is evaluated along trajectory-tracking logs using the tracking-error state. The mean Lyapunov value, maximum Lyapunov value, discrete Lyapunov difference, and mean squared error are used to compare the generated controller with PID, LQR, and PID + DOB baselines. The results show that the generated controller satisfies local Lyapunov stability conditions near hover. Our findings demonstrate that established Lyapunov tools can be applied post hoc to a search-generated UAV controller, providing evidence of local stability. Full article

The huge demand for natural sand in the global construction industry has caused resource shortages and severe environmental issues. Meanwhile, China produces massive annual iron tailings, and their stockpiling poses prominent potential safety hazards. At present, numerous investigations have been carried out on the fundamental properties of concrete prepared by replacing natural sand with iron tailings sand (ITS). However, most studies are limited to single replacement ratios and conventional strength mix proportions. Systematic research focusing on high-replacement-ratio systems, long-term durability performance, and supporting practical construction technologies for engineering applications remains insufficient. Obvious gaps still exist regarding the key mechanisms and practical operation standards for high-value and large-scale utilization. Against this background, this paper prepares concrete with three strength grades (C30, C40, C50) and six ITS replacement ratios (0%, 20%, 40%, 60%, 80%, 100%). Cube compressive tests and prism axial compressive tests are conducted, combined with SEM microscopic microstructure analysis. Axial compression tests and bearing capacity research are further carried out on reinforced concrete short columns (RCSC) with the optimal replacement ratio. The results show that concrete compressive strength increases first and then decreases with the rise in iron tailings sand concrete (ITSC), with 60% identified as the optimal replacement ratio. At this ratio, the compressive strength of C30, C40 and C50 concrete increases by 24.3%, 11.5% and 12.9%, respectively, while the bearing capacity of short columns rises correspondingly by 18%, 14.1% and 8.1%. Microscopic test results reveal that ITS exerts both physical filling and chemical active effects. Its fine particles fill internal pores inside the matrix and refine the pore structure. Meanwhile, the reactive mineral components contained in ITS can participate in the hydration reaction of the cementitious system, accelerate the hydration rate and generate more dense hydration products. Therefore, ITS facilitates the hydration process and improves the mechanical properties of concrete. A calculation method for the axial bearing capacity of RCSC incorporating ITS is proposed via theoretical analysis. This study provides a theoretical basis for preparing concrete by replacing natural sand with ITS. Using ITS as aggregate is expected to alleviate tailings stockpiling risks, reduce natural sand consumption, and realize solid waste resource recycling. It also offers valuable references for the green development of the construction industry and safety protection in mining areas. Full article